This above makes me sad. It always makes me sad to see tech companies in litigation in general and in IP litigation specifically. This compounds when any company seeks to do so under the cover of using the whole of government, trade l…

Whether this is the right thing for a short time, a new long-term approach to knowledge tools, or a step backward is the subject of much debate. In the short term, it is probably fair to say the general concerns over the rise of AI in terms of jobs, replacing humans, and current limitations of the technology (to name just a few debate topics) mean this change is seen broadly positively. This is especially true because it is from a thought-leading intellectual powerhouse.

It might be a surprise to some, but almost 45 years ago Harvard Law School banned the use of the first truly portable computers. Students were bringing (lugging) the 25lb (11.5kg) Osborne 1—the computer I learned to program on—to exams to type and then print their answers. There were no caselaw databases, no internet (didn’t exist!), no modem, no battery even...just a loud grinding tractor fed dot matrix printer and the first version of WordStar on a 5” screen and extension cords. Other students used a typewriter, probably the one they got as a gift for graduating college.

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Two students brought computers to the exam in Alan Dershowitz’s criminal law class. Mid-exam a note was passed to the Dean of Students. The brave computer user who sought no special permission to use a computer—not because they were a hero or rule breaker but because using a computer seemed as obvious as using a calculator in math class—instead of a typewriter was summoned to the Dean’s office. In a follow-up meeting the student was given permission to use a computer while a hearing was scheduled. The primary concern it seemed was the anxiety the computer created for other students with regard to fairness. The hearing was months off.

First the story was written about in the Harvard Law Record. Then the Wall Street Journal picked up the story, March 23, 1982, with the title of the front page story quoting one of the computer users “Will Computer Memories Replace Notes on the Shirt Cuff in Exams?” Then, Time Magazine covered the story:

This was huge news among a tiny set of very interested people, myself included. Computers were new and scary, but the world was optimistic. Time Magazine had yet to announce the computer as “Machine of the Year” (December 1982) but the world was abuzz with the potential of a computer in every home and on every desk. Atari sold twice as many computers as the next leading company, Radio Shack, both more than either Apple (279,000 units) or IBM (240,000.) Literally almost no one had a computer with about 1.8M units sold collectively worldwide since 1977.

While the initial concerns were about a potential unfair advantage for students with computers—something that will later be known as the digital divide—some began to speculate about longer term concerns of computers providing a form of cheating such as pre-written text. Interestingly the idea of connecting the computer to a database of other text or case law resources was simply speculation at this point. It is worth noting that just a year later it would be routine to use a dial-up service to gain access to databases like legal cases as I did with my Osborne.

I was in high school using my Osborne when I first learned about this story. It appeared in the #2 issue of the magazine dedicated to Osborne users. Back then every computer had its own magazines. The story detailed with photos the whole Harvard experience. Below you can see the whole story. It is just too wild to read today. Deans and university presidents getting involved. Banning the use of a tool. Fear. Anxiety. It all seems too absurd over a computer.

Oh wait…this time is different.

In the end the school banned the use of computers and word processors from exams. The brave student told the Dean “I opened the door to 21st century technology and they slammed the door in my face.”

Seems crazy. I know.

Regardless, students increasingly used a computer in preparation of course notes, outlines, and assignments, though not in exams or take-home exams. In just a few years, the computer was ubiquitous in law school. By far the most interesting development at first was just how much students were typing compared to how recent graduates were practicing law where typing was the first thing you stopped doing as a lawyer.

Business school was the same way but instead of word processors it was spreadsheets. MBA students began using Lotus 1-2-3 in droves years before the banks and consultancies they would work for would make worksheets ubiquitous. The most tech savvy students were using VisiCalc on Apple ][ first of course.

My own college experience looked a lot like what I read about at Harvard Law. I brought my Osborne to school. I had the computer because my father had bought one to use for his wholesaler, even though he had no knowledge of computers whatsoever. It was a wild fluke that I ended up moving from the warehouse to the front office to figure out how to make use of it.

My freshman year (1983) had a required writing course. I just assumed I would use my computer as I had to write my admissions essay and even some papers in high school. I had the only computer in my dorm of nearly 100 students where Smith-Corona typewriters were the ubiquitous tool. To use a computer at Cornell meant slogging up the hill to the “terminal room” and using a connection to the IBM 4300 mainframe which was housed at the airport. When I set my Osborne up on my desk and dialed into the mainframe—no small feat—I was able to amaze my new classmates during orientation week.

I was so anxious having read the story about Harvard I actually asked my prof if I could use a computer before the first class even started. She was very excited to tell me that the writing program was embarking on an “experiment” (her words) to “test the quality of writing that students produce when using a word processor compared to a typewriter” and our section was deemed one of the sections that would use a word processor.

I kid you not. In my limited world view computers were already ubiquitous. I had computer books and magazines. I sold computer software I wrote the summer before arriving at school. I was in a computer club filled with NASA engineers working on the Space Shuttle. I was dialing up to FIDONet bulletin boards and downloading CP/M utilities. Literally everyone *I* knew used a computer.

But Cornell, like most every school, was skeptical. The first week of our writing class the dozen of us in class took a field trip from our 19th century, wood-paneled seminar room to a tiny and sterile closet of a room that housed two Wang “word processors.” These were computers from a then famous Boston-based company that did one thing and one thing only, which was word processing. They cost $10,000 and had monochrome portrait-oriented screens with elaborate keyboards featuring rows of dedicated function keys for word processing capabilities. There was what was called a “letter quality” printer which was like a Selectric typewriter with no keys. To use one we had to buy our own 8” floppy disks at the bookstore.

It was then my turn to meet with the Dean. When I asked to use my own Osborne in my room I had to seek permission from the Dean who was overseeing this experiment. Would using a computer invalidate the “data” or give me an advantage. A demo was impractical but I was asked to bring a sample printout to see if the prof could read it. I was told I needed to achieve letter quality output. I called home in a panic and using my magazine knowledge I secured a Royal electric typewriter that connected to the Osborne with a 2” wide ribbon cable from 47th Street Photo in NYC. It sounded like a strafing A-10 Warthog when I printed a paper. It was impressive because it basically “typed” faster than any human.

My classmates using the Wang constantly complained about the fact that the two word processors were oversubscribed by all the experimental sections and to use one required making a reservation. What the experiment failed to consider was that students would actually write at the computer not simply type. They originally thought students would use paper and pencil for a draft then reserve time to type the result in. Using the word processor was just a fancy typewriter.

The process of writing with a typewriter varied depending on whether it was an essay, report, or research paper. Generally one had handwritten notecards that could be sorted and organized. Following that, a hand-written outline was created. From that outline a draft was written out longhand. Some assignments required going over that with the prof or TA. Corrections were made with red ink on that draft. Then a final draft was typed from that. As the semester progressed and deadlines approached, many of those steps got skipped. It turns out those analog tools were ripe for misuse as well.

This was a really important lesson. The people controlling things had no idea how the actual “work to be done” would change because of the tool. Writing on a typewriter while difficult was also expensive. One could only correct small mistakes, and awkwardly so, with whiteout or just a pen. Once you removed the paper from the typewriter aligning any fix was impossible. A typewriter was not for writing or thinking. It was simply better handwriting.

I had no paper drafts. I was using a word processor to outline, write, rewrite, arrange, spell check, and more. I was somewhere between annoyed and puzzled at the experiment being done. I wrote my entrance essays using a word processor. In fact, it soon became provable that using a word processor freed a person to—potentially—be far more productive and produce much better output.

The writing program experiment no longer mattered. I don’t even know if they ever filed a report and I can find no evidence of one.

Reality rolled right over testing the theory. Even the need for “letter quality” output was relaxed as ImageWriter dot-matrix printers with tractor fed paper were standard. Late night on Thursday or Sunday you could sit in the courtyard between our dorms and hear the ever-present grinding of those printers as students put the finishing touches on their assignments. The tractor feed edges of paper would be strewn throughout the dorm the next morning. Every artistic and handwritten sign and announcement hanging on cork boards around campus was replaced with a “ransom note” of outline and shadow printing by an ImageWriter.

Yes I said “reality rolled over” on purpose. The logic of “preemptive regulation” or “presumptive negatives” is what incumbents use to slow technology adoption. They do so using the language of fear or appeals to morality to just slow down and consider... The problem is you really can’t consider a technology that is already out there. You can’t put it back in a bottle. You can’t make people stop using something they like out of concern without making a case that the mere worries negatives provably exceed the realities of the benefits. The ability to express concern does not replace the need to demonstrate harm. Preemptive regulation is the enemy of progress. We would definitely not have had the 20th century with such a mindset.

I know for many there is a visceral reaction to this. The government should protect us. Industry should not move forward until it can prove something is both good and safe. The easiest algorithm I have for this is to ask if some new technology will be used by the government alone before it is approved or neutered for use by everyone else. If that is the case then history tells us the technology is being used for control or even oppression first and foremost. I do not intend to be political here, but practical. In the case of AI, the connection of AI to freedom of expression is unshakable and irrefutable.

Make no mistake, students were still writing shitty papers. They just lacked spelling errors if they used the right word processor and they might have had some bold and italics. An important lesson was being learned—one that matters for today—which is for all the fears that the tool would make things too easy and take away the process of writing, the reality was that there were those that used the tool effectively and those that did not. The mistakes were new. There were weird typos. There were duplicate paragraphs from errant block moves aka copy and paste. There were loads of half-finished sentences. These were all things that you didn’t see when writing a paper meant transferring a hand-written draft to a typed final draft, which is all one did with a typewriter.

In my opinion based on my own real world experience leading up to that point, this new normal diffusing across campus was completely obvious.

Over the next three years of college, the entire curriculum and teaching process was upended. Everyone became connected, not just those in the computer science department. Every professor used a word processor for preparing papers. Every numbers-oriented department was using Excel on Macintosh. Every engineering department was using Macsyma (or μMath) and early design software on PCs. Databases that were kept on mainframe cards and tape were migrated to dBase or File. The first connected computers over BitNet allowed us to “chat” in real-time with other students.

This wasn’t just a university thing. In the four years since Harvard had temporarily banned computers the working world had begun to acquire IBM PCs and use word processing, spreadsheets, databases, and soon “presentation graphics.” Most everyone technically inclined was using a PC for their internships and all of us had stories to tell about how we impressed our bosses with cool computer tricks. In my job I turned around an idea my boss had for a inventory reports on Javelin handheld anti-tank weapons and Pershing Missile repair histories using Lotus 1-2-3 and CrossTalk that had been backlogged with the COBOL team for months.

We were in a new era. The optimism for the possibilities drowned out those that thought of these tools as shortcuts, cheats, or unfair advantages. It was obvious by 1985 or so that not using a computer was a disadvantage, in academics or business.

This all has me thinking about the University of Chicago. While many immediately came to the defense of the wisdom of the school, my experience put me right back talking to the Dean about using a word processor. What seemed obvious to him seemed like a risk to teaching and learning. The short term accolades that came from pacing the introduction and experimenting with the right way to use the technology were basically steamrolled by reality of the “native” generation.

That is what is happening right now with AI. The generation entering law school and frankly those entering the profession are AI natives. They are going to use AI no matter what anyone says. Trying to stop them is like trying to stop a new banking associate from using 1-2-3 in 1983. Not only is it impossible but it makes little sense. This is not about not having rules—for example the rules for cheating, stealing, hurting people and more all still exist and are in full force. This is about realizing that freedom of expression and use of information tools are intrinsically linked and controlling information tools is akin to controlling expression. Again, this isn’t political, just practical.

Many (many!) will dismiss this assertion—and that is all it is—immediately because as we know will be said, “this time is different.” The narrative goes something like AI is different. AI is not simply faster typing. AI replaces the whole process of writing (or analyzing or learning or reading or whatever).

There is some truth to this. But you cannot say those things about AI without recognizing that is precisely what was said about the rise of the PC. I sat at Thanksgiving dinner with some relatives who were first year banking associates who had gone to a fancy MBA program that had not yet adopted 1-2-3 or VisiCalc. Their view was banking was about knowing what questions to ask and then getting an intern to use a computer to work out the answer.

What they didn’t see was that the new tools were not about automating the answer to a question but about taking a problem and turning it into 100 variables, analyzing the interaction of those variables, and simulating thousands of potential questions. The idea of “solve for” completely changed how banking operated day to day. Modeling was the new thinking. And yes, if you had bad assumptions or bad formulae then you would be in a lot of trouble. The expression GIGO was already hanging in every computer operating room for a generation already—Garbage In, Garbage Out. I learned that from my NASA buddies at computer club.

If that isn’t convincing, this same logic was said about the rise of the internet. Many critics of the internet (and I’m not talking about Paul Krugman in 1998 saying the internet would amount to nothing more than a fax machine by 2005) were saying that the internet with its ability to find the exact right answer would replace thoughtful research and consideration. It would replace output with theft. The internet would make us all lazy at work.

No one in 1995 saying those things was predicting the true impact of the internet. Not only would it fail to have those negatives so adamantly declared, but the positives came in entirely new ways. Jobs were not eliminated but unleveled. People did not become lazy about doing new things, they just expected old things to be more efficient. We all know this now. And yes, whole new kinds of mistakes or bad behaviors arose. The same could be said of electricity or cars, or fire.

I can’t prove that AI will evolve in as favorable a manner as PCs or the internet, or even my Ti-35 calculator. I can say that the forces in play already point in that direction. We have a generation of natives going to college and joining the workforce. We have a technology that so clearly does new things in new ways.

Yes we have risks. Hallucinations are supercharged AutoCorrect typos. But you know, AutoCorrect (or spell check) typos were simply a much more efficient way to have typos than simply mistyping. AI might bring more versions of the Excel date formatting problem. I grew up in an era where we called things like these “stupid computer tricks” after our hero David Letterman. AI will have its own versions of stupid computer tricks.

One of the most popular ones to talk about now is the rise of hallucinations in legal briefs in court. Suddenly there is an explosion of court-submitted documents with made up citations or quotes. You know when you get a new car and suddenly you see that car everywhere.1 That’s what’s going on now. I ran across a compilation of all the court cases where hallucination came to the attention of the judge. There were just over 1,000 cases. That seems huge. You know what the denominator is? It is about 65,000,000 new cases filed every year (most lasting more than a year.) What is the rate of disciplinary action for shady filings without AI? Turns out that is common too. In the 1980s courts began a concerted effort to take note of attorneys stretching the facts in briefs—human hallucination—and since then most federal judges encounter that at least every year. There are almost 1800 federal judges. The reasons are different.

I am not dismissing any concerns at all, but a reminder that all the millions of laws we live under and rules in place at every institution still apply. No one is confused about accountability. This is even true with nascent agents as they are running as someone in an organization. AI is already a governed and regulated technology. AI is still overseen in its entirety by the post-war regulatory apparatus. This includes everything from liability to copyright to civil rights to antitrust.

New tools give us new ways to fail doing old things. And more importantly new ways to succeed at doing new things.

To anyone who made it this far, be a native AI user. Hire native AI users. Let them do native AI things. Let’s together see what a new technology can do. That’s how optimists and builders approach new things.

Author’s note: LLM was used for typos and grammar. I asked for pointers on where a skeptic would be provoked and in my own words made about five additions. FWIW, the model said those changes would result in simply putting down the essay and “reacting poorly to what you wrote.” Thank you Clippy.

Below is the full article on Harvard Law banning the use of computers.

I am completely blown away by it. It is a paradigm shifting computer.

But I also have to say it made me a bit melancholy, and I’ll explain why. This is an indulgent post but it has been a decade in the making and it just took today’s Neo to put it all in perspective. Consider this my “review”.

I set it up via migration and was up and running quickly. Usually the first 24 hours of a new computer are the worst time to evaluate performance as system optimizations (like Spotlight) that run in the background are doing their work.

I put everything on it that was on my MBA: Apple apps, Box Sync, OneDrive, Office, Chrome, a few utilities (Keka, exif cleaner, Nikon WTU), ChatGPT, Zoom, Xcode, and set up app icons for some browser apps like Gemini and Google Remote and so on. I like to have files local so I set a subset of OneDrive and Box to sync locally (about 100GB). I have other apps that come and go. I do run some models locally to try things out but haven’t gotten there yet.

I spun up all my apps, photos, and so on. I could not tell the difference between this and my MacBook Air. Max memory use was just under 7GB in the first couple of hours. I think when launching stuff it bumped up a bit and then dropped down. This was just using Activity Monitor.

All the “compromises” are totally acceptable and go unnoticed to me. I always charge over USB anyway. Anywhere I need an external display there’s an HDMI/USB adapter attached. I only rarely use external USB storage (security!) and so on. The trackpad is a tad smaller but the physical click feels little different than Force Touch to me. The screen actually looks a bit brighter side by side and I can see the resolution difference but I’m ok. I rarely use the camera. I can tell the difference in physical dimensions, but only when I try. I never need an actual full day of battery life. I don’t even use a sleeve or anything so I won’t notice it in a suitcase. On storage, for my mobile computer I do my best to avoid having all my iCloud and cloud stuff locally, just current work and resources. This is a security thing. So 512GB is not a limitation for me. I don’t edit 8K video :-)

Neo doesn’t have to get better. It just has to stay excellent. If you need or just want better, there’s two more levels of laptops and two levels of desktops. Plus iPads. The Neo in 5 years will be more powerful than most of those and probably still cost $699. Moore’s law is undefeated.

For me, Neo is just a MacBook Air replacement. And in a much cooler color. It is also a laptop made with “a phone chip”. That’s the part that is so familiar.

That’s why I got a bit melancholy looking at it. Everyone who knows me knows I (too often) like to bring computing history into the present for context, framing, and comparison. I always do so thinking about the old adage of “generals fighting the last war”. I don’t want to be that person.

If you’ve read any of “Hardcore Software”, which tries to put all those stories in one place (hardcoresoftware.substack.com), then you know a theme in computing that repeats is how something that appears to have been a prescient product or “early” is actually little different than “wrong”. In almost all cases something that was early was early across many dimensions. The “concept” was right, but the ability to actually execute the concept was wrong. For example Newton and then General Magic (and to some degree mobile Palm Pilots) were all perfectly right as concepts, but the lack of a usable data network, the ability to shrink computing, and even display and input technologies all added up to being “early and wrong”.

So when I thought about Windows 8 over the past dozen years, I quite often settled on being early AND wrong or too much too soon when I didn’t want to feel that bad.

But today I’m using Neo and thinking about Windows 8 and Surface, and I have to admit I’m struggling with that conclusion. We had all the pieces and all the pieces worked then. One I’m thinking about is compute. The original Surface on ARM (Nvidia Tegra) had 2GB RAM and 64GB storage. Those were also the published baseline specs for Windows 8 on Intel at the time. Both had no problem running Office and browsing.

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In other words, the hardware and software were not early. The world as we lived it was quite capable of running the device. And it cost $599 with keyboard/32GB, $699 for 64GB. Here’s a slide we used when we announced ARM. Baseline compute power for phones had already matched baseline PCs. We were there. The Nvidia Tegra was ready for the world as was the next iteration in the pipeline. As Jensen said to me “we’re going to create a new class of device”. We were so excited. Betting on Jensen and Nvidia then was “easy” as I wrote before, and few could argue that in hindsight it was the right bet.

Where we were wrong was in moving the ecosystem to a new app model fast enough that was safer, more reliable, more power efficient. A lot of people rebelled about this. They wanted the old Windows app model. We knew there was no way to secure it, no way to make it power efficient, no way to make it safe. It was designed for another era. From the day we announced ARM we sought to separate the x86 Windows world and be new. I knew that any baby-step in the Microsoft world was in practice a lifetime commitment. You can see this in how ARM is treated today, as a forever alternative to x86. We viewed it then and I still view it that way as the replacement. There’s no revisionist history here. It was our strategy.

