Monday, August 17, 