Apple, seeing these same problems (remember the “I’m a Mac” commercials) starting with OS X, spent the next two decades moving to new OS APIs for apps. It was not quick, but they moved the ecosystem and removed old code. Unlike Windows up until recently, where you could still run Excel 4 designed for Windows 3, you can’t run Excel 3 Mac on anything. In fact you can’t run Excel from even a decade ago (not going to research this so consider this rhetoric). Apps have all been modernized. They are power efficient. They are more secure. They use different system APIs (frameworks) than were used when Apple moved to Intel. Yes there was emulation and that was brilliant but that technology has been sunset and thoughtfully isolated. The real news there is with Neo people aren’t even complaining or asking all that much. Everyone on Mac is current. Every Mac is the most secure, power efficient, and reliable Mac ever made.

We can’t say that about Windows PCs even today.

Apple’s software secret was this constant upgrading of the OS and the ecosystem (from drivers up). Microsoft’s secret was “run everything forever”. As is almost always the case in business and product development, your greatest strength (in any of the 4 Ps) becomes your greatest weakness. The pull and push of forever compatibility was not just “Windows DNA” but it was the soul of what made Windows successful and was sacred. But it was obvious then and now that it was the part that needed to change. The web and browser were born. That middleware layer was going to take over. Chromebooks were just the Network Computer from 2000. Mac was starting to look like that too, especially if you had an iPhone where the real new apps were being built.

Beyond that broad view, many saw that app model as specifically about “touch” and trying to be like an iPad, a product that hit the market just as we were going public with Windows 8 (see hardcoresoftware.substack.com). We definitely over-indexed the communication of Windows 8 on tablet form factors and Surface was a tablet with an integral keyboard. But make no mistake, from the start Windows 8 was designed to work exclusively with a mouse/keyboard OR touch, or using both (stay tuned for that touch MacBook!). The Start Screen was symbolic of that and many people could never ever get past the start screen. I litigated this in Hardcore Software. That might have been wrong but it wasn’t early. It was an easy fix as the evolution of Windows showed, though it could have been done better I am certain.

The feelings today are about those emotions I felt leaving Microsoft and particularly after. I knew the winds and emotions at the time wanted to give up and walk away from Surface and particularly ARM. To pretend it never happened and get back to the world as “we knew it”. Watching that happen was incredibly sad. I knew the trajectory we could have been on. I also knew that I was not bullish on the Windows API and Intel going forward. We’re here today seeing this. That’s emotional for me.

I sat there looking at my Neo and admit and apologize, but all I could feel was a bit of “what could have been”. I use a Mac a lot but generally don’t feel that way. The Mac is brilliant and the Apple Silicon work was the best linear silicon and packaging the industry has ever seen. macOS is fantastic. It’s still macOS though, the one I grew up with in college and was hired to work on at Microsoft, but I’m a PC and always wanted to make the PC better too.

I type this today with these emotions and there’s no escaping my “certainty” that had we kept going and been able to round the corner with developers to build new apps we would have been in the same spot Neo is today in just a few years. Ironically, the rescue plan I suggested to new leaders after I left Microsoft in 2012–13 was to turn RT into what was just announced as Chromebook focused on corporate use. And how are people talking about Neo today? A better Chromebook.

The trajectory of the hardware was clear. I am certain we would have had a clamshell (look at Surface Pro from the 2012 launch, it was almost that). We would have had a desktop all-in-one. We would have done cellular (all the code was there and we even gave that hardware out previously). What kept us from doing those out of the gate was most obviously our own need to focus but also a desire to not compete with PCs. I never felt we were competing. I felt we were replacing the traditional PC.

In the past when I looked at Apple Silicon I wrote that there was no way Microsoft would have gone first party that far down the stack. But now today I look at what Apple delivered with Neo and can see just how close we were without doing all that. We had chosen Nvidia specifically for the GPU. The compute was there to run the most demanding productivity tools in use. We had all the sensors (many still unused on typical Windows PCs). We had additional processor support for media. I now look at things and confidently can say we would not have needed to own the silicon. Nvidia would have continued to deliver.

There are a million ways (ok just a few dozen) this is complete fantasy and would never have worked. But I couldn’t help myself in using Neo today. It felt like a strange way to validate what we began 15 years ago with that first demo of Windows on ARM or in 2012 when we unveiled Surface to a completely shocked audience.

I remain proud of what we did and write this in no way at all/even a little to take away or distract from the wonderful work of Apple on Neo and all their products. Neo just offered me a new way to think about something that I’ve thought about and written about a lot.

And a chance to once again thank the Windows 8 team that even to this day delivered more in one release, on time and on schedule, than any other Windows team before or after. We were early, but not wrong.

Congratulations Apple on another insanely great product 50 years in the making.

Maybe you must take my word for it, but this year’s CES had a lot of extremely solid advances in things that matter and at the same time the progress is more than just tangible. The old saying “the future is here, it just isn’t equally distributed” applies. For many at the show, seeing the Amazon Zoox picking up and dropping off people on the Strip was mind-blowing. It was just last year that these bubble cars with no steering wheel were just on display on a show floor.

The show was big this year, up over 2025 with 4100+ exhibitors and 148K+ attendees, including some 6900+ media (according to CTA) that compares to 2025 of 4,500 exhibitors, 141K+ attendees, and some 6,000+ media.

The number of exhibitors might catch your attention. My sense is there has been somewhat of a restructuring of the show. There’s always been a tension for big companies over attending with a big presence or just sending the right bizdev people to meet privately in hotel rooms. There was some noticeable shifting this year. Samsung and Sony both left the central hall, as did Panasonic to some degree (making a smaller, boxed in theater-only booth) which freed up a lot of space and dramatically improved the flow of people in what was historically a completely jammed and miserable entrance experience. Samsung set up their own convention within a convention at a hotel complete with reservation times. It was a wonderful experience where you could really see stuff and even breathe at the same time.

The PC industry has long been in retreat at the show. Dell and Lenovo have done primarily small private events for years and even those went away. Instead, this year Lenovo did a monster keynote as The Sphere and had signage everywhere for what they were talking about. I didn’t have the energy for a special trip.

Nvidia followed the Samsung model and at a different hotel set up their own exhibit space. It was branded as a CES themed “The Foundry” which makes a lot of sense. In my view Nvidia is now the underlying technology of the whole of CES the way that “home theater” was for the first generation, then the computer, then the internet, then phones. More on Nvidia below.

With Sony’s absence we also saw Nikon and Canon both pull back. This meant that “image capture” was not represented at the show. There are other places for this such as the NAB show for broadcast or Photokina in Germany. But this made me sad since I love photography.

For the past decade or so, CES was almost an electronics show combined with a car show, a mini-Detroit Auto Show held in the North Hall. The car makers had huge booths with exotic cars or prototypes, and the hall was filled with a vast array of after-market products for car enthusiasts, all of which was difficult to navigate and often only borderline tasteful. The rise of EVs and Tesla brought a wave of high technical car components aimed at car makers from platform batteries, charging infrastructure, and electric motors. Then with autonomy came all the components for self-driving such as LiDAR. By and large all this has been replaced by the broad category of mobility, which for a while meant an over-abundance of scooters. This year the emphasis of mobility was on full autonomy and a bit of general mobility. These changes bring more focus to the show, and the North Hall was once again traversable.

The ever-expanding role of international or country level booths continued. These booths are when some country level agency such as a ministry in charge of science policy or an economic development rents a big chunk of floorspace and then curates startups or other companies to attend. This is an amazing opportunity for a tiny startup in Korea, Romania, or Italy to come to Vegas and have a booth. But as an attendee these are extraordinarily difficult because “country of origin” is not a pivot you care about compared to healthcare, home security, enterprise, or whatever. Plus, navigating the whole show as a series of booths within booths is logistically impossible. That said some countries over-achieve. I lost count but there were at least two-dozen booths sponsored by one of a major Korean university, government agency, or trade group. Japan had two giant booths next to each other representing Japan but neither could tell me who the other was! There are other interesting ways floor space is allocated. For example, the AARP (American Assoc. of Retired Persons) had a large space dedicated to technology for aging and health.

On top of all that, this was the first year without a major part of the convention district under construction. Truly a remarkable decade of remodeling. The amount of super nice exhibit space that is all gracefully connected and accessible with bathrooms and places to get food is an accomplishment. Along with that there are huge numbers of brand-new hotel rooms all easily walkable from the convention center. It kind of blows my mind to think we used to come to the COMDEX show with almost twice as many people with half as much space and half the number of hotel rooms, no food anywhere and hotels were all 2 miles away.

One meta comment about “global trade” which is this year was as global as ever. I did not see or hear any commentary on global trade issues. In fact, I think there was less than last year where booths were out front saying “opening factories in <not our home country>”. There’s a broad set of new normals and it felt like everyone is working through what needs to be done for every market to have new levels of safety and self-determination.

As usual I am going to share a lot. That’s just because I love this stuff. You don’t have to love it as much as me. So here are the sections you can look for:

1. AI and Nvidia

2. Television and Display (includes my show favorite, Samsung 130” MicroRGB TV)

3. PC and Tablets (includes my show favorite, Dell XPS laptop)

4. Home, Automation, Security (includes my show favorite, Amazon Ring products)

5. Health (includes my show favorite, Triage 360° from Omedus)

6. Robots

7. Mobility

8. Lifestyle and Accessories (includes my show favorite, Roam Smart Tracker)

9. And Finally… (includes…an appearance by Clippy)

AI and Nvidia

It’s been clear for quite some time we’re in the midst of a platform transition. What hasn’t been clear is what shape it will take. The progress Nvidia has made over the past year and the strategy they have has solidified my view they are not just benefiting from but setting the direct for how things move forward in both hardware and software, much more than I think most are saying. My view is that the (stock) market dynamics are making this seem like a battle where there will be a GPU winner and an LLM winner. That pre-supposes the next platform is LLM based but I think that is too narrow a definition.

The question people should be asking is who is leading in a compute platform—it is not only LLMs that are the next platform but a switch from algorithmic computing (bound by instructions per second) to data computation (based on model computations or “tokens” broadly defined) per second.

The race is no longer about MIPs, megahertz, or parameters but about computing on tokens. As with those old-style measures, tokens will have infinite demand and essentially infinite supply, and the price will continue to drop. And like those other measures the availability to compute on tokens across an entire network (the “edge”, devices, datacenters, hyperscale) means that whoever has a strategy working across all of those is the de facto leader in the platform.

Nvidia is the leader. The signage saying “The Next Generation Begins” is not aspirational. It is predicting the present.

Nvidia

Nvidia is executing better than any previous leader in these shifts in a more dynamic and fast-paced environment—better than IBM and mainframes, DEC/Sun in mini/workstations, better than Microsoft with Windows, or Google and the internet. They are executing at the level Apple executed from 2006-2025, but doing so in a way that drives an entire industry at every level of the stack not “only” (not trying to understate Apple, just contrast) at the app ecosystem level. Nvidia is executing like a combination of Microsoft, Intel, and Open Source all combined. It is incredible.

Nvidia brings software assets and a surrounding ecosystem at multiple levels, proprietary APIs unlike any in the market and open source contributions on par with any one else. They bring hardware from the edge to devices to hyperscale, not just compute but networking, sensors, and more. They are marshalling the “old” PC ecosystem in new ways to redefine what it means to even be a computer.

Author’s note: We bet on and with Nvidia to redefine the PC when we built the original Surface computer. While I am biased in favor of Nvidia today, I kind of feel validated. Read what it was like to Launch Windows on ARM with Nvidia at CES January 2011.

At CES 2026 Nvidia had a show within a show, first with Jensen having a pre-exhibit keynote where he among other things announced the latest GPUs are in production, and then with a large-scale set of booths at a hotel off the show floor. The square footage wasn’t huge, but the density of technology matched most of the rest of the show combined.

One aspect of the booths that really put me back at Microsoft twenty years ago was that the booths were staffed with line engineers showing off their own work. I had a half dozen conversations and listened in on a dozen more and was simply blown away. Nvidia is simply executing at the most phenomenal level with incredible talent that can easily answer rapid fire if not always on-point questions. The only other company that could do that today would be Google, but it isn’t the whole company the way it is at Nvidia. The breadth and focus are what you notice.

Some examples for me were robotics, autos, biological discovery, and of course machine learning. Each of those stations was the absolute pinnacle state of the art. And all represented real products with real partners making real progress. This was not demoware. It was like being in the Windows booth in 1996 after spending the night putting signs on every computer on the show floor proclaiming “Windows Compatible”.

Below is an example that can be seen in many contexts (security, manufacturing, etc.) of real time video processing but what you can see here is the “platformization” of this technology – the hardware, software, device integration, all coming together. It’s just one example. Another example follows which is another full-stack showing integration with robots for the purposes of ensuring safety.

There is a separate section below on PCs/Tablets showing traditional PCs. Nvidia was showing where PCs are heading. While AMD might also play a role here and fingers-crossed that Intel can pull something off, the modern PC is being defined right in front of us. A modern PC starts from the assumption that AI compute will happen on the PC where it will be free, low latency, private, and continue to improve exponentially. The modern PC will do a lot of what we call inference today on device. And like every era the most important step is when the device can bootstrap—that is the device can be used to build itself. We’re already seeing that and it is almost certain that soon enough it will be a routine part of development to do AI coding on device.

I know some will doubt that but I also lived through people saying a PC will never be powerful enough to develop PC software (note, the first versions of Word and Excel were only debugged on Windows but cross-compiled and Windows graphical tools were not used by developers until the 1990s and even then most did not use Windows until NT). I also lived through people saying the PC would never be a powerful server, yet here we are.

With that context and building on the Nvidia announcement a year ago of the Spark DGX platform (a full stack computer running with an NVIDIA GB10 and MediaTek CPU, etc.) was this full display of DGX compatible devices from all the major OEMs. If this sort of display looks familiar it is because it is exactly what Intel was showing for laptops. This is the sign of an ecosystem bootstrapping. This year we’re seeing the tower version with a GB300 with Dell and Gigabyte announcing them. While these might be seen as developer machines or just “OEM packaging” that is how the Windows ecosystem works today. These computers can be used in labs, for deployment of apps, and for developers.

At the other end of the spectrum is where Nvidia is positioned in traditional PCs and here you can see Nvidia penetrated at the highest level. While these are often positioned as gaming (or professional graphics) level PCs, they are also indicative of the demand for Nvidia’s APIs across devices. It should be clear that the Nvidia software layer is becoming more mission critical to the kinds of applications being developed today, and while simply running AI in the cloud and relying on a traditional browser might be enough, I am convinced more and more will migrate to a local device where it will be more economical, more private, and more responsive to end-users.

AI Broadly

If you take my assertion that AI is the platform technology and Nvidia is the key enabler and first software on that platform, the next area to observe is what is this technology being used for. Below will describe mobility, home security, health, and more. We are seeing literally everything get touched by AI. People will want to know or assert the killer application. It is clear chatbots and generative text, video, audio are wild new applications but that is just the start, and it isn’t even clear if those generative applications will be the anchor. AI will be an ingredient in all existing areas software solves problems and will also create whole new solutions breaking down existing barriers. This is just like the graphical interface or internet or cloud.

The key inflection point we are at today is debating whether AI brings new solutions or is simply an ingredient to be used by existing solutions (and importantly software companies). If you were around in the late 1990s this was exactly the debate that was had about the internet. Then in the 2000s that was the debate about cloud. Reality today tells us that those were ingredients and by and large the software and hardware in use today are new companies and categories, even if the large existing companies continued to dominate the markets they created by using the new technology as an ingredient.

Across the show floor, particularly in the startup and smaller country booths (also startups) there were thousands of companies essentially doing “AI for <X>” where X was as broad as you can image. AI to:

• diagnose a disease, read scans or labs

• review or summarize an industry document

• secure web traffic, detect phishing and spam

• translate, dub, transcribe, caption text or video

• choose ingredients and cook food

• determine nutrition of a meal

• water and fertilize plants in a pot or in the largest of fields

• monitor and manage pet behavior and health

• select proper lighting and enable a vast range of lighting scenarios indoors and outdoors

• profile car and truck tires for wear and safety

• detect cheating on exams and in interviews

• coach people at work after an interaction with a customer, partner, or collaborator

• improve support documents for readability and utility of complex “manuals”

As I walked the floor at every corner I was blown away by the companies with specific AI enabled scenarios solving actual problems in what might seem like narrow domains requiring domain knowledge to even approach the work. A few readers might know, but the original software market included highly specific software for farming, medical offices, construction, and real estate management (check out an early RadioShack catalog or here). The sign that something is a new platform is seeing all the above reimagined or done for the first time with the new tools.

There are also many solutions using a frontier LLM platform directly. I saw a dozen devices that in one form or another recorded conversations or notes to myself then with a phone and app provided transcription, organization, and follow up. These even took the form of MagSafe connection to the phone. This one by Plaud is an example.

Amazon recently acquired Bee computing and was showing off their Bee Pioneer ambient computing band. I think we all expect this space to see a resurgence as the models have dramatically improved.

Vocci expressed ambient computing in a ring form factor. The ring has a tiny button on it to start/stop recording and a companion app to provide transcripts, summaries, organization of notes. I am extremely uncomfortable with this sort of recording without notification.

Nirva is a company more focused on journaling and mental well-being with jewelry providing the microphone and recording. It aims to go beyond recording and summarizing as “it tracks your mood, maps your social relationships, and delivers truly useful, personal insights and guidance.”

One thing many new AI applications are confronting is the concern over privacy, particularly when using the frontier models. This is driving a wave of innovation where capture and processing are happening on devices or even as a private cloud. For me this continues to reinforce that what was fancily call “the edge” today is really about having a device that does the work locally will be cheaper and more private.

In that spirit there were quite a few “devices” that are essentially AI-computers, which are really building a new kind of PC that has the GPU-compute capable of running the AI software that matters. We saw the full devices on the Nvidia platform but there were others. One I thought was cool was Tiiny AI. Tiiny connects to your existing laptop and provides a local web interface to the compute engine capable or running an array of models locally. The software layers is essentially an AI workspace. The hardware in the small box provides a long-term memory of your work, connection to your local data, along with 80GB RAM and almost 200 TOPS (whatever that might mean!)

Tiiny is a companion device. At the higher end are mini-pc form factors like the Minisforum MS-02 which is a full PC form factor that can be stacked/daisy chained for even more capability. While a variety of these exist, they all run Linux and open source models on top of combinations of AMD, Intel, and Nvidia hardware. My view is these are a stop along the way to a more converged hardware standard, aka Nvidia.

I don’t see this activity for local compute abating even as the frontier models from hyperscalers continue to dramatically improve. One could point to the increase in “on-prem” data center efforts for either traditional workloads (private or secure cloud) or new AI workloads.

Finally, in the first year or two of chat and LLMs there was a view that many of the newest “applications” were simply “LLM wrappers”. This was a common claim at the early days of the graphical interface as well—new products look like most of the product is just surfacing intrinsic capabilities of the underlying platform, in that case windows, icons, menus, and so on. This is because there’s a perspective that the new capability from the underlying platform is the “hard part”. One look at Excel and we can see that those claims were never really true.

Still, CES had quite a few products that early on might appear to be easily subsumed by the model itself. Time will tell. For example, there was Loona a consumer robot that is essentially a friendly interface to a GPT model. It provides a speech and expression-based interface to GPT capabilities. It is a physical version of the prompt engine you interact with using speech and audio and a bit of vision.

Very clearly CES lived up to its marketing and innovators in AI showed up in all forms. The debate over feature v. product v. company will continue. I would assert the answer to that will not change the fact that all of these scenarios will indeed be solved with AI-enabled software.

Television and Display

Some years of TV are about form factors like flexible, curved, or 3D and those years seem to come and go. Other years are about thinness or bigness as the main theme. You walk about not so impressed and think “these people aren’t doing anything”. Then in really tragic years it is all about “smart” and TVs try to turn themselves into computers and most people get frustrated and wish they would just make great displays because the idea of signal has been completely separated from TV and 100% of tv buyers have a phone and/or a streaming box. All while we’re thinking this as consumers the number of displays in our lives compound exponentially (we carry and wear one, drive with several, and there are countless in the home and at work). Even so, the business is absolutely brutal and has leveled massive companies in the past – RCA then Toshiba then Sony – and has proven difficult for even the biggest Chinese companies to break into (Haire, ChongHong). Today Korea overwhelmingly dominates between Samsung and LG.

This year the two companies showed exactly what we all want to see which is innovation in picture and sound. The new displays are really incredible in color, thinness, size and soon price for early adopters. The buzzword this year was “RGB” with modified of Mini and Micro. In fact, if you take RGB, Mini, Micro, and LED you can mix and match and create any sort of new display tech you want. I was so confused. And the vendors all add modifiers like EVO (evolution) and Next Gen to confuse even more. Here’s the best I could do to explain for a world where we know LED and OLED and “O” is better:

Some of the permutations and combinations of LED, RGB, Mini, Micro, and organic include:

• (Today’s Best) OLED self-emissive (no backlight) display where each pixel produces its own light and color, enabling perfect blacks. Can be made FLEXIBLE.

• (Today’s mainstream) Mini LED: LCD that uses tiny white LEDs as a backlight, improving brightness and contrast through zone-based local dimming. Rigid.

• (Latest) Micro LED: step up from OLED with self-emissive (no backlight) display made from microscopic inorganic RGB LEDs, OLED-like rendering with might higher contrast.

• (Latest) Mini RGB: LCD approach that replaces white backlight LEDs with red, green, and blue mini-LEDs, allowing more precise color but still has an LCD layer.

• (STAY TUNED) Micro RGB: self-emissive (no backlight) display where each pixel is made of microscopic RGB LEDs, making for super thin and near borderless panels with near-borderless.

The bottom line on displays is we’re in for a step function increase in blacker blacks, whiter whites, thinner bezels, and much thinner TVs.

Are you still confused? Me too. I’m sure I messed that up. I swear if you wanted to confuse a staff person ask them to compare/contrast or even define which tech they were showing off.

Here’s some up close photos showing different kinds of pixels. I got in a lot of trouble taking these so please appreciate them:

Below was the best TV of the show and will most probably cost as much as a Tesla should it make it to market. (Note: I learned after the show you can order the 115” 4K version for $30,000).

How thin will the TVs get? Micro RGB is the ultra-bezel-less ultra-thin technology on the horizon but still must go through manufacturing ramp up so is a way off. Here’s a 9mm thin bezel-less display from LG. I couldn’t figure out how to visualize the thinness but here’s a smart IC next to it which is just under 8mm along with a shot of what that TV looks like on a wall. I got in trouble taking this photo.

It isn’t just picture. When outfitted as TVs (v. computer monitors) behind these displays are now a full wall of rear firing speakers designed to bounce the sound off the wall and simulate a full range of audio capabilities normally heard from a set of speakers. Samsung declared it “The Year of Audio” with a soundbar containing what they claimed eliminated the need for both surrounds and a subwoofer. But if you get their latest wireless speakers you can add up to 4 for a full range effect. Sounded incredible in the booth of course.

The TVs and resulting monitors are getting ever-increasing refresh rates as well. There’s a caveat with these in that they are starting to create synthetic framerates (the same way Nvidia does with the GPU) by computing extra frames. So, you get absurd claims like 1040hz which kind of sounds questionable to me.

The other thing going on is the size of TVs continues to rise as fast as the lift on American pick-up trucks. TCL has found its niche as the mainstream (read: Costco, Walmart) supplier of ginormous sets for relatively low prices. They routinely sell a 98” unit. These are monsters that you really can’t hang on a wall or put on the second floor. But boy they are fun.

The big negative is that each vendor is attempting to apply AI to the image being displayed. So, this is going to drive A/V enthusiasts nuts and provide endless hours of “disable” at family gatherings. Here’s HiSense (Chinese maker, usually highlighting their laser projects which are super cool but still seem niche) using AI for everything.

Even with all this, there’s an effort to truly extend the viewing experience. While many of us see these with sports or Youtube TV, like everything the TV makers want to embed it into their platforms. This can make for some interesting experiments. HiSense was showing a 21:9 aspect ratio which allows for all the extra information while not scaling the main show, which you can see in the above photo on the left. This particular feature has made appearances a number of times but is usually blocked by the inability to build this into an ecosystem. YouTubeTV is doing this for sports by scaling the main event.

That might have been enough but there continues to be a push with 3D as well but no glasses or goggles. Here’s a Samsung commercial 3D display for signage, particularly retail. Obviously, the photo doesn’t capture the effect, but it is rather remarkable. This can be done live as well as they were showing it with people lined up to add themselves to a 3D display ad.

Bottom line is there’s a lot of innovation going on in display and TV and it is aimed in the direction I think most consumers care about which is better picture and sound. Given how much of our video content is now watched at home yet the era of “home theaters” (with $20,000 “RUNCO” projectors and a $50,000 rack and a remote that doesn’t work) is long gone replaced by a giant flat screen in an open-plan living/dining room with people sitting in random places with their phone in their face, I am hoping there’s a potential to do great setups with these broad consumer TVs so we don’t go back to building out rooms that cost more than the house itself. If we’re going to spend $30 on a first run movie in 4K HDR Dolby Atmos, we should have a fantastic audio/video experience approximating what the director had hoped.

PC and Tablets

I can’t help but seek out the personal computers even though they are a tiny fraction of the show. Except for Computex in Taipei there’s no real forum where PCs come together anymore, which is a weird feeling. CES sort of picked up PCs when the COMDEX show (think Halt and Catch Fire) failed to make it through 9/11 and the dot com crash.

In keeping with the show delivering on innovation, like TV, the PC world is delivering solid improvements in the hardware. Like TV these improvements will not redefine the category, create new use cases, or drive early replacement, but they will be better.

This is about Windows PCs. Apple is ubiquitous at the show but has no public presence. US people walking the show get a good reminder though of Android market share outside the US, especially in Asia, when seeing all the folding phones in use by attendees. Make no mistake, easily the majority of PCs in use in booths are Macintosh and don’t think I don’t notice this. It hurts.

The Windows PC faces two structural issues:

• The spreading of effort over ARM v x86 today is unnecessary. The gains from ARM will not materialize and the edge compatibility cases keep it out of the enterprise. ARM was about a new software ecosystem and new hardware capabilities with a break from x86. Merging them was always going to cause these challenges and gain none of the benefits.

• Windows doesn’t carry the APIs for new scenarios in AI and there’s an Nvidia ecosystem gaining momentum as a true replacement in a browser-based world. That isn’t an enterprise thing, but it is a developer thing and is easily, as Chromebooks demonstrate, a consumer thing.

A symbol of this second point is that the chip companies and some OEMs are offering AI accelerators for offloading compute to dedicated chips when running APIs not generally part of Windows. Note: TOPS is a meaningless number comparing across architectures and operating systems just like megahertz is.

Additionally, PC enthusiasts would also chime in and talk about the evolution of the Windows user interface itself but that is a bit like the TV software platforms (Tizen, WebOS, etc.) and not core to the issue. The taskbar, explorer, start menu, and so on are not going to alter the trajectory. Worrying about those is truly rearranging deck chairs.

That said, what is being delivered by Dell, Asus, Lenovo, HP, and others working with Intel and AMD are very nice PCs. While I certainly have offered the cliche “these are the best PCs ever” this year is particularly good. I believe they represent the right kind of innovation in the market given where PCs are. If you’re doing “PC things” then these are the best ever and you probably have no need to try to make them do things PCs are not so good at these days.

Dell relaunched the XPS with an absolutely rocking model. Real function keys. Thin. Light. Solid. Great display where Dell has been executing fabulously. It is premium and premium priced especially if heavily specified. The Dell XPS 14 has long been my PC recommendation and I’m glad to have that back. Dell also continued to do stellar work on monitors announcing two mind-blowing products: UltraSharp 52 Thunderbolt Hub Monitor, a 52-inch 6K display, and the UltraSharp 32 4K QD-OLED Monitor, focused on performance and color accuracy.

Geekom produces a full line of performance and price favorable PCs. Their latest X14 Pro is only $999 (half of the above Dell) with an Intel 125H processor/ARC graphics, weighing only 999g.

Asus introduced a line of business-customer focused PCs, which means they are a bit more durable and overall premium and come loaded with Windows Pro. These were quite nice.

Samsung and LG both offer premium PCs as well. Here’s the new Samsung Galaxy 14.

At home I have always been a fan of All-In-Ones when you want a big screen for a stationary PC. The market is limited as laptops are now equivalent in capability and in fact the AIOs are just laptops in the base or behind the screen. Still this ASUS model was super nice. Lenovo introduced an AIO with a large dual screen format with almost a square resolution for creators. The screen is a dual letter sized stacked landscape. You either think this is an ideal size or it needs to be tilted 90° sideways. I think it is ideal for productivity like XL or PPT (aka sheets or slides).

All of the above are mainstream PCs that do a great job at PC things. I think that is where the market is and pushing PCs to be more creative in form factors really requires new software and the investment in new capabilities at the app layer just isn’t there compared to devices on the edge with companion mobile apps. That’s causing people to bemoan the lack of innovation in PC form factors.

That said, Lenovo showed off (again) a flexible screen laptop. People went nuts over this prototype. Asus had a more practical product in this area, the (updated) Asus Zenbook Duo. This is a two part tablet/laptop with a big folding screen that can be dual or full screen. The way they make this practical is that the keyboard magnetically attaches/detaches for sure and the screen has a stand. They don’t try to make it a tablet, just a dual screen laptop. If you’ve seen those USB-C powered folding screens in Instagram ads it is basically that sort of screen with a high quality laptop built-in. I like it because it focused on what laptops are good at without needing software updates that won’t happen.

The presence of tablets at the show is substantially less than previously. In the Apple world, tablet evolution is clearly one where the improvements in PC silicon and software as a result of silicon (power management, security, etc.) have made their laptop value proposition a superset of the iPad even as iPad run rates continue to be enormous. In the non-Apple world, tablets seem to be used as utility screens for point of sale, signage, and in other places where touch and durability are key.

The biggest presence for a tablet on the floor was the Samsung Galaxy Z Trifold. This is a case of the industry continuing to pursue folding screens. I swear the industry is going to will this form factor into our hands one way or another. Around the show you casually see way more folding devices than you would in any crowded space in the US in general. The presence of much of the Korea GDP in attendance might have something to do with this!

The Z Trifold is no doubt an incredible device. Geeks love folding convertible devices and always have (Surface!), and the trifold has it all. It’s a phone. It’s a bigger phone. And it is a tablet. Just keep unfolding it. Samsung has done a bunch of work to enable the Android platform to somewhat gracefully handle the screen dynamics including a model that basically runs three apps side by side. My general issues with double or triple folding are overall futz factor and the size. As with a PC versus iPad having windows can be helpful but more often than not you have to devote cognitive energy to arranging and managing windows that just isn’t that beneficial. For me the bigger problem is I can’t figure out how to effectively or efficiently type. I generally fold the device to type. I love the idea of having a big screen for video but maybe I just don’t watch enough long form video on a phone. For productivity I struggle with the bigger screen. Needless to say, right now in the tech scene I’m the minority and Reddit went crazy over this device.

The mini-PC form factor was everywhere and not just for AI PCs. In many ways these are the modern PC desktop outside of gamers (which I’m not going to cover in this trip report though there was a big and significant presence). The benefit of the mini form factor is for ports and ergonomics in a home or office environment especially with multiple monitors. The low power consumption and mostly laptop-level fan noise are great. Enterprises love these for ease of transport and because the useful life of a display is even longer than a PC. The price is great too. Below is a Geekom updated one. I’d get one like this.

Home, Automation, Security

Devices for the home represent the heart of CES after television and audio. If you’re not a professional installer with dedicated shows (appliances, security, custom homes), CES offers the best chance to see the evolution of this broad range of devices but also the complexity being pushed to the home.

The continuing challenge with the home remains integration of devices classes (power, switching, plumbing, lighting, locks/doors, cameras, major appliances, and safety/disaster). There’s a fork in the road with all devices. Do you go with major existing brands and wait for their own “smart” platform which almost never integrates (for example, garage doors)? Do you choose to make a device smart by going with a brand-new vendor in an area that often lacks a long-term track record for maintenance, parts, repairs and is often disconnected from all legacy approaches (lighting is the best example). Or do you choose a class of smart add-on capabilities that integrate with legacy infrastructure (like a Nest thermostat).

I’m basically a fan of the latter. I literally can’t stand the wholesale “new” stuff for a home because the last thing I want is 10 years from now needing replacement parts that don’t exist from a company that doesn’t exist with preconditions I can’t replace. I currently have that problem with Lutron (a MAJOR manufacturer) light switches which I scour eBay for needed replacement parts. In the past I have covered the non-integrated smart platforms but that’s another area where I’ve been burned as a consumer (aforementioned garage door, Chamberlain, which cut off HomeKit support). I have no patience (literally) for this type of home futzing and no tolerance for a poorly integrated home experience which I define as “an app for every system or device”.

In this context, CES made substantial progress this year and that is where I’ll focus. The Matter standard—championed by Apple HomeKit—has seen fits and starts but is really coming together. Even if you don’t use HomeKit, the presence of Matter has elevated platform support and integration across devices. Plus, it has made setup much easier. The main integration points are Google Home, Apple HomeKit, Samsung SmartThings, and Amazon. Across those there are many common devices from third parties but first party devices when they exist often don’t hop ecosystems.

In the following you can see how both SmartThings and Amazon have continued to expand partnerships and first party devices. The partners across all the platforms are mostly the same which is great for everyone.

Looking above, Amazon added several first party sensors announced at CES including an OBD2 car alarm, air quality monitor, and sump pump monitor. Amazon has done a great job integrating with legacy sensors especially safety owing to their work with professional installers. For example, they have a Ring Alarm add-on that can replace a wired alarm and use those door sensors. They have a smoke alarm sensor that listens for the alarm and reports that in your Ring App/Alexa as a fire alarm.

There were many new models across door locks, thermostats, switches/plugs, and more. Many companies offer complete product lines of these that integrate across Matter and older standards. Buying these on Amazon itself is easy as well. The only caveat is you might get cut off from firmware updates if the company vanishes and some might see the security risks of these devices as noteworthy. I do.

Security cameras and systems are like plumbing, HVAC, and electrical in the sense that few of them integrate effectively into a single home app from the platforms. Even Amazon which offers Ring cameras and home control (and Wi-Fi) still show many integration seams from acquisitions. HomeKit has limited camera support so far. That said, home cameras are becoming a requirement and the various world events that took place during CES show how those security cameras are a vital part of home ownership.

I have been a Ring fan since the earliest days and find the experience great. That the doorbell is part of an incredible array of cameras and the alarm system is fantastic. Amazon does sometimes get a bit complex as to whether they are a direct to consumer or professional channel-supported brand and the products often teeter. The new 4K home cameras are great but have too much of a low-end consumer industrial design for a device that should be a bit more robust, professional, and stealthier. At the extreme they added some big outdoor cameras that will look great on a loading dock even though you’d probably love one for the whole back yard.

At the extreme Amazon introduced a job site security system on a trailer! This seems to go with the job site Eero introduced at a previous CES. I kind of wonder if the primary customer for these might be Amazon itself? Below is a trailer with a solar panel, battery, and giant outdoor 360° camera.

While there are some standards that connect third-party cameras, you still have to buy into a hub and with that an app and potentially third-party monitoring. All of the cameras at the show are now doing some sort of AI image recognition, owing to the fact that most come from China where this is a primary scenario. This year all the new cameras are 4K. What I found most interesting is the addition of integrated solar panels (versus the add on panels of past years) and the addition of secondary cameras for more field of view or even infrared.

Finally some companies are adding 4G/5G connectivity thus making the cameras completely wireless.

Cameras are becoming AI “edge” devices. In fact many commercial systems are themselves either incorporating edge style AI computers or equipping legacy cameras with an edge style endpoint providing computation and connectivity. This system below from Sixfab is using the equipment shown to process the many cameras on the screen to do scene and person identification.

What is most interested with respect to cameras, however, is how security is evolving to NOT use cameras. A number of approaches were on the floor using mmWave RADAR or even Wi-Fi signals to monitor a home or public space so as to preserve privacy while providing real time monitoring.

A kind of scenario where this matters is in the home where you don’t want to constantly video monitor the living room or a bedroom but want to know presence, breakin, someone falling, kids or pets fighting, and so on. These systems put a small device on a table or shelf that connects to an app. They use AI to transform the sensor signal into alerts. They can monitor sleep (or sleep walking/waking), nursery, changing in lighting, entry/exit a room, falls, or in a public space even crime or unwarranted contacts.

Restroomguard is one such product that provides security for public restrooms, clinics, or dressing rooms, and more. The range of sensors is impressive.

For the independent-living aged population, a number of solutions were shown. One of them—Silvershield—even uses the phone’s camera to map out the room and provide even more accurate representations of furniture to identify potential falls, bumps, or obstacles.

Acoustic Eye uses cameras and microphones to provide aerial coverage of a space in order to notify the presence of drones. The device attaches to a window. Cool!

Old-fashioned home appliances remain targets of the onslaught of AI. There’s been a desire to connect legacy style appliances to the internet and now to use AI. I found the internet connectivity for the kitchen and laundry room to be worse than a bust, but an actual negative. My feelings have not stopped the ongoing attempt with AI.

What bothers me most about the connected/AI appliances is that the claims are about cleaner, faster, easier, but that doesn’t seem to be the case in practice (for the few I have). But they are more expensive and they seem generally less well made and certainly will be obsolete sooner.

Using AI is great of course but also can be dubious. This washing machine uses AI to better understand the floor and adapt the W/D to the floor surface. But the floor surface doesn’t change underneath. I’m confused.

Does AI really need to be used to identify the clothes?

One category that seems to be getting better even without AI and connectivity are vacuum cleaners. The combination of improvements in understanding the physics of suction (!) and battery/motor technology is truly improving things. I do really like the new vacuums that have floor-based charge stations. The upright stick models that used a wall mount charger bugged me because I don’t like mounting things in the wall if it can be avoided. Even though the demos were just sucking up inordinate amounts of Cheerios, the demos were compelling.

Finally, home appliances offered a great chance to see how a company can just “appear” to the US market but has been on a long journey. Dreame is a Chinese maker of vacuums that started a decade ago. This year they had an enormous booth and a product line covering everything: vacuums, TV, Smart home, small appliances, Air conditioning and quality, personal care, laundry, and refrigerators. They had a catalog the size of a paperback novel. Totally wild. Their booth represented a product line like Panasonic or Samsung and was at that scale.

Health

The biggest thing on display at CES has always been the divide between consumer health and wellness and FDA-approved medical care. Every booth is a discussion of either how a device is useful and valid even though it isn’t (and doesn’t need to be) approved by the FDA, OR it is a discussion of how it is in the process of seeking FDA approval. This year was no different. The show tends towards the non-FDA world which is why when I see something approved it is worth a good look.

The wellness trends have been huge, but are really in full force now. There were countless bands, rings, watches that measure body telemetry non-invasively and the process that telemetry to provide some form of wellness scores. It is impossible to provide any insights on these products without trying them. This is one where making a platform bet is a key decision. For many the form factor will drive the initial choice, a two-way phone-integrated watch, a discrete ring, or a sensor band are the choices today. There wasn’t much new in this area other than more of all of those.

Many in the outdoor sports world are fans of Garmin. They introduced a new Forerunner GPS watch. It had a lot of new features. One of the cool ones was a red/white flashing light that serves as a safety measure when running. It has a long duration battery due it its huge size.

Also, for athletes (and more perhaps) is a new sensor that measures lactate while exercising. The noninvasive sticker sensor goes on an arm or wrist and measures the content of sweat. The first one measures lactate for endurance and mitochondrial health and primarily aimed at lifestyle improvements. The vision is to add biomarkers to measure cortisol, creatinine, and glucose for comprehensive health insights.

Sleep is by far the category with broadest coverage and also converging with AI. Every one of the above devices also acts as a sleep monitor. There were also countless mattresses and toppers that provide sleep measurement. I know for me waking up to two different sleep scores plus how you really feel is probably more stress than anyone needs first thing.

The most basic body telemetry is weight. Withings has had some of the earliest connected scales (along with other connected health devices). The company introduced a new Body Scan 2 scale. This is a scale with an extendable impedance grip device. The scale measures a whole host of biomarkers and does a longevity prediction that is more detailed and precise than the previous generation. It said “muscular thin”, so I was sold. The device connects over Wi-Fi and integrates data with Apple Health. They are definitely pushing a monthly/yearly plan and much of the analysis slides into paid-only so be on the lookout before buying.

Quite a few devices especially those from other countries are designed to be deployed by and used with a primary care doctor. In many countries these startups are funded/supported by the national health services. One cool example I saw was a Korean company, exoFit, that designed a reusable stick-on patch that measures body composition, EMG muscle activation, gait, motion analysis, and more. It takes the collected data and provides “AI-powered” analysis for training and rehabilitation using the accompanying dashboard. The software is detailed and technical designed to work with a specialist. Thus, it includes the full occupational therapy/rehab plan and compliance.

Many devices on display are just designed to be better at what we have always measured, but better because of form factor and connectivity. Another Korean device I liked was the Thermosafer XST600 (!) which is a core body temperature sticker that provides a connected and continuous measurement. There’s a little sticker you place on the body forehead) and a pair it with a gateway and monitor which can then display the temperature on an app or a multi-patient console (or feed the data to an EMR system). The motivator for the device was covid and viral infections. I love these simple improvements.

I loved this finger blood pressure monitor. Interestingly they created two models one with Wi-Fi and one with cellular. It is deployed via hospitals/doctors for monitoring where connectivity is important and with many patients, Wi-Fi isn’t an option at home.

One badly needed bit of body telemetry (at least until the world is on GLP1s) is continuous glucose monitoring. The current minimally invasive patches are widely used (as I see in yoga class) but not particularly convenient and costly. For a very long time there’s been a search for a non-invasive measure. Many believe that AI will unlock some telemetry that will prove correlated with blood glucose. Every year there are a handful of non-US companies that claim to have a solution that never breaks through the FDA. There were several this year (and one I see on Instagram ads all the time). I saw a ring and a fingertip system this year. I will wager these won’t make it.

PreEvnt is a US company with a new implementation of an old bit of telemetry. It has long been known that your exhaled breath changes with blood glucose level. The correlation to time and level has been difficult to model as well as the specific elements. Isaac is a small “breathalyzer” form factor that measures volatile organics/acetone and couples it with an AI model to deduce glucose levels.

After low back, foot problems are one of the most frequently reported conditions and often go undiagnosed and untreated. The sensors have been around for a while but getting duration measures and correlating with conditions has remained unsolved. There have been shoes and insoles in the past. This year the Orphe insole combines those with a good deal of software in an effort to diagnose and treat a broad range of motion issues as well as falls. The insole has six pressure sensors that provide motion sensor-based gait analysis and software that can help directly or couple with third-party software for more analysis.

Not all of the products were devices. One product I was fascinated by was XRaedo from a Korean company that has a number of health related XR-based (extended reality) products. XRaedo creates a full motion A/V avatar of a loved one that has passed. The platform enables interaction and supervised grief counseling. At first this seems kind of creepy but as we see generative A/V arise from small samples and combining that with LLMs and training corpora based on real life first party materials, it does seem that recreating loved ones (or historical figures) is going to be a feature we will all have easy and low cost access to.

One of my show favorites was Triage 360° from Omedus, a US company based in Nebraska and founded by a triage nurse who worked through the pandemic, a physician, and a former Air Force officer. The product provides a high-tech addition to first responders of mass casualty events. Today triage is a color-coded arm band and a sharpie with a lot of verbal communication and physical separation (watch the tv show “The Pitt” for a good demonstration of this). Triage 360° is a crash case with a bunch of reusable modules that attach to the chest. These modules have the same color codes but also provide basic and needed telemetry, wirelessly sending this back to a console that can be monitored and adjust triage. It is not hard to see this product in stored in any location where a mass casualty event might unfortunately arise.

Robots

I came to the show certain I was going to be overwhelmed by robots. In a sense that was true. There were a lot of robots. The only problem was most of them weren’t working. My view there were three types of robots to be seen:

Articulating arms and hands. While I won’t call this a solved problem, they have been used in manufacturing for decades. What is new is setting them up, training them, and how they function in the face of ambiguity. AI has dramatically improved these and it is easy to see we’re going to have a lot more sorting, picking, welding, attaching, and so on to drive “lines” of all sorts. Below is a set of arms that pick off a shelf at a robot-staffed modern Automat.

Roomba style autonomous machines. I was (again) blown away by the number of lawn and pool robots. I spent my youth mowing the lawn and cleaning the pool so can appreciate these, but I had no idea cheap teenage labor was in such short supply :-) Lawn robots are becoming larger and more tank-like for sure. These scenario specific robots cover everything from aforementioned lawn and pool to other scenarios such as warehouse delivery, construction site material movement, commercial office cleaning, and warehouse stock movement, to just name a few. Again, these are vastly improved and independent with the new layer of AI software and sensors driving them. There are going to be many many many more of these. The unifying theme of these are the docking stations so I suspect new offices and factory floors will be developed with dedicated docking space, something you see on luxury custom home TikTok for Roombas in kitchens today. Below are a few examples of this style.

Humanoid (and four-legged) autonomous machines. For many the progress as evidenced by CES seemed slow. The demos were a chorus of failures for sure and reminded me of so many speech recognition demonstrations of the past. There’s a feeling these are always a few years out. There’s no denying the progress and given the pace of autonomous driving, it is fair to see the set of problems these devices face will dramatically improve. Will they get broadly deployed in a few years? To say no, requires one to bet against Elon Musk which I am definitely not willing to do.

Here are a couple of humanoids. The first picks items off a shelf. The second is one of the defensive Boston Dynamic “dogs” but it wasn’t quite lively at the show. The third are just some robots standing there suspending by humanoid robot racks.

By far the EVW-1 was my favorite robot demo. It is an assist device so robots of the Roomba class can make their way up and down elevators. The robot somehow summons an elevator (which was a step they said could happen with a Wi-Fi command) and then via another command select the floor. This robot then slides up and down and pushes the button. I wasn’t sure why the same Wi-Fi API couldn’t press the button, but I digress. Presumably a full humanoid robot does not need this help. So, this is only for when R2D2 is alone without C3PO.

This one was pretty cool. And really does show that ample opportunity to turn jobs that are difficult at best into jobs that manage, maintain, repair, and keep supplied the robots.

I refuse to be cynical about robots both in the “always 5 years out” view and in the “they are net negative for jobs”. I think the demand for robots is infinite and the more we use, the more jobs get created, just as we saw with transportation as autos created whole new classes of jobs for humans above those in horses (and many more jobs).

Mobility

As mentioned way up at the top, a big chunk of exhibits from past years that were not at the show this year pertained to mobility, particularly autos. I welcome that reduction even though mobility is deeply connected to all the technology work I love and follow.

The show featured a small amount of micro mobility—scooters and ebikes and other assorted ways of moving around in an urban or warehouse setting. There was also a collection of full exoskeleton suits that seems to be increasing in display for both individual and commercial use. While more health related, there were a number of joint-specific exoskeletons such as for knee or arm.

For me there’s one strategy that really matters for mobility and that is autonomy. Like PCs, I believe human-driven vehicles (particularly but not only gas combustion) have reached their saturation point. While obviously ownership will increase, the technology has plateaued and the growth scenarios for vehicles are in autonomy. I believe like mobile phones, it is likely that parts of the world that have low vehicle ownership today will leapfrog human-driven cars once the road infrastructure and economics are in place.

The national companies building GCE all seem to have either retreated or struggle with EV transition. It seems the case is clear that the model of in-house integration and manufacturing of broadly outsourced design and engineering has made it nearly impossible for existing automakers to transition to EV. China is clearly leapfrogging the gas engine with new companies like BYD. Still the existing GWA known for heavy equipment made a big showing of its line of consumer-oriented EVs. They are a distant number two but making a run for it.

The San Jose-based company Tensor showed off its “designed from the start for autonomy” passenger car. Tensor, like much of the whole auto industry, make use of Nvidia compute on board. The several not-Tesla, EV-first makers have also been struggling in the US. This is very tough.

While I laud the efforts at innovation, I don’t think it is necessary that we keep reinventing driver interiors and dashboards for manual driving. It is costly, has uncertain benefit, and right now the safety record is dubious. There were far fewer customizable dashboard components at the show.

Along with Zoox providing transport around town there was Waymo. Waymo had a giant booth. A lot of people in the booth don’t live where Waymo is offering service.

There were assertions of all sorts of autonomous vehicles for commercial use from Bobcat earth movers to heavy trucks. My favorite are the small private property/warehouse people and supply shuttling vehicles. I fully expect to see these shutting around suburbia soon enough.

I loved this “All-in-one" retrofit autonomy kit” specifically designed for military vehicles to provide field deployment. You add this to the tank and mount the various sensors depending on the level of autonomy desired (scout, ranger, commander).

Lifestyle and Accessories

My favorite section is the most personal. This is about things that we all use and make life a little more fun or better. No long essays needed here, just some cool stuff with comments in the captions.

I want to start with a show favorite. This is a super tracker. It works with both Android and iOS and seamlessly taps into those phone-based tracking tools. It also features a QR code which can be scanned (so no find my needed) and connected directly with the owner. To solve the “how to attach” problem it has a built-in connector which easily works with a bicycle tube, handle, shoelace, or strap. The last feature is it uses the cell network to provide positioning by receiving and triangulating. I was not sure how it transmits this or makes use of it. I will let you know as I ordered a pair from Amazon.

This AirTag is built into the bell on a bicycle or scooter! Reflying is an ODM and always has a lot of creative location solutions.

Every year there is some new charger or cable that you just see everywhere. It used to be that to learn about this you had to go to Japan where they appeared first at retail. Then they started showing up at CES looking to find distributors. Now most of these are on Amazon before the show. That was the case this year with both the “saw these everywhere” chargers. First there was the retractable cable charger that packages a 40-65watt charger with a short cable and often an additional plug or two. The deluxe models of this feature a tractable MagSafe stand. The problem is they don’t have the output to power all the ports based on my experience. The other device is a flat box with a mains cord and several mains receptacles along with some USB-A/C ports.

There is clearly a race to build the charger with the most output. The highest rating I found was a ridiculous 370 watts. Ironically this was branded by Monster who used to have a booth selling magical analog cables with silver and nitrogen in the wire cases.

Aukey (not to be confused with Anker) offers a nice view of how these accessory companies all offer a FULL range of the same accessories.

These cables/chargers combined a SIM slot for the purpose of acting as a cellular hotspot. Pretty wild. Feels like a spy device.

From the same company, this is a physical SIM card that itself supports a dozen eSIMs. You put this physical SIM in your (Android or non-US iPhone phone) and then you can load it up with eSIMs. I think the app for loading only works on Android.

Moving on to connectivity. There’s been a rise in a micro category of mobile hotspots for use off of public Wi-Fi or wired networks. This provides a level of security or often VPN access as well. I travel with one though I couldn’t get it to work at the hotel this year! They like many things go from cool idea to wowza that’s a lot, probably too much. This one is HUGE and is more like a stationary router at this point. The big addition is a screen for doing all the management on device.

ASUS showed the first live demonstration of Wi-Fi 8! (I am still not on 7). The booth showed it to be faster. The stated goal is to be better for a lot of low-bandwidth consuming devices. In the photo the thing with all the antennas is the device and the hexagon-ish model is the proposed final form factor. Also, Asus it is Wi-Fi not WiFi.

At the other end of connectivity, there were several demonstrations of LoRa and Wi-Fi HaLow™, which share a portion of the megahertz spectrum in the US. HaLow is Wi-Fi 802.11ah for low bandwidth IoT devices that benefit from very long-range connectivity. This is what could be used in a giant open field or very large warehouse/factory floor. The devices look like Wi-Fi chips but they benefit from a bigger base station antenna. Below I included a bandwidth explainer for fun :-)

The product Rockland LowMesh is a LoRa radio that has a transceiver that pairs with a phone (that does not need cell/Wi-Fi for use, just BTLE) and allows a private mesh network over long-range (longer than family radio). It also has a base station to even further extend the range. They sell a whole suite of connectivity tools for the platform.

MileFlask by ShowMo, a security company based in the US, has a HaLow-based camera solution to provide security/surveillance for a multi-mile area.

Handy bandwidth/frequency explainer:

I don’t like using my phone on a plane because there’s nowhere to put it that isn’t too far from me. I loved AVP but that was a schlep. These headphones which can be plain audio, feature a cool “screen” integrated that you can stream from your phone. Pretty wild and very nice ID. Not available yet but can’t wait to try out on a trip.

These earbuds were wild. They went beyond noise cancelling and were basically voice isolation. They would play a bunch of loud music like a conference, but you were able to carry on a normal conversation.

HDMI introduced HDMI Ultra96 which is 96Gbps. The key is HDMI is now like USB-C in that you can’t tell if a cable will work because the connectors are the same but the wires inside are different. So kudos to the EU for this victory.

We’re addicted to our Gardyn (so are the kittens). I love these home planters using AI, lights, and water. This one lets you use your own soil and doesn’t require pods. But still has all the AI monitoring you’d expect.

This planter uses prepackaged themes/schemes and uses all the fancy tools to help you keep them alive. It looks very nice in a room too.

Speaking of cats, this is a body composition scale for pets. I can tell your firsthand our cat would not be happy with this as he is just living his best life.

And Finally…

Just a few things that made me smile or something…

This was kind of…creepy.

So was this.

If you made it this far then you’re probably as exhausted as I was on Sunday afternoon hitting publish. What I’d ask you to do is just take a deep breath and think about the millions of people directly employed by everything in those 4100 booths. The thousands of people that worked 7x24 the week before building the city and then tearing it down until mid-week this week. All the work they put in is mind blowing. And think of the 50,000 or more people who spent hours in booth duty or in meeting rooms buying, selling, explaining, partnering, and more. There is nothing that compares to the learning from booth duty. I want to thank all the people I bugged with questions or who without skipping a beat ran through the script for the 100th time. Thank you!

See you next year!

Notes. I visited the whole floor but still didn’t see everything so I know cool stuff is missing, especially if it wasn’t on display. I only attended a few of the private/press events. Nothing here is an endorsement. No products or links are sponsored in any way including free samples. I took all the photos unless indicated. I am sure I made mistakes or missed something and take full responsibility. I estimate there are a dozen typos and garbled sentences in here and those are my fault and I appreciate the reports. You try typing this up after walking 40 miles ;-) No LLM was used in the production of this report. No market or financial advice is intended in anyway. All views are my own, 100%.

What a year it has been. It has also been a year where I chose to read books from a wide range of topics, some well outside the technology and innovation non-fiction I almost exclusively read. With books on Apple, Nvidia, China, and AI there was plenty in my traditional wheelhouse—some very good and some not so much IMO. Like many hot topics there were …

Now imagine when even the author hasn't read what was written... yikes. How does AI writing and reading impact this reality?

The Paper and Its Premise

At a technical level, the paper asks important questions and answers them in super interesting ways.

The paper was written by Apple researchers including an intern, The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity by Parshin Shojaee†, Iman Mirzadeh, Keiv…

For those deep in tech, AI is clearly a new paradigm—a sweeping theorem of software. Most paradigm shifts precede new tools. But with AI, we fast-forwarded: from paradigm to tools in under a decade, now used by hundreds of millions. That speed doesn’t soften the typical reaction to new tools—fear, skepticism, even rejection. We’ve seen this with every major shift in computing. This post shares a few examples of that resistance in action.

On Bari Weiss’ Honestly podcast, a recent debate tackled: Will the Truth Survive Artificial Intelligence?

The “yes” side featured Aravind Srinivas (Perplexity) and Fei-Fei Li (Stanford); the “no” side, Jaron Lanier (Microsoft) and Nicholas Carr. I won’t spoil the debate, but a major theme was concern about learning, writing, and education.

AI is a tool. Tools abstract and automate tasks. Each new one adds abstraction and automation over what came before. That’s rarely controversial—until it touches something people are emotionally or professionally invested in.

Case in point: teachers once opposed typewriters in class. They worried students would forget how to write. They were right—by college, I could barely write cursive. But typing papers was faster and easier to grade. Teachers opposed calculators for fear of failing to add. But now engineers skip the slide rule and get vastly more done with libraries of routines and more.

My freshman year (1983) was a turning point. Two quick stories:

First: Most students arrived with typewriters—graduation gifts. You were expected to turn in typed papers. Rich kids had “fancy” models that let you backspace before a line was committed to paper.

Meanwhile, the university had a few WANG word processors—business-grade machines—available to select writing sections. Faculty were worried: if students didn’t handwrite first drafts, would they learn to write at all? That exact fear came up in the podcast too.

So we ran an experiment. Most students used pen and paper, then typed. A few of us used WANG machines for everything. Faculty planned to compare the results.

Then came January 1984. Macintosh launched. Apple pushed them onto campuses. What the faculty hoped to study was rendered moot overnight. The tool leapfrogged the debate—just like GPT did two years ago.

The real issue wasn’t just speed. It was abstraction. Word processors offloaded spell check, formatting, and editing—freeing us to focus on content. Educators already complained about poor spelling before grammar checkers showed up.

Second: I was a computer science major. CS was a new discipline then—separated from electrical engineering in the 1960s. Its foundation? Abstraction: you didn’t need to solder circuits to build software.

This wasn’t universally accepted. Many schools kept CS under engineering, requiring EE and physics. That meant you still learned transistors to write code. My school dropped that. We were among the first CS majors who didn’t take physics or EE—and some argued we’d never truly understand computers.

They were wrong. That too was an abstraction.

AI is the next abstraction layer.

And like all previous abstractions, it’s criticized on two fronts:

• Loss of fundamentals: New users won’t understand what came before. That’s true. But also true: they can do far more than previous generations. Abstraction is about not needing the old tricks. No one misses manually hyphenating or footnoting on a typewriter.

• Lack of understanding: Critics say people won’t know how their AI-generated results were made. That’s a weak argument. When a carpenter uses a nail gun, do we say they no longer understand roofing? I know what my computer is doing even if I’m not flipping bits manually.

So why the negativity around AI in learning? Is it just a replay of new technology in schools?

It’s not unique or new. People say students will get lazy, not “really” understand, or miss what “matters.” The same was said about word processors. And Macs. And dropping EE courses.

Growing up, we were drilled on how to find things in the library—but never allowed to use the encyclopedia. That was “cheating.” Odd, since many families invested in full encyclopedia sets.

Then I discovered the almanac. Game over. I won every classroom research contest using that book. We bought a new edition every year. It felt obvious. That instinct is why my dad bought an early PC. My first thought going online? “Now I’ve got a real-time almanac—at 300 baud.”

What we hear today about AI—worries about truth, AGI, or education—isn’t really about those things. They’re dressed-up ways of resisting change.

Writing and learning with AI is the typewriter, the word processor, the encyclopedia, and the almanac rolled into one. Seeing it as something scarier than that is just fear of new tools and new paradigms. Again. It is not surprise that we're seeing so much writing about concerns—writers are the ones who are directly challenged. Just as electrical engineers were challenged by software abstracting out hardware.

Some will say not all abstraction layers are created equally. Not all tools are “harmless”. And they would conclude if they believe that about AI that AI needs more scrutiny sooner and that we should slow down before we understand. The challenge is the future doesn’t just wait around for everyone to come to a consensus. It arrives with new tools in hand. That’s what happened in 1984 when Macintosh arrived. That’s what is happening with AI.

AI is here. It’s already happening.

The docs are pretty straight forward and it is easy to see why everyone from developers to app providers to enterprise IT are excited by it. Essentially MCP is a way to broker requests between AI providers and consumers while integrating with local data. Using the MCP terminology, a Host might be a desktop tool that wants to access AI from within the tool (like an IDE). Clients maintain 1:1 connections with Servers which are programs that exposes specific capabilities through the API (think of a service). Along with that there can be Local Data and Remote Services which are as you’d expect. It all makes for this tidy picture:

At this early stage of AI every one wants “in” and wants to start building but at the same time everyone is afraid of lockin on the LLM side and everyone surfacing AI in their existing products is afraid of their value add getting sidelined by native LLM capabilities. Having an API that allows LLMs to claim integration with any existing product is a clear win for any LLM trying to build a developer platform. Having an API that allows any developer to plug in a different LLM is a clear win for those products not wishing to put all their chips behind any one vendor. Enterprise IT is excited because one big promise of AI, especially agentic AI, is that everything will connect to everything.

MCP is quite definitionally the classic middleware playbook. That it was introduced by one of the key leaders in the field is itself a classic aspect of the middleware playbook. The industry has a long history of middleware. Many might not recall or even know, but the initial Dept. of Justice antitrust case against Microsoft was all about middleware and at the time the browser itself was viewed as middleware, as was Java. That there was one case about two instances of middleware that were supposed to also replace each other shows the complexity of introducing middleware.

The term middleware appears 38 times in the Consent Decree from 2006 but this is the key definition:

and

The point of middleware is always the same— integrate things on one side with things on the other side. The promise is always that betting on the middleware allows a single party to avoid relying on any instance of one side of the equation while being able to take advantage of the full breadth of market capabilities on the other side. Middleware is supposed to make it such that the best product wins for every customer. The customer being in the middle of both sides of the middleware. It means no one provider (or service) can dominate by monopolizing all consumers (of services) while consumers are placed on level playing fields with all their competitors.

All cross-platform software is a form of middleware. The creators of cross-platform middleware promise to make their middleware run on all operating systems while all the vendors using the middleware layer are granted freedom from worry about the nitty gritty of different platforms.

My own personal experience has seen everything from C to object-oriented programming to application frameworks to SQL data connectivity to business intelligence to HTML to browsers themselves all come and go as middleware solutions. Everyone even today knows a browser isn’t one thing but many. Even more history, when Microsoft started as a company (50 years ago) its claim to the market was creating BASIC to run on all the microcomputers of the time and then build its first MS-DOS applications to do the same using a proprietary middleware toolset which we still actively used for Word and Excel across Windows and Mac when I was a new hire until Office for Windows 95 and eventually Mac Office 98.

That’s enough background but will circle back to this point in a moment as to why this is challenging.

Middleware never quite lives up to these promises in practice. MCP, if history is any guide, will go down one of two paths:

1. Everyone will use it.

2. Everyone but one key platform will use it

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When (1) happens two things will be true. First, no one will effectively monetize it. Second, every vendor will also add unique aspects to how they consume (client) or produce (server) the interchange. This is internet networking, TCP/IP or HTTP. For (1), in practice the resulting feature is low level enough that all the interesting things will happen on top. Remaining at a low level can happen as something goes from "new and cool" to building out broader capabilities on top of the low level bits. You can think of the full HTTP stack as adding value all on top of the basic protocol.

When (2) happens that is because one platform is the leader along with our industry that has a long history of "everyone but.." APIs/protocols used by everyone but the leader. Usually by the time this leader "comes around" to being a first class citizen, it no longer matters as the industry has moved on to the next big thing as a center for innovation.

The reason this happens is because at the heart of the matter anything that everyone might want to be a producer/server will only retain its position if it has a user experience that is unique and monetizable. Eventually, one of those consumers will also become a competitor at being a server. Things then blow up.

Everyone that wants to be a consumer/client will be trying to consume *all* the other servers out there. They will, however, always be missing one important server, the leader who is busy trying to also become the consumer/user experience. Consumers who rely on everyone else being their server are in for a surprise when they see the lack of motivation to only be a server. Every enterprise customer, for example, will always be fighting to get one vendor to "open up". See how identity/security have evolved. There’s adverse selection in that the second and third-ranked producers and consumers often sign up eagerly for the middleware API in hopes of gaining distribution and/or traction.

On the whole, HTML followed this path. Everyone thought all the UI would just converge to standard HTML and consume XML from servers (or some variety of that). What happened though was that all the data people wanted to build their own user interface to maintain control of their data/server/service. And on top of that the definition of HTML took on many vendor specific implementations. No one directly monetized browsing (some even de-monetized it) while it took 15 years to get to implementations that reached 90% feature compatibility.

Why is this? The biggest challenge with middleware is that for it to be successful and not stifle innovation middleware needs to be the sum of all the capabilities that it chooses to integrate. Middleware always starts off simple because it always starts off in the earliest days of new platforms. The platform is just simple so it is easy to envision middleware. As mentioned that is when demand for middleware is the highest because uncertainty is the highest.

In 1989 no one was sure if Windows would work and if you were to pick up any computer industry press it was filled with evaluating new products based on which platforms they worked on. I spent the first 3 years of my career trying to make Windows, DOS, Mac, OS/2 apps all the same by building middleware. It was not difficult to write an abstraction layer for the 150 or so APIs that made up the core experience of each of those operating systems. I literally knew them, the error codes, the parameters, and more by memory. I still do. But that is a single point in time. Today iOS has 250,000 APIs. AI has infinite APIs. See this post for more on cross-platform.

I get it the excitement. The key realization I came to and talked about at the first Win32 Developer Conference when Windows 32-bit was announced was that to be great at working across all the platforms that were interesting, a toolset/framework needed to be a superset of all the capabilities of those platforms. To build a superset meant that building successful middleware required a development team the size of all the other development teams. I also knew how fast Windows had grown in just 3 years since Windows 3.0 and how many people were working on expanding it.

Now everyone always has their favorite example of when this works or how it worked for them. Games commonly get talked about as following a great model. Except games integrate poorly with every host they run on. Game runtimes in effect create a purpose-built OS for running games and offload a vast amount of work to game developers.

A cleaner example is database connectivity. In the world of structured data everyone wants to be free of Oracle in the enterprise. But there has never been a production API that could easily “choose” which database to use. This is wild when you think about it because SQL data is extremely well-defined. But in the real world, the performance characteristics for any non-trivial products using SQL vary depending on how Oracle or any other database might have been implemented. While the semantics might be the same, the implementation was different.

Anyone who has build cross-platform mobile applications knows how much Android and iOS have diverged, and they started from a huge and complex API that was already difficult to make cross-platform. And every web developer knows the ins and outs of browsers, even after Microsoft converged on Chromium. Meanwhile everyone from Oracle to Nvidia to Apple to Google wake up every day to make the job of making software work across these platforms with middleware even harder. It is literally the business strategy.

The other side of this is the consumer side, that is the side of the equation that wishes to present their product as integrating with all other products. This always seems benign enough. Who would not want to be able to pull data from every system into Slack or Notion or even Excel? Everyone would.

But there is a challenge with that in that the transformation from the user experience and data semantics of that tool to those generic tools that everyone uses all day is lossy. What does it mean to “use Excel to analyze Workday” or “use that applicant tracking system with Slack”? These integrations often make for good demos but the edges quickly show. Data can be viewed but not modified. The product can add new capabilities but the integration experience fails to show them off, even when that might be required. Very quickly what seems like an enormously customer-friendly solution if you’re Slack of Excel turns into a nightmare if you’re Workday, Salesforce, or something else. In fact much like the platform vendors who wake up making it harder for middleware to commoditize them, these application providers wake up every day trying to get people to stay in their tools and see all the capabilities.

This is why even when middleware works, the economics aren’t there. Or when it works, there’s always a set of key players—providers or consumers—that aren’t participating because they want to be “on top” and have the market power and customer base to do so. For every Oracle there’s a Microsoft SQL Server trying to be more open and win that way. And there’s always the open source alternative being used in large numbers but less so at massive scale (always the MySQL+Oracle strategy anyway).

All isn’t lost. The key reason that middleware can win and become the standard is when a company solves the middleware problem so well that it becomes the platform itself. In a sense it rises above being in the middle and becomes the actual platform. There are two examples which let me circle back to how I got the the (1) and (2) at the very start when it comes to how MCP can be a success.

It is possible for middleware to become the platform and win, but win hearts and minds but not the economics. Ultimately that is what happened with Google Chrome and browsers (at least for a “generation”). One can debate the economics and whether having that default search engine and cookie handling and so on had economics but there’s no debating there are no direct economics. The browser remains middleware. Unless you use a Chromebook, you run the browser as middleware on iOS, Android, Mac, Windows, and every other device. Google retains outsized influence on the direction browsers will go but also because it lacks full penetration across devices developers will be less likely to adopt new features. Winning isn’t so great sometimes.

It is possible for middleware to win and include everyone but one important vendor. That is what happened with identity and access management (“directory”). Okta became the market leader in a category that started off as middleware. They did so by solving the problem of integration even as the then leader, Microsoft with Active Directory (AD), refused to participate at every step. As it turns out Microsoft’s history at winning with AD played an important part of failing to recognize the importance of Okta to customers and the very need it solved.

Briefly, Microsoft “woke up” to the power of the directory when Erich Schmidt made a bet while he was CEO of Novell (before Google). Schmidt posited—based on doubt on his experience at Sun in the Unix era—that the PC networks will need a directory. Microsoft saw that and reacted by expanding AD into a competitive position. Because Novell was losing the server market, Microsoft’s AD was able to win by being part of the server market. Netscape then came along and pioneered an open source academic project, LDAP, in an effort to provide an Internet scale directory. While AD was woefully inadequate for the scale LDAP could manage, AD was adept at managing enterprise PCs (servers and printers too) and ended up winning again. The fact that Microsoft won both these battles with AD in a sense gave it the confidence to assume that everyone would write special code in their enterprise SaaS apps to integrate with AD. But that code was complex, Windows-centric, and kind of annoying to deal with because of how it was architected. Okta on the other hand subsumed that complexity and made it easy to do the one thing customers to do which was maintain one identity across all their enterprise products and keep it in sync with what they believed was the ground truth, AD. Ultimately Okta did this so well that it became the ground truth. So in an “everyone but Microsoft” strategy, the real winner was the company that did a massive amount of work to subsume what Microsoft seemed unwilling to do.

There are other examples and I’m sure people will always quibble or debate details. Having lived through the middleware world for so long, I admit to feeling the pattern rather quickly.

One final word about middleware APIs is unfortunately a weird way to end but an important point. Vendors pledging support for middleware might do so at the start with legitimate and sincere intentions. But over time the negatives of either being easily replaced or having their user experience and feature innovations ignored end up making the commitment to middleware look like a pretty poor investment.

Even well-placed intentions end up meeting market realities. Fear of commoditization, customer churn, or inability to innovate are powerful motivators away from middleware.

—Steven

Our indu…

TL;DR for this article: DeepSeek was always going to happen. We just didn’t know who would do it. It was either going to be a startup or someone outside the current center of leadership and innovation in AI, which is mostly clustered around trillion-dollar companies in the US. It turned out to be a group in China, which for many—myself included—is unfortunate.

But again, it absolutely was going to happen. The next question is US technologists recognize DeepSeek for what it is?

There’s something we used to banter about when things seemed really bleak at Microsoft: When normal companies scope out features and architecture they use t-shirt—sizes small, medium, and large. At its peak, Microsoft seems capable of only thinking in terms of extra-large, huge, and ginormous. That’s where we are with AI today and the big company approach in the US.

There's more in The Short Case for Nvidia Stock which is very good but focuses on picking stocks, which isn't my thing. Strategy and execution are more me so here's that perspective.

The current trajectory of AI if you read the news in the US is one of MASSIVE capital expenditures (CapEx) piled on top of even more MASSIVE CapEx. It’s a race between Google, Meta, OpenAI/Microsoft, xAI, and to a lesser extent a few other super well-funded startups like Perplexity and Anthropic. All of these together are taking the same approach which I will call “scale up”. Scale up is what you do when you have access to vast resources as all of these companies do.

The history of computing is one of innovation followed by scale up which is then broken by a model that “scales out”—when a bigger and faster approach is replaced by a smaller and more numerous approaches.

Mainframe→Mini→Micro→Mobile

Big iron→Distributed computing→Internet

Cray→HPC→Intel/CISC→ARM/RISC

OS/360→VMS→Unix→Windows NT→Linux, and on and on.

You can see this pattern play out at these macro level throughout the history of technology—or you can see it at the micro level with subsystems from networking to storage to memory.

The past five years of AI brought us bigger models, more data, more compute, and so on. Why? Because I would argue the innovation was driven by the cloud hyperscalers, whose approach was destined to do more of what they had already done. They viewed data for training and huge models as their way of winning and their unique architectural approach. The fact that other startups took a similar approach is just Silicon Valley at work—people move and optimize for different things at a micro scale without considering the larger picture. (See the sociological and epidemiological term small area variation.) People try to do what they couldn’t do in their previous efforts, or what their previous efforts might have overlooked.

The degree to which the hyperscalers believed in “scale up” is obvious when consider the fact that they are all building their own Silicon or custom AI chips. As cool as this sounds, it has historically proven very very difficult for software companies to build their own silicon. While many look at Apple as a success, Apple’s lessons emerged over decades of not succeeding PLUS they build devices not just silicon. Apple learned from 68k, PPC, and Intel—the previous architectures Apple used before transitioning to its own custom ARM chips—how to optimize a design for their use-cases. Those building AI hardware were solving their in-house scale up challenges—and I would have always argued they could gain percentages at a constant factor, but not anything beyond that.

Nvidia is there to help everyone not building their own silicon and those who want to build their own silicon but are also trying to meet their immediate needs. As described in “The Short Case” Nvidia also has a huge software ecosystem advantage with their CUDA platform, something they have honed for almost two decades. It is critically important to have an ecosystem, and they have been successful at building one. This is why I wrote and thought the Nvidia DIGITS project is far more interesting than simply a 4000 TOPS (tera operations per second) desktop (see my CES report).

So now where are we? Well, the big problem we have is that the large-scale solutions, regardless of all the progress, are consuming too much capital. But beyond that the delivery to customers has been on an unsustainable path. It’s a path that works against the history of computing, which shows us that resources need to become less—not more—expensive. The market for computing simply doesn’t accept solutions that cost more, especially consumption-based pricing. We’ve seen Microsoft and Google do a bit of resetting with respect to pricing in a move to turn their massive CapEx efforts into direct revenue. I wrote at the time of the initial pricing announcements that there was no way that would be sustainable. It took about a year. Laudable goal for sure but just not how business customers of computing work. At the same time, Apple is focused on the “mostly free” way of doing AI, but the results are at best mixed, and they’re still deploying a ton of CapEx.

Given that it was inevitable someone was going to look at what was going on and build a “scale out” solution—one that does not require massive CapEx and architectural approaches that use even less CapEx to build and train the product.

The example that keeps running through my mind is how AT&T looked at the internet. In all the meetings Microsoft had with AT&T decades ago about building the “information superhighway,” they were completely convinced of two things. First, the internet technologies being shown were toys—they were missing all the key features such as being connection based or having QoS (quality of service). For more on toys, see “[...] Is a Toy” by me.

Second, they were convinced that the right way to build the internet was to take their phone network and scale it up. Add more hardware and more protocols and a lot more wires and equipment to deliver on reliability, QoS, and so on. They weren’t alone. Europe was busy building out internet connectivity with ISDN over their telecommunications networks. AT&T loved this because it took huge capital and relied on their existing infrastructure.

They were completely wrong. Cisco came along and delivered all those things on an IP-based network using toy software like DNS. Other toys like HTTP and HTML layered on top. Then came Apache, Linux, and a lot of browsers. Not only did the initial infrastructure prove to be the least interesting part, but it was also drawn into a “scale out” approach by a completely different player, one who had previously focused on weird university computing infrastructure. Cisco did not have tens of billions of dollars nor did Netscape nor did CERN. They used what they could to deliver the information superhighway. The rest is history.

As an example, there was a time when IBM measured the mainframe business by MIPS (millions of instructions per second). The reality was they had 90 percent plus share of MIPS. But in practice they were selling or leasing MIPS (not the chip company from Stanford) at ever decreasing prices, just like Intel sold transistors for less over time. This is all great until you can get MIPS for even less money elsewhere. which Intel soon delivered. Then ARM found an even cheaper way to deliver more. You get the picture. Repeat this for data storage and you have a great chapter from Clay Christensen’s Innovator’s Dilemma.

Another challenge for the current AI hyperscalers is that they have only two models for bringing an exciting—even disruptive—technology to market.

First, they can bundle the technology as part of what they already sell. This de-monetizes anyone trying to compete with you. Of course, regulators love to think of this as predatory pricing, but the problem is software has little marginal cost (uh oh) and the whole industry is made up of cycles of platforms absorbing more technology from others. It is both an uphill battle for big companies to try to sell separate things (the salespeople are busy selling the big thing) and an uphill battle to try to keep things separate since someone is always going to eventually integrate them anyway. Windows did this with Internet Explorer. Word did this with Excel or Excel did this with Word depending on your point of view (See Hardcore Software for the details). The list is literally endless. It happens so often in the Apple ecosystem that it has a name and is called Sherlocking. The result effectively commoditizes a technology while maintaining a hold on distribution.

Second, AI hyperscalers can compete by skipping the de-monetization step and going straight to commoditization. This approach is one that counts on the internet and gets distribution via the internet. Nearly everything running in the cloud today is built on this approach. It really starts with Linux but goes through everything from Apache to Git to Spark. The key with this approach, and what is so unique about it, is open source.

Meta has done a fantastic job at being open source but it’s still relying on an architectural model that consumes tens of billions of dollars in CapEx. Meta, much like Google, could also justify CapEx by building tools that their existing products better; open-source Llama is just a side effect that is good for everyone. That is not unlike Google releasing all sorts of software, from Chromium to Android. It’s also what Google has did to de-monetize Microsoft when they began Gmail, ChromeOS, and it’s suite of productivity tools (Google Docs was originally just free, presumably to de-monetize Office). Google can do this because they monetize software with services on top of what they do with the open source they release. Their magic lies in the fact that their value-add on top of open source is not open source per se, rather it’s their hyperscale data centers running their proprietary code using their proprietary data. By releasing all their products as open source they are essentially trying to commoditize AI. The challenge, however, is the cost. This is what happened with Hotmail, for example—turns out that massive scale, even a 5MB free mailbox adds up to a lot of subsidies.

That’s why we see all the early AI hyperscaler products take one of two approaches: bundling or mostly open source. Those outside the two models are in a sense competing against bundles and against the companies trying to de-monetize the bundles. Those outside are caught in the middle.

The cost of AI, like the cost of mainframe computing to X.25 connectivity (the early pre-TCP/IP protocol for connecting computers over phone lines), literally forces the market to develop an alternative that scales without the massive direct capital.

By all accounts the latest approach with DeepSeek seems to be that. The internet is filled analysts trying to figure out just how much cheaper, how much less data, or how many fewer people were involved. In algorithmic complexity terms, these are all constant factor differences. The fact that DeepSeek runs on commodity, disconnected hardware and is open source is enough of a shot across the bow of the approach to AI hyperscaling that it can be seen as “the way things will go”.

I admit this is all confirmation bias for me. We’ve had a week with DeepSeek, and people are still poring over it. The hyperscalers and Nvidia have massive technology roadmaps. I’m not here for stock predictions at all. All I know for sure is that if history offers any advice to technologists, it’s that core technologies become free / commodities and because of internet distribution and de facto market standardization at many layers that happens sooner with every turn of the crank.

China faced an AI situation not unlike Cisco. Many (including “The Short Case”) are looking at the Nvidia embargo as a driver. The details don’t really matter. They just had different constraints. They had many more engineers to attack the problem than they had data centers to train. They were inevitably going to create a different kind of solution. In fact, I am certain someone somewhere would have. It’s just that, especially in hindsight, China was especially well-positioned.

Kai-Fu Lee recently argued DeepSeek proved that China was destined to out-engineer the US. Nonsense I say. That’s just trash talk. China took an obvious and clever approach that US companies were mostly blind to because of the path that got them to where they are today before AI. DeepSeek is just a wakeup call.

I’m confident many in the US will identify the necessary course corrections. The next Cisco for AI is waiting to be created, I’m sure. If that doesn’t happen then it could also be like browsers ended up which is a big company (or three) will just bundle it for everyone to use. Either way, the commoditization step is upon us.

Get building. Scale out, not up. 🚀

—Steven Sinofsky

Let’s get two things out of the way.

First, CES continues to be HUGE. I mean literally the s…

Mike joined Microsoft in 1988. He was an unexpected hire to many, as he came from IBM. He was hired at the most senior level in the company, back when the company had few executives and had not done particularly well at outside hires. Microsoft had a strong business partnership but challenging joint development program with IBM during which the combination was building the OS/2 operating system. As a joint project it was culturally difficult to say the least. He was hired to run the Applications Division, Apps, which at the time was primarily seeing success on Macintosh representing almost half of Microsoft revenue and profit. Microsoft’s first-party applications were distant number 3 or worse. At the time, Windows was mostly an idea, that took forever to ship. Still, the Apps strategy was confused between DOS, Windows, OS/2, and Macintosh. The team was not particularly organized for success as a combination of product units and job functions.

Through a series of organizational changes as well as some key acquisitions like Forethought/PowerPoint, Mike led the transformation of Apps into an execution machine. What was incredible about how Mike led was that these results were achieved by incredibly difficult work—pioneering work—by many people doing amazing things with little chaos or randomness as we used to say. All along, Mike created a culture of respect, collaboration, and most of all “promise and deliver”. He instilled in everyone the most basic notion of saying what you’re going to do and doing that well. It was during these early and formative days of the Apps business that Mike coached the team to learn and improve from mistakes, such as the famous “Zero Defects” memo on quality. With a history of all of Microsoft’s products spinning out of control and shipping years later than promised, internally and externally, Excel 3.0 shipped a mere 11 days later than its originally planned date, an unheard-of accomplishment. It wasn’t simply Mike’s direct efforts. There were amazing people assembled on the product team and leading the Excel product unit, Mike’s creation. It was Mike's cultural leadership, his touchstone. Mike challenged the team and coached them. The team delivered. And Apps as more than an org, but a culture, was born. Mike was Apps.

If you visited the Microsoft campus you would have noticed in the Apps courtyard special bronzed tiles with the names of products and the dates they shipped. This was part of a culture Mike created, the Ship It awards. Everyone received a weighty acrylic block commemorating the accomplishment of shipping in an era when that was nearly impossible. After each product shipped, a tile was added to the courtyard and we each got a mini tile to affix to our personal Ship It Award. Mike instilled the idea of shipping across the company.

Some very smart people in marketing had an idea for delivering both individually successful apps of Word and Excel to customers that seemed to be buying only one of the Apps. An earlier idea for DOS Apps did not do well in market but the seed was planted. The early results from Macintosh Office were so successful it was clear there would be a pivot to a suite of products and not just one. Mike wrote a key memo outlining both the customer strategy and the competitive advantage that came from a focus on the newly birthed Office product. It became something of a stump speech he delivered. In the technically and technology-driven Microsoft culture, Mike was among the first to bring customer and market strategy to the forefront.

At the same time, Windows 3.0 was close to completion and was looking like it would be an excellent product. Windows Office 1.0 shipped just months after Windows 3.0. What Mike did was lead us to strategic clarity. I was just a developer in what would become C++ trying to figure out who we were building tools for—Windows, Mac, OS/2, DOS, NT—we just had no idea. I vividly remember the day Mike brought us all clarity. Windows was our focus, though Macintosh remained “sim ship” for quite some time. While Bill Gates had written clearly that “Windows was a platform for the 90s” he also thought doing cross-platform wasn’t difficult :-) Mike was an incredibly important force in balancing all we needed to do at the time. Again, promise and deliver.

On my C++ team, which reported to Mike, we were so struggling with focusing on Windows that we had to do a “review” meeting with him. Now Microsoft review meetings at the time were of two totally different types. There were the Systems meetings (Windows, DOS, OS/2, and then NT) which were like the BillG reviews that had become infamous. Apps meetings were much more structured and much less "in the weeds”. We prepared a deck that probably had 50 slides in it, which we could never cover but would have been typical at the time. We went through a bunch of slides. We were running out of time and jumped to the end with a slide that raised the question “Should we do a Windows hosted toolset for building Windows or stick to command line”. We were torn and debating but we knew Windows was the strategy but so was everything else we thought.

Mike looked at us, rings of people encircling the big table. He asked, “How long have y'all been thinking about this problem?” Of course it had been months, day and night, but mostly we just froze. He then said in his best Oklahoma accent “There’s a lot here…much more than I can absorb in an hour. How long have y’all been working on these foils and this problem?” More silence.

Mike then followed up, “Y’all been working on this longer than me, and know more than I will ever know. Why don’t you just tell me what you decided to do and then we can move the project forward?” That wasn't how Microsoft worked, the more senior a person was the more certain they were and did not hesitate to tell you that. He was teaching us how that doesn't really scale.

We continued to debate in front of Mike, the two sides of the C++ team. The big issue was a Windows product might take longer and appeal to fewer customers which meant losing competitively perhaps. Mike looked at us and told us to tell him when we could ship and why that would be a competitive win, and then just ship that when we said. That’s what we did. Probably the most important meeting of my career.

With Office doing well, Mike took the next step which was to build an organization that represented the product that needed to be built and that customers were buying. Mike had created the organization that got us to this point. In what you don’t see all that often, he then put the right people in place to create a new kind of organization, one structured to build and deliver Office. He did so by undoing some of the things he did. He did so with such grace and clarity that it became a model that I and others would follow through many more generations of Office and then a few generations of Windows.

That change was in a sense a passing of the torch to those that Mike had mentored and managed through his original Apps organization to this new organization (this is also when I joined Office). Mike became one of the three most senior executives in the company with Bill and Steve, leading the entirety of Microsoft product development. In this immense role he was the executive leading Windows and Office and everything from tools to games to enterprise servers. Everyone came to benefit from Mike’s leadership and cultural transformation.

Mike retired to his beloved ranch in the summer of 1995. Of course he didn’t quite retire. He served as an advisor, investor, board director, educator, and more to companies of all kinds. I had an incredible opportunity to teach a class at Stanford with him in 2016 when he made a trip out. I was overcome with emotion when the first slide went up — my name next to Mike’s on a slide.

I wanted to remember Mike’s professional life but his life outside of work was everything to him and a source of support and inspiration. Mike’s wife Carolyn was ever-present at Microsoft events always remembering each of us and survives him in Texas. Mike’s son, Mike Jr. is himself a legendary investor and founder of Floodgate in Palo Alto, and he is also an author of the recently published Pattern Breakers: Why Some Start-Ups Change the Future.

I owe everything in my professional life to Mike, most literally everything.

Many have so much to be thankful for the contributions Mike made to the computer industry.

May Mike’s memory be a blessing.

Tren Griffin, long-time Microsoft employee, wrote an essay “A Dozen Things I’ve Learned From Mike Maples Sr. About Business and Investing” which also references a wonderfully detailed interview with Bob Gaskins, founder of Forethought/PowerPoint, should you wish to read more about the impact Mike had during his time at Microsoft and after.

The WSJ published an obituary on February 5 (online and in print on February 8). It included this wonderful photo of Steve Ballmer, Mike Maples, Frank Gaudette, and Bill Gates as well as this candid from Esther Dyson’s PC Forum in 1989 (Jon Lazarus and Pam Edstrom on the left and right).

@Martin_Casado tweeted some wisdom (as he often does) in this:

Here's a Books I Read in 2024 list. Some of them I enjoyed. Some of them drove me bonkers. I like that part of reading. Hope you enjoy this list.

This year I included some "thoughts" which in no way a full review but offer more than just the title and jacket (new this year…emojis). I enjoyed some long books this year that took two weeks :-) I have always liked to give books I've read to friends and to teams I've worked with. Each below is available print, kindle, and audio. Links are FYI and non revenue generating.

I'm not trying to make a statement with this list or thoughts. Just sharing how I felt after the read. Ordered in the order I read them. This post also on X.

1. 💯 The Power Elite b C. Wright Mills https://a.co/d/gjHfCWZ // I read this classic 1956 book in a college course (Power and Elites in Society) that I found to be particularly influential to me and felt it was a good time to re-read. It should really make you think even more today. From the jacket: “The Power Elite stands as a contemporary classic of social science and social criticism. C. Wright Mills examines and critiques the organization of power in the United States, calling attention to three firmly interlocked prongs of power: the military, corporate, and political elite. The Power Elite can be read as a good account of what was taking place in America at the time [1950s] it was written, but its underlying question of whether America is as democratic in practice as it is in theory continues to matter very much today.” // I feel like everyone should read this and think about it. It is very easy to use this work to argue one side or another when the real question is “what if anything to do about it” and alternatively did we have any structural changes that changed this trajectory or did we substitute one set of structures for another equally problematic along the lines of “we become what we vanquish”. I think a lot about the formation of the intelligence community (OSS-CIA) and compare the early days to today, as seen in “The Good Shepherd”. If you liked Burnhams “Managerial State” or "Company Man" by Sampson then this is a natural follow on but also a different perspective. Note, this is a decidedly old school essay. It isn’t bullet points or footnoted. It’s a thought-piece though the conclusions and "jabs" along the way are decidedly one-sided if not particularly well-supported beyond anecdotes.

2. 😻Big Intel: How the CIA Went from Cold War Heroes to Deep State Villains by J. Michael Waller https://a.co/d/d14cMmJ // This is a book that starts from the recent events in massive failures of the national security “apparatus” and both looks backward for root cause and forwards for how to fix it. Now that we know everything from WDM to proximal origin of COVID to Steele dossier to 51 NatSec leaders say ‘Russian hoax’ were all massive intelligence failures the question is how, why, and what to do about that. This would all read as paranoid conspiracy theory had we not just lived through the gaslighting of the recent failures. Some stuff does get pretty far out there or just personal to the author.

3. 💯😻 Firepower: How Weapons Shaped Warfare by Paul Lockhart https://a.co/d/6IJrGjM // This is a fantastic book about guns/munitions used in war. It is not a technical book that has specs on every weapon from every country (that kind of big coffee table book I loved years ago). It is a book that puts arms in the context of war in a historic sense. So so relevant to today. But really this is a book about innovation, inventors/founders, as well as disruption. It is my favorite book this year about “making things”. The book traces the role of weapons and firepower from the end of the Middle Ages to the end of World War II. The role innovators, needs of soldiers, local conditions, and costs all factored into what worked. It is an incredible book. With all the changes we’re seeing in war today (Israel and Ukraine and drones for example) and what is almost certainly going to be a totally different next big war if there is one, there’s a lot to think about. Founders should read this book for the long arc no matter your view of war or guns.

4. 👎Nexus: A Brief History of Information Networks from the Stone Age to AI b Yuval Noah Harari https://a.co/d/cqDMkLK // up front I have to say this was the rare book I gave up on half way through. from the author of “Sapiens” comes this book that takes on the very broad topic of “what is information”. Let me say about any book that says the Internet and information is a "threat to democracy"—I have a very hard time taking the book seriously, especially after this book's historical account of printing presses of the printing press. Also includes the tired assertions about “algorithms” and extends it to “agents”. For many this will flip the bozo bit in the whole book and thesis. Following that the book took on an AI doomerism tone with all the standard and poorly understood (by author) tropes. That said let me talk about the book a little bit. It takes us through the history of information such as stories and books and builds up all the way to a very modern view of AI and information. It has a good number of essays that could be good stand alone especially the first chapters like the section on bureaucracy and documents. I enjoyed this part but make sure to allocate time to take in the breadth as it isn’t for the faint hearted. Also important to not read this through a political lens and recognize the views expressed are an historian with an obvious present day bias selecting which sources to weigh more than others—the selection makes the author’s personal views fairly clear. For example, the author sites a mid 1400s document from the Pope, giving permission to destroy, takeover, and convert other (Pagan) religions in the name of the Church. But this is hundreds of years after the Muslim expansion had started and thus many recognize that such authorization came as a result of defending the Church and recapturing what was lost by a pacifist Church, not really expanding it. I appreciated the history of the overlap of printing and witchcraft. The basic idea is that the free exchange of information also could lead to the free exchange of that erroneous or conspiratorial information, such as witches. But that leads to the need for society to have information curators. Which of course sounds good on paper. But then you overlay the Church and you realize that the curators themselves are susceptible to human fallibility. This is why the free exchange of information was necessary, but not sufficient for the expansion of science. Because the church quashed everything that was counter to the teachings of the church, even though it was a new form of scientific information. There’s a lot more as it gets into AI but I did feel it became more of an (not well-informed) opinion essay and less of a substantial work and disagreed with the extrapolations or implications presented. The goal seems to be about democracy but the conclusions felt rather extreme in putting power in the hands of those with self-perceived enlightened views.

5. 😻😻😻 Civilian Warriors: The Inside Story of Blackwater and the Unsung Heroes of the War on Terror by Erik Prince (2014) https://a.co/d/horKsBs // Reading about the Crusades made me want to learn more about how the US fought in the Middle East. There was so much controversy over “mercenaries” and the role they played in “profiteering” (many congressional hearings and Sunday talk shows) but I also knew paid support of the military had a long history in the US not to mention all global conflicts. What I didn’t realize was just how big the US government (not just military) came to depend on contracts for support. This is also the story of an entrepreneur, a soldier, and a person on their own life journey. It is a fascinating story. It is super important to go into reading this aware or willing to acknowledge that there’s no world order without private military contractors and calling them mercenaries or thinking they are somehow “extra-jurisdictional” doing things that are sketchy then you will miss what is an important founder story and significant issue for executing our global foreign policy. Recommended for founders too since that is ultimately the story.

6. 👎A Colony in a Nation by Chris Hayes https://a.co/d/5hCoRgh // This book is a pretty standard view of the current racial situation in the US—the view that there are really two societies in the US (the title comes from a President Nixon speech during the upheavals of the late 1960s). I don’t think there is any new territory the book covers and the focus is on the notion of institutional white racism or “white fear” though it tries to build on the more recent events such as the Ferguson MO protests and BLM movement. The book as is usually the case tends to overplay anecdotes and say the statistics are just symptoms of deeper problems. While the book tended to anchor on the BLM movement it was only in a mere footnote did it mention hands up don’t shoot” was fake news and in fact Michael Brown was moving towards soldiers in a “threatening manner” and repeats the trope that “small number of young men looting and rioting” to excuse the wave of violence across the country that many of us lived through (Seattle CHAZ). There are plenty of anecdotes from the authors life growing up in the Bronx and attending Brown University. ultimately this book feels like a sum of defund the police, empty prisons, remove sentencing guidelines, etc and move accountability for crimes from criminals to white “fear”. I was hoping to gain some new perspective. In a world where our cities have been rendered unrecognizable it is tough to think the same approaches make sense. Of course the claim is that the true best approach (treating crime like a social problem and not a violence problem) have not been fully implemented. This debate structure quickly descends into the college debate about Marxism not having been fully implemented in Russia/USSR.

7. 😻😻 😻😻Sword and Scimitar: Fourteen Centuries of War between Islam and the West by Raymond Ibrahim https://a.co/d/2mGfL0x // With all going on in the Middle East it is easy to lose sight of the history of the region. In particular most in the modern debate (like on X) often talked as though history started in 1948. It is worth reading different perspectives on the history of the battles across antiquity, from the pre Christian era through the Roman Empire and the rise of Islam etc. the violence of the rise, expansion, and then retaking of Europe between Christendom and Islam say a great deal about what is going on in the world today and importantly provide context about why what is happening, at least for many many, is hardly localized to Israel and doesn’t end there. Those that think what is going on is a fringe part of one religion or another would be served to read a perspective that takes a strong point of view and this book is that. There’s a very deep and to some deeply concerning question about the ability to find peace between Christendom and Islam. This book is incredibly well sourced and noted. It cites specific original writings which are often the subject of debates over “context” in modern dialogs.

8. 😻😻 😻Defenders of the West: The Christian Heroes Who Stood Against Islam by Raymond Ibrahim https://a.co/d/5BZcQBz // This book should be required reading for those not well-versed in the “why” of the crusades and the way the west pushed back on the colonialist expansion of the islamic world, not to mention the brutality all around. Well known scholar and an Arabic language specialist for the Near East section of the Library of Congress Ibrahim tells the story of 8 defenders of Christendom against the challenges of brutal Islamic imperialism. A sequel in some sense to his previous book on the history of the Christendom - Islamic cultures. Especially today, one might think the 1400 year history of Islamic culture is a peaceful religion on the defense against Western Europe. In fact the expansive and violent nature of the history is well worth understanding. His writing is viewed by some as propaganda but it is history told by an Arabic scholar and translator. One might argue that the dislike of his scholarship is due to the incredible control the Islamic culture exerts over any scholarship that might be seen by them as critical of their history or worse the Prophet himself.

9. 😻😻 😻 😻 The Strange Death of Europe: Immigration, Identity, Islam by Douglas Murray (2018) https://a.co/d/8nQvHw8 // This is an important topic and excellent book but a difficult one to discuss, at both a personal level and general level. What is culture? What is multi-cultural? What does it mean to be an immigrant? Is there a healthy level of immigration? What is guilt over the past? What is asylum or refugee status? When and why did collective wisdom stop being about assimilation. The topic is about the way UK/Europe has lost its identity due to immigration and the erosion of what made Europe, Europe. It is a super interesting topic. Personally, since all my relatives “immigrated” (eg escaped) from Europe and generations before them “immigrated” (eg escaped) to Europe it is close to home. The book starts with an early 2000s prediction that the majority of citizens in London will be neither white nor Christian by the end of the lives of everyone alive at the time. It was both absurd and “-ist” to make statements like that. Yet just two decades later, 44% of London identifies as white Christian and 1/3rd of households have no English speakers. That’s how the book starts. The US in major cities is of course is much the same. All of these “fears” were discussed in the early 20th century when my grandparents and great grandparents arrived. The biggest difference was one of assimilation. That’s why this is so personal as a product of assimilation versus cultural continuity for those that arrived. Chapter 10 on “European guilt” is required reading for those who have thoughts on reparations, genocide, or apologizing for the past. This is happening. I recommend reading about it.

10. 😻😻The Parasitic Mind: How Infectious Ideas Are Killing Common Sense by Gad Saad https://a.co/d/6Wcgx1w // The author is a Lebanese-born, Arab-first-speaking jew who as a child fled his country under gunfire to grow up in Canada. Almost no one reading this list will read this book. It is one of those books that the built-in audience gets a ton of confirmation and those not reading it just assume it is not worth the effort and probably only know the author as what would be called a twitter troll for some battles with well-known people. The book is better thought of as an essay and strongly formed and supported opinion piece. This is not about “proof” even though the writer is a credentialed social scientist. He’s been on Joe Rogan and quotes Jordon Peterson which is enough to “classify” him for many. Yet that is why it is worth approaching something like this with an open mind. The arguments are sound in many ways but proof is elusive since we’re talking about human behavior—with the exception of the section on Islamophobia and antisemitism which are excellent and provide ample footnotes to rathole. That said, this book offers chapters on likely what originated with this author—the woke mind virus. As a product of 1980s political correctness, I just wish the debate this book took on could receive more rational discourse as the problems described are real. As I read this the discourse around DEI had reached a new conclusion as major universities began to share admission demographics for the incoming 2024 students and classes.

11. 😻😻😻The Future Was Now: Madmen, Mavericks, and the Epic Sci-Fi Summer of 1982 by Chris Nashawaty https://a.co/d/76JXGmC // wow this book is amazing. It is the “behind the scenes” story of the birth of and creation of modern/epic sci-fi in the summer of 1982. That summer saw 8 landmark films including Tron, Blade Runner, E.T., ST:WoK and more. Really a super fun read. Also that was an amazing summer. Loved this book from when movies were such a part of the summer.

12. 😻On the Edge The Art of Risking Everything b Nate Silver https://a.co/d/1Tbm2ux // this book was a tricky read for me. I love the underlying topic but the use of poker and sports at fairly extreme detail left me behind. The book is about the culture of risk. I just think it would have been more enjoyable had I a shared connection with those topics Silver is so passionate and articulate about.

13. 😻😻😻Peace to End All Peace by David Fromkin (1989) https://a.co/d/ab23luJ // I felt the need to dig into a well-regarded book on the pre-1948 history of the Middle East. This is _the_ book AFAICT. It is about the dissolution of the Ottoman Empire at the close of World War I and the consequences for the Western powers, the then Soviet Union and, to a lesser extent, the peoples of the Middle East themselves. At the macro level the book shows the political origins of the present-day Middle East. The book ends with the territorial settlements of 1922, when political lines were drawn that mostly reflect today’s boundaries. The amount of contemporaneous European politics, -isms, and misunderstandings was as surprising to me in reading this book as they are when reading twitter posts today.

14. 😻😻Dead Aid b Dambisa Moyo (2009) https://www.amazon.com/dp/0374139563 // Have billions in aid sent from wealthy countries to developing African nations has helped to reduce poverty and increase growth? Poverty levels continue to escalate and growth rates have steadily declined—and millions continue to suffer. This book is really a must read for anyone who believes that big philanthropy and global development work are even a net positive. It is irrefutable that the trillion dollars of post-war aid have done more harm than good. This book explains some of the reasons why. I’m re-reading this just as the President wrote off 10’s of billions of student loans and the recent large scale UBI tests failed. Why does simply giving money to a country or an individual fail to work the way it feels like it should? This book makes a strong case and one that is just as true after another 15 years of aid than it has been for the first 60 years. There are other books critical of aid, with the classic being “White Man’s Burden” by Easterly that are probably more “scholarly” though this book is a good read, overview, and kicks off potential solution ideas. The thrust at the end brings us back to what made me reread this—conditional cash transfers—an offshoot of UBI. The recent study shows, at least in the developed world, the lack of efficacy of this solution. The wildest aspect of this book is that if you work in this field at the international level, everything that it said is true, so why do people keep trying the same things over and over again? This is a space that could use some innovation or more likely some invention and rethinking from first principles. What most people are really concerned to mention is the success that China has had. Rather than try to create a government or manipulate society into behaving a certain certain way, China simply turns this entire process into a transactional one. You have money in exchange for roads or resources or other commercial relationships. And if you are corrupt or anything like that, it doesn’t change the fact that you need to deliver. The west view of altruism has always assumed nothing in return in the short term, but in the medium term, some convergence on ideas, government, morality.

15. 😻😻😻Raven Rock: The Story of the U.S. Government's Secret Plan to Save Itself--While the Rest of Us Die by Garrett Graff https://a.co/d/2CzRcbH // this is a fantastic book tracing the history of the procedures developed to ensure that the government of the US can continue even in the face of nuclear attack on our soil. A vast amount of money and thought have gone into the scenarios, plans, and materiel. As a 70s bomb shelter drills in elementary school and an 80s “survivalist” I have always been fascinated by this topic. Yet the reality is a modern nuclear or chemical war will with near certainty be an extinction event, at least for North America and whoever starts it. Given the fragility we all saw with Covid and our general inability to make it through a flight with poor WiFi it isn’t clear to me, and this book and Nuclear War only emphasize such a conclusion, that any preparation makes sense. As we learned from a War Games, the only way to win is to not play. Scary to think this current leadership thinks they are prepared when for 80 years and 100’s of billions of dollars we were not. The pandemic response shows that the system is not about the population but the government (FEMA is really about the government), which came as a surprise to most (remember the gov sitting on stockpiles of masks, O2, and respirators but not releasing them—that’s why.)

16. 😻 😻 😻 Nuclear War: A Scenario by Annie Jacobsen https://a.co/d/55vsybE // Do these terms mean anything to you: MAD, fallout maps, LOW, SLBM, doomsday bombers, nuclear winter, SIGINT, Puzzle Palace, SIOP, Ivy Mike, NRO, Cheyenne Mt, MIRV, Triad, Raven Rock? If so then like me you grew up at the height of the threat of nuclear war. If not then you grew up in the “it will never happen” era of 1990 to about 2020. Read this for a reminder of what we grew up with or read it to see the reality of War Games and what the world would go through. With N Korea, Iran, Russia all putting the world at a level of risk not seen it’s worth considering that defense isn’t an option. This new book is filled with first hand accounts from the people who built out our nuclear defense and strategy. It is written as a tick-tock scenario not unlike the myriad of “docu-dramas” we saw throughout growing up like Nuclear Winter by Sagan and others. It really is a must read. Riveting and scary AF. PTSD for boomers and GenX. Incredibly well done and necessary.

17. 😻 😻 Suicide of the West: An Essay on the Meaning and Destiny of Liberalism b James Burnham https://a.co/d/0eVe2Vhs // From 1964 (!) this book does a great job of framing the world we live in today—a world where we find the progressives/liberals largely siding with entirely anti-liberal/anti-progressive positions/concepts/nations. It is essentially a treatise on the evolution of the concept of liberalism. The book is written in classic Burnham style which means many lists of bullet points/assertions that are expanded upon (one list was 19 items long, another list of “modern liberals in the media” seemed to go on forever.) It often feels like a full assault on the reader but that is also a bit refreshing compared to just broad thematic work. Everything from “Karens” to reverse discrimination to white guilt to asymmetric outrage make a prescient showing. The section on foreign policy—written in the 1960s—could be describing “support decolonization even if it means supporting the enemy sworn to your demise” we see today. If you’re expecting footnotes or proof this is not for you, the title says it all—this is an opinion essay.

18. 😻 😻 Several Short Sentences About Writing by Verlyn Klinkenborg https://a.co/d/0j2i6HPT // Without going too far, this book is in the spirit of Strunk & White that had such an impression on every Cornell freshman like me. The author brings the idea of a relentless focus on short sentences and clarity. He does so without claiming to offer a recipe or “system” which I really appreciated. Everyone, especially me, would benefit from a deep engagement with the ideas and approaches in this book. One read of this is why generative AI writing is verbose and pretty wordy. It is build off a lot of patterns that followed by people writing “one word after another” versus “one sentence at a time”. Super interesting to think about. Worth reading just for this. Really difficult to do.

19. 😻 😻 The Hacker Mindset: A 5-Step Methodology for Cracking the System and Achieving Your Dreams b Garrett Gee https://a.co/d/09YSpiQ6 // trapped, frustrated, bored then being a hacker is for you—the book uses a mindset of hacking and merges it with the techniques and language of general self-help. Not at all what I was expecting. “Slackers versus hackers” is about people who are trapped in a system (life, job, etc) versus those breaking or disrupting that system. He does point out he is taking an amoral stance and that bad people can do bad things just like good people can do good things. When I’ve talked about this in the past I used a sports analogy—are you a person that embraced intentional fouls, sacrifice flies, or grounding? Those are the rules hacks of sports. The biggest innovators saw the rules and used them to an advantage even in the face of claims (or risk of penalty) of sportsmanlike conduct. The 6 principles of a hacking life include: 1. Be on Offense 2. Reverse Engineering 3. Living Off the Land 4. Risk 5. Social Engineering 6. Pivot. This is a really important mindset. The title is not what you might think. The book tapered off at the end when it got into starting your own business and was a bit vague and difficult to act on along with basic money management tips that felt a bit out of place. But the framework is great.

20. 😐 The Utopia of Rules: On Technology, Stupidity, and the Secret Joys of Bureaucracy by David Graeber https://a.co/d/5b8z1tV // This was a complex book by someone I know I would not agree with on just about anything. Early in the book, which is more a collection of essays, he introduces the “iron law of liberalism” where any market reform, any government initiative intended to reduce red tape and promote market forces will have the ultimate effect of increasing the total number of regulations, the total amount of paperwork and the total number of bureaucrats the government employs. Given our collective experience it is difficult to disagree with. It is the more hyper-progressive Occupy Wall Street view of solutions I don’t agree with, even if I found myself nodding in agreement with the awfulness of every anecdote.

21. 😻😻😻😻Stories I Only Tell My Friends: An Autobiography by Rob Lowe https://a.co/d/jeRI7vM // I loved every story and every word of this memoir. And the audiobook was an incredible treat, like having Billy, Danny, or Sam tell the story. Films like Outsiders, Class, About Last Night, St Elmos, Oxford Blues formed the backbone of trips to the Altamonte Mall or Pyramid Mall in college. When I was an RA every girl in the dorm (literally) had that Billy Hicks poster/crush. Beyond that personal connection to his work the memoir is filled with insights about the evolving film industry. I loved for example the sentence “Dustin Hoffman’s opus ‘Agatha’ from a time when a-listers made movies that didn’t have their character’s name in the title.” The deeply personal stories were all tastefully and emotionally told—not at all a gossip. Oh, and the West Wing. Treat yourself to this audiobook. I wish I had done so sooner.

22. 😻😻😻The End of Race Politics: Arguments for a Colorblind America b Coleman Hughes https://a.co/d/3znEyLc // I am a new Coleman listener having joined his following when I listened to an interview with Israeli author and war cabinet member Benny Morris, an historian with views and books that are criticized from all sides but an enormous depth of knowledge. Coleman works through the very core of the “anti-racist” movement to demonstrate how it is itself racist, what he terms neo-racism. He does an excellent job detailing all the ways the well-intentioned efforts end up disadvantaging the very people they aim to help. The telling is compelling even if you are predisposed to strongly agree or disagree. After reading I looked at some reviews and found out just how much of a hard time he is being given—The NY Times used the headline “The Young Black Conservative Who Grew Up With, and Rejects, D.E.I.” from Feb 2024. One look at that and you can actually see Neo-racism in play, which is awful—how they can call out his skin color in a review about a book on being colorblind is kind of incomprehensible. Read this book.

23. 😻😻😻Morning After the Revolution: Dispatches from the Wrong Side of History b Nellie Bowles https://a.co/d/9skQNrI // This book is amazing. It captures the absurdity of a “movement” that went haywire during the pandemic. It became a NYT best seller opening week which is amazing and deeply ironic (not to mention rewarding for Nellie a former NYT reporter). The description of Seattle’s “Autonomous Zone” is beyond precious. Don’t let the incredibly entertaining writing take away from the important facts and storytelling of a lens on events that is mostly buried by nearly all press outlets of record. The entire section on “anti-racism” and “Karens” was a tour de force of saying the unsayable. It took me back to my OG resident advisor training at the dawn of anti-racism (c. 1984 when it was just called power dynamics) when I got yelled at for an afternoon for being white and an abuser of power by a facilitator in a pink jumpsuit with colored hair, which even then was a weird thing to tell a jew with living Holocaust relatives. The section on gender and sexuality was both sensitive while pointing out what can be seen by all. I listened to audio narrated by Nellie which makes for an even better read and the occasional great French accent. Detractors will see Nellie as a traitor and will scorn at her descriptions of people, what they said, and events. I think she’s saying what a lot of people felt or feel but were legit afraid to say. The book is a personal memoir not a sermon, which also annoys those who used to agree with her.

24. 😻 😻 😻 The Genius of the System: Hollywood Filmmaking in the Studio Era b Thomas Schatz https://a.co/d/eQYAzkg // There are a ton of books about classic Hollywood but this one has a unique perspective that will be super valuable to any builders. It talks about the “system” of Hollywood and what made that system and why it worked and why it failed. It tells the story through the lens of big important people we have heard of like Thalberg, Selznick, Zanuck and Hitchcock. It importantly talks about what it took to get movies made and the ever present balance of art and commerce, of story and spectacle. It demonstrates, intentionally or not, that in most endeavors/orgs only a very small number of people really know what to do at any given time/era. There’s even stories of disruption such as how the big studios slow-rolled talkies since they were vertically integrated theaters with orchestras whereas the lesser studios (Warner!) were not set up for any sound. This book should really make you think about the operations of big companies and creative endeavors. Lots of interesting “org” thinking as studios pioneered the “unit” org versus hierarchical general management. Plus even antitrust makes an appearance. And not to be outdone so does censorship. But wow, the salaries in classic Hollywood were crazy—50-100x the typical salary, but also the reality of taking advantage of the writer/director/actor talent (like Cagney, Davis, and more). I know for me it made me think a ton about the “operating system” we built at Microsoft for building software. If the “Fountainhead” describes the idealized view of a founder (or “The Founders”), the “System” describes the idealized BigCo. Another founder book.

25. 😻Means of Control: How the Hidden Alliance of Tech and Government Is Creating a New American Surveillance State by Byron Tau https://a.co/d/3yiOdeD // When watching a show like “FBI” or the classic “Person of Interest” there are two kinds of people when it comes to privacy and the government. One kind says “dang this is cool and this is how crime should be stopped” and the other says “OMG why in the world should we trust the government to only do good things with all this data and not ruin lives”. It is very tough to see all the benefits of technology, specifically cell phones, GPS, location data and at the same time the risks from global terror or even domestic violence and not think the government should use the tools it has. Yet there need to be limits because it isn’t just abuse but the ability to completely upend the lives of innocent people. I think about on “FBI” when someone just happens to be in the wrong place at the wrong time and sees a crime (or worse taking a cell phone photo of a getaway by accident) and there’s Jubal in the JOC barking out “get that phone, ping it, got it…send OA and Maggie and pick them up” and then an innocent person ends up in the dragnet of the effort. This book is about what the government has done to use not secret eavesdropping but the grey area of “public” data collected for advertising or by apps and data brokers (NOT BIG TECH). It doesn’t do a lot other than freak out you but this is an important topic that is not so simple. The right to privacy is not in the constitution but the framers certainly believed in the right to be left alone. This book breaks my regular guidelines of being a journalist writing about their beat but it is not about one company or frankly even anti-tech. You learn that the worst offenders are the brokers, the parasites riding off (or circumventing) the benefits we all see every day from Google, Apple, Facebook, etc. This is a valuable contribution if looked at through that lens.

26. 😻😻The Second Brain: A Groundbreaking New Understanding of Nervous Disorders of the Stomach and Intestine (1998) by Michael Gershon https://a.co/d/a5h5TH3 // “My interest in serotonin started in 1958 as an undergraduate at Cornell!” From this in the introduction this book only got better. This incredible book is about how real science is done and real discoveries made. I got a great sense for how good this would be early in the book when Gershon said “this was back when the government funded science experiments even when it wasn’t sure the experiment would even work.” (This book is from 1998!) There’s attitude, rivalry, personalities, success, failure, good ideas, wrong ideas, stubbornness, persistence, collaboration, and everything in between. The descriptions of the people he collaborates with and those that are in his lab are so wonderfully warm and amazing. It is a memoir and a book of discovery. Shout out to @davidacrotty and memories of transgenic megacolon mice from the 80s and that time my car got broken into at 168th st. The science in the book is real as is the humility and humanity of discovery. This is a “builder” book for the year. Loved it.

27. 😻Zero Days by Ruth Ware https://a.co/d/bQ4T4ym // this was super fun and fulfilled my one-per-year fiction. One part of it bugged me a lot and was key plot point that was technically off. Would have been fine in a screenplay but not a book (2fa via SMS). As usual/expected did not need the self-reflecting essay/monologue at the end. A good one for the airplane or beach.

28. 😻The Art of More: How Mathematics Created Civilization b Michael Brooks https://a.co/d/fYuA9es // AI is just math. When thinking about regulating AI it is a good idea to have some context about the history of math. There are a lot of books about math history. I enjoyed this one in how it presents some deeper examples but presented in a way that makes them fun. Really enjoyed some of the history I had not come across such as logarithms. Pay attention to the PDF or get print.

29. 😻Four Battlegrounds: Power in the Age of Artificial Intelligence by Paul Scharre https://a.co/d/ezqmf9J // former Ranger and defense analyst at pentagon argues that four key elements define this struggle: data, computing power, talent, and institutions. A major theme is the risk of China and in this regard it talks about the importance of AI in defense, the huge negatives of AI as used in Chinese society, and the many places the US is conflicted in China (there’s a lot devoted to the role Microsoft played with Microsoft Research in elevating China’s AI work.) The defense arguments are strong yet much of the civilian use starts to sound like the fairly standard/mid “AI is risky and we need to get ahead of it”. Where the author was aggressive in the use of AI in the military (personally having been an advocate in the military) he is reluctant or concerned about civilian uses and uses by government outside military. At the same time there is clear recognition that the cat is out of the bag. There’s an entertaining section on Microsoft’s MSR lab in Beijing and how instrumental it was to the *creation* of China’s AI ecosystem, which I’m sure is how people feel but definitely looked better a few years ago (if you read Mandarin you can read about how I was a negative influence wrt China on that earlier era in a book by Kai-Fu Lee). The irony of this view today is also just how much effort Microsoft was putting into elevating MSRA all the while OpenAI is gaining momentum and Microsoft had no product offerings of its own on this “foundational research” yet had no problem giving tours and touting the whole of MSRA. The section on TikTok does the standard “algorithm is the problem” which for me is always a bit of a🚩for what follows. I really enjoyed the section towards the end bringing together topics and detailing the future of war. It had shares of Terminator and ST:ToS “Taste of Armageddon” and “Ultimate Computer.” There not a ton new here but the perspective of a DC/military insider brings value and I very much appreciate how frequently Scharre was on the ground at least hearing firsthand what was going on and telling us when he was.

30. 😻😻The Metaverse: And How It Will Revolutionize Everything b Matthew Ball https://a.co/d/eLb9AWb // Given all that is going on with AVP and Meta I would suggest reading this. If you think the EU is doing wonderful work on DMA, at least read the chapter on Payments to understand history behind 30% and how either EU should be going after gaming companies or EU was short sighted in going after only Apple or that the whole thing is a farce because the market works. This book, for me, is a sharp contrast with Read, Write, Own. Both books acknowledge the power-dynamic with big incumbents where RWO focuses on building and creating a new way to do new things in the market, The Metaverse seems to focus too much on how to extend the existing games market and “divide the pie” versus grow it. It takes as a given the big companies needing to be regulated, even at one point towards the end simply suggesting that it doesn’t seem fair to regulate them after creating the platforms we all use, but that is the price of success.

31. 😻😻😻💯Read Write Own: Building the Next Era of the Internet b Chris Dixon https://a.co/d/3wtIe9o // Chris is a friend. He’s also written some of the best thought-provoking essays of the internet era (come for the tool stay for the network, the internet is for snacking, idea maze, climbing the wrong hill, hobbies/what the smartest people do on weekends). But please if you work using the internet you must read this book. First, grasp the historical description of the culture and origins of the Internet. This background is incredibly important to understand the “problem space” technologies like blockchain are going after. And second, even if you can’t see past the “casino” (as Chris calls it) there’s an enormous amount to consider that chris describes when it comes to improving and reinventing the internet by returning to the roots of the “movement” that started it. An analogy that works for me is that in the 1980s a lot of the commercial world was against “free software”—which many saw as the heart and soul of the internet—for obvious reasons (myself included as part of Microsoft). Then as the movement changed approaches and companies like Google, Meta, etc. joined and became contributors to the “open source” movement it became much more acceptable everywhere. There will always be casinos (as chris points out) but there will also be a strong rationale for what comes out of the openness and culture of the internet. It is really important not to let the casino players mess with learning—if only because one might not have noticed there were land grabs/casinos at every step of computing that went unnoticed by some.

32. 😻😻Intellectuals and Society by Thomas Sowell https://a.co/d/1Rl2Qp6 // With all the stuff going on with university presidents and more importantly the debate over the integrity of basic research (Stanford, Harvard Medical, even all of Covid) I wanted to reread this book from 2010. Who are the “public intellectuals” and why do they have so much influence compared to the people “in the arena” (my words)? Fundamentally this is an intellectual critique of intellectualism. It is a social science book questioning the validity of social science. But it is also compelling in the context of today’s punditry.

33. 😻😻The End of the World Is Just the Beginning: Mapping the Collapse of Globalization b. Peter Zeihan https://a.co/d/cbv8gvg // I think there are real challenges in the global order (as it is called) as we saw with Covid and supply chain. This book is almost doomerism comes to the world order and economy. Reminds me a great deal of 1980s Howard Ruff’s “how to prosper during the coming bad times”. Very much a “story” and not a deep economic reference or footnoted analysis. Audio version is like a 17 hour TED talk. Will some be true? Absolutely yes. Just which parts and when? But makes you think and/or stress. If you want an optimistic view of what happens in the US after “globalism” ends, this is it. Go America!

34. 😻😻How Innovation Works: And Why It Flourishes in Freedom b Matt Ridley https://a.co/d/iWD57Z1 // Really two books. First is a series of well-done vignettes on a good number of innovations and how they really came to be. Chances are readers will know one or more of these stories but they are well told. Book is structured as a well organized essay taking those examples and developing a framework that is highly tilted towards the thesis that free markets, free exchange of ideas, ability to try and fail, and to share matter a huge amount. Every time someone takes this approach they immediately rush to point out the really big inventions came from government (like the computers, internet, medicine). Though those champions always minimize the role that war or nationalism played in those. It might be impossible to generalize about innovation and perhaps that is the real point—it takes a lot of approaches to “innovate” though masterminding or inventing are not the ones that tend to work best. I liked this was an Issacsson-like book but pivoted by innovation more than personality. A lot of stories are classic anecdotes and I wish there were primary sources as I picked up on a few things too many that left me feeling uncertain or that a community note would appear. The take down of EU regulatory failures and misinformation is worth the book. I did enjoy this book and it is would make for a really great “book club” discussion on innovation.

35. 😻The Canceling of the American Mind: Cancel Culture Undermines Trust and Threatens Us All―But There Is a Solution by Greg Lukianoff and Rikki Schlott https://a.co/d/02NDDgt // started reading just before university president congressional hearings. So many examples and anecdotes. There’s a whole chapter on the gaslighting of “there is no cancel culture”. It is easy to get caught up debunking this book, but it even has a section on how arguments against cancel culture are routinely made.

36. 😻Surveillance State: Inside China's Quest to Launch a New Era of Social Control b Josh Chin, Liza Lin https://a.co/d/eqDeAVV // all about surveillance and the growing risk to privacy and individual liberty. Shows the depth of the development of Chinas infrastructure and exporting it around the world. But the real stressful part is how the US and far less overtly dramatically increased the surveillance state with too little accountability. This topic drives me bonkers as far as US policy but I feel helpless.

37. 😻😻The Lessons of History b Will & Ariel Durant https://a.co/d/5fLQaXE // A concise survey of the culture and civilization of mankind, The Lessons of History is the result of a lifetime of research from Pulitzer Prize–winning historians Will and Ariel Durant. “Do we really know what history was or what really happened or is it simply a fable not quite agreed upon? Most history is guessing and the rest is prejudice.“ I wish I could read all 10,000 pages of their “The Story of Civilization”. Still the book has many cringe moments such as ”you have to breed as well as breathe.” “Throughout history man remains the same. He changes his habits but not his instincts.” The Durants were the foremost award-winning historians of a generation. Yet when I listened to this book (audio has excerpts of Durant interviews) I could not help but be taken back to 6th grade world history with Mr Huston saying things like “the negroes of the Nile” and “nature versus nurture” or “decline of religious belief is far more important than any economic battle” Durant says we are in a post-theological time in the west which is necessarily a decline if you consider history. Listening to the Durants speak was like listening to the narration record accompanying a dukane project filmstrip. Thus the best reason to read this is to think about what is taught today as history and realize it too will be cringe in 40 years or less.

38. 😻😻Classified: The Untold Story of Racial Classification in America b David E. Bernstein https://a.co/d/cTqkSGB // With all the debates over oppressed v oppressor looking at how we even categorize people in the US for things like jobs, hate crimes, preferences, etc. is critical. This book is an **infuriating** look at the arbitrary and cynical world of racial and ethnic classification. It is filled with the absurdity of the legislation, court battles, and cynical application of what amount to fairly nonsensical classifications when considering the goal. This book is must reading for anyone arguing for any disparate impact or remedy based on a classification. The system is abused from every direction and the resulting benefits go disproportionately to those not particularly harmed while the negative results continue to grow. If you really want to be upset read the chapter on race and medical research. The whole concept has gone so far astray from the original goals it is no surprise no one can agree on these topics today. The use of classifications for science research even though they are wholly unscientific is not just bad science it is harmful. tl;dr It is amazing how much a role money plays in all this.

39. 😻😻😻😻💯Chip War: The Quest to Dominate the World's Most Critical Technology b Chris Miller https://a.co/d/02Sz24S // Great quick history of Silicon. A -00-level overview of the history of silicon. Why read? Everyone needs to know the story of DRAM in the 80s especially Japan, DoD, and US companies. Also great characterization of chip company culture, founders, and execs (tl;dr very tough managers). Follow the links mentioned and keep reading (eg Made In Japan, Only the Paranoid, etc). Super fun!! Given the runup of chip stocks this seems like a required read.

Suggest some books to me in the replies! Happy 2025!

# # # # #

The concept of “disruptive” technologies or more broadly disruption in business goes back to the 1940s and economist Joseph Schumpeter and his concept called “creative destruction”. Creative destruction in the simplest terms is “the deliberate dismantling of established processes in order to make way for improved methods of production”. It can be applied to a broad set of circumstances across technology, government, finance, media, and more. As an economist he was keenly aware of the effects of such destruction, both the intended and unintended, or byproducts of such a seemingly violent way to innovate.

In the mid to late 1990s, Clay Christensen and Joseph Bower coined the term “disruptive innovation” the timing of which coincided with the rise of the modern internet and the broad-based information age. It was in part due to that timing and the businesses successes that followed that the literal meaning became second to the broad and appealing metaphor of being disruptive innovators.

Clay’s (with Bower) Harvard Business Review paper “Disruptive Technologies: Catching the Wave” and later his book “Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail” became beacons of technologists everywhere. Everyone claimed to be disrupting something. No matter what you were doing you were in the business of disrupting some old way of doing things with your new software and internet way of getting things done. From 1998-2000 (March 10th specifically) delivering groceries, selling pet food, and even creating internet money were all major disruptive efforts—and colossal failures.

We make fun of those failures today. Yet those efforts and many more proved to be not only successful years (or decades) later but wildly successful. What we forget is how much we mocked the people creating these efforts and many like them. What we forget is the litany of experts who predicted their failure. What we forget is just how difficult it was to change things.

One example from that era I will never forget is listening to the CEO and founder of one of the major shipping companies in the world explain in painstaking detail how “local delivery” (that’s what it was called when stuff gets delivered to your house) could never be any faster than the overnight shipment that was then standard, extremely expensive, and used only for very important documents or emergency machine parts and the like. The modeling put forward was detailed and excruciating. It explained why there was no way to ever deliver food or groceries from the source to a home. As a bonus he went on to explain how shipping had a baseline cost that precluded making it free and that returns of goods would always be an exception, which is why there were limits to how much one would end up buying via new-fangled internet shopping.

When a successful founder and executive dismantles an idea so many people are chasing it lends credence that is carried forth through the media, other businesses, and more broadly. The experts spoke. It wasn’t just that they spoke, it was that those attempting to challenge the experts were ignorant at best or at worst simply defying basic laws of physics. The arguments against shipping weren’t about strategy or anything, but physics of miles, time, and gallons of fuel.

Then when companies failed—delivering anything from clothes to cookies—the told-you-so comments were everywhere. Those risk-taking founders were held up as examples of people that didn’t listen to experts. They didn’t “understand” the “real world”. They were naive and wasteful.

Of course, when any sort of creative effort succeeds those same people are innovators. They “defied” experts. They are the “rule breakers”. Then they are celebrated. They creatively destroyed something.

We collectively spend significant time and energy on the “victims” of creative destruction. The companies that failed to innovate and went under. The efforts those companies failed to make or technologies/processes they failed to incorporate or capitalize on. The people that poured their labor and personal capital into efforts that failed. Often these stories turn into blame ascribed to the new success or even the single individual.

In other words, what Schumpeter describes as an essential part of systems results in the demonization of those who try and even those who succeed. Even when someone is celebrated for success, it almost never takes long before they are torn down. As much as people generally love success there’s also a view that however the success is achieved, they must not have been playing fair.

Of course, and I can’t say this strongly enough, there’s nothing in being successful that itself grants immunity from vast transgressions as history has shown. There’s nothing about having entrepreneurial spirit that makes one virtuous.

But, and I also can’t state this strongly enough as well, there is a great deal required to creatively destroy something or to develop disruptive technologies. There’s a very strong requirement that one be able to absorb significant negativity, ignore a vast inbound criticism, and make decisions that indeed have unintended consequences.

There’s one other set of skills required that many find distasteful but are equally necessary. That is, one also needs to be strongly critical of the world—the product, the technology, institution, or process—that one wishes to displace and disrupt. Many find this unpleasant.

Examples of such inter-personal challenges are endless. Some are so classic and the success so great and often so long ago we forget the dynamic. It is worth an example of two to illustrate this and explain why this is all necessary.

When Steve Jobs was leading the introduction of the iPod (this is an iPod example not even an iPhone one) he famously made the initial launch all about the benefits of mobility and having your entire music collection in your pocket. We remember those benefits. At the same time, everything about the product was attacked and often from both sides. From the sound quality to the user interface to the selection of music in the store (2003) were criticized. The music industry which had done the $1/track deal came under fire from the musicians. Because it was the early 2000s and PDAs were popular tech reviewers balked at having a music-only device. Many insisted that mobile phones needed to be the music player. The list goes on and on.

Because Steve, as we all know, was a disruptor at heart going as far back as one can, he had already lived the PC revolution, the failure of Lisa, the rise of Macintosh, the return to Apple, and more. He was not only dismissive of these and other complaints, but he was outwardly aggressive about them. At D2 May 2004, asked about coming out with a phone in this context after the galactic success of the iPod, Steve famously said there was no way to innovate in phones because the “problem with a phone is that we’re not very good going through orifices to get to the end users.”

I was in the audience at that moment and can definitely say there was an audible gasp. Here we were at what we thought was the height of cellular/mobile phones with Nokia and Blackberry on top of the world and AT&T/Cingular on a hugest of huge rolls (not unlike today’s semiconductor rally on Wall Street) and Steve just trash talked the lot of them, and rudely so. The reaction of those companies was to be rude back. Industry experts jumped on CNBC and the WSJ with stock charts of Nokia, AT&T, Blackberry, and talked about PDAs more.

Fast forward to the iPhone launch—a lesson in his reality distortion field and knowing that when Steve trash-talked something he was about to trounce it—and again the entire first part of the launch is a literal takedown of the existing phone industry. He ranted about screen size, little keys, the stylus, weird software, and more. It was brutal.

The reaction to the launch was entirely predictable. I watched that reaction from the Windows Phone team (this is the old Windows Phone with the start menu and most models had a stylus and resistive touch screen). The iPhone was dismantled on technical and business grounds. It was too expensive. Touch won’t work. One carrier isn’t how the industry worked. The carriers not ATT/Cingular pointed out that there was no way for the unique carrier services that provided real value to do their job. Blackberry went all in on battery life, typing speed, and their BBM messaging service loved by folks in finance and legal. Apple and Steve retreated from those battles and did the work of execution they knew disruption required.

The first year was brutal. It looked a lot like the 1984 Mac. It was an incredibly innovative product that came with the expert consensus that it would be at best a niche. Then the first year of sale were not mind-blowing and the “market share” of Nokia and Blackberry—and importantly their stock prices—did just fine.

Then came apps. Then came failed products that tried to thread a needle in responding. And so on. The rest is history. The creative destruction happened. RIM is what it is today. Windows Phone and Nokia was what they were. The people, teams, and ecosystems moved on. Without that destruction there can be no global smartphone revolution. The displacement of technologies, companies, and even individuals just had to happen. And those steps they took from the 1990s to 2008 or so also had to be taken. Without those innovations, those disruptions, there could have been no baseline to build today’s smartphone. Most reading this are too old to remember, but before mobile phones there were only land lines. Business communication meant an ATT calling card near the gate at the airport or spending an hour making dial up work after hijacking a hotel fax machine phone line. All that infrastructure, all those companies, all those processes were displaced.

So often when this story is told, we look back with nostalgia. We remember fondly the old way of doing things. We remember the glory of the introduction of the new way. We collectively often memory hole the absolute hell that everyone on all sides of a disruption go through. We forget:

• Experts telling us all the new thing can’t possibly work.

• Incumbents explaining all the problems with the new thing and the societal costs.

• Industry leaders detailing the failings of the new approach.

• Individuals working on the current products worried and defensive turning into anything from defiance to flight.

• Ecosystems around the current product joining in this chorus while defending their own processes, contributions, and businesses.

• Everything from public company investor relations to labor unions to trade associations going after the disruptor both the entity and the personalities associated with the disruption.

All of this is done at brutally personal levels. Some might think this is a product of the new online social network world, but above I tried to provide a glimpse of the negatives that flew around. The real costs. The real “attacks” for lack of a better word. There’s nothing that social networks, including X, do that wasn’t already happening. Yes, everyone can see it faster and sure people who aren’t in the nexus of the situation can see it happening and offer their opinions. But no one working on this suffers more because they are already suffering.

The responses or even the first volleys are also brutal and direct, as Steve Jobs was by seeding the fight with carriers. Why is that? This is what it means to lead and be at the tip of the spear of disruption. It isn’t enough to just introduce something even if one gets that far. One needs to build a team that shares the same vision and same spirit of breaking from the past to do something new. In Steve’s case and in most all cases, you must get a whole “system” to change.

Many might think this isn’t necessary or shouldn’t be. But there is no other way. An agent of change is a lightening rad because the default action for every technology, process, business, or institution is to *not* change. The response to potential change is by default to resist change and to protect status quo and incumbency. Change is difficult and individually and institutionally perceived (and in some reality) costly. This is the root of everything from NIMBY to industry groups protecting the industry.

Many also suggest that no matter what a change might be or how significant, there should be a way to ease into a change. Go slow, they say. Compromise they say. This is perhaps at the root of the most polarizing debates. Everyone always wants a simpler and longer path to a change. Why change the user interface all the way, just fix some problems. Why not provide an option to do things the old way. Give us a period of migration and adjustment.

This really doesn’t work the way people think it should. The problem with half-measures is that they are, well, half measures. Taking baby steps all but guarantees the innovation will fail. Amazon famously ignored the experts around retail and refused to accept telephone orders (I had a friend from college who worked hourly staffing a phone center for people calling up trying to order books). The problem is obvious in hindsight which is building out a whole system and process to handle phone orders, phone returns, phone credit card charges, etc. All of those take time and effort away from building out e-commerce which was the goal. Importantly once they would take orders by phone there would almost never be a way to turn it off other than to wait until no people order that way. Think about how long it took Netflix to stop mailing out DVDs or how many people still have dialup internet surprisingly. The long tail not only costs a lot of money and time, but literally prevents disruptive innovations from being fully formed and focused.

Disruption is one of my recurring themes in “Hardcore Software” where I write about accounts going back to just literally using C++ to write Windows programs (“can’t work”) through building a suite of products (“need best of each category”) to introducing a server for Office (“no one wants a server for Office”) to Clippy (embarrassing) to resigning Office head to toe, and yes Windows 8.

One of my most significant and early lessons that helped me to see the personal cost to experts when it comes to what I think everyone might consider routine innovation is when we did the most mundane thing to the “setup program” for Office in the 1997. This was literally just the way files got copied from the floppies to the hard drive to run. Enterprises customized Office setup back then and to do that they would edit what amounted to our *internal* table of files to be copied, SETUP.INF. It was a crazy format fragile and inscrutable, but necessity mandated they figure it out.

We introduced a whole fancy new database (you might know this as MSI files in Windows today) to make it “easy”. In the process, though, the very people we were trying to help ended up hating, I mean hating, what we did. Why? Not because it wasn’t better. No, simply because it was totally different. We were victims of our success and by changing it we took away their skills. We make it harder for them to be successful. They didn’t pay to price of fragility down the road that we were worried about (stuff like “corrupt registry). They just had to learn a new thing. Time passed. Everyone adapted.

I could repeat this for a half dozen other things. Changing the user interface for hundreds of millions of people using Office over decades was an even bigger deal with a massive pushback. That worked. Changing the Start menu for Windows, not so much.

I can say with certainty, success or failure feel exactly the same, carry the same dynamics, and attempting or succeeding at being disruptive comes at an enormous personal cost even though it is incredibly difficult. It also isn’t automatic. For example, iPod or every dot com failure, there are untold other failures and more, but far fewer successes, but the pattern is always the same.

Not everything is a disruptive change and it can be pretty lame to label everything and anything (from a startup or anywhere) as such. Certainly just applying that label isn’t an excuse to be rude in public discourse. In other words, the actions of disruptive behavior need support the broader disruption.

Therefore, when someone or some organization is trying to do something new and dare say taking on the role of a disruptor, recognize that the pattern will always be for others that see the change as a risk to tear down what they are doing. The disruptors will be broadly critical of what they intend to replace as they marshal the teams, ecosystems, and resources required. There’s simply no other way.

It is worth remembering this reality when being critical, harsh, or personal while the change is being attempted and put in motion. Ask yourself if your reaction is coming from a place of defense, a glass house, or maybe just reacting to the style of a disruptor trying something bold or difficult.

It is called creative destruction or disruptive change for those reasons.

Most people who have built an automation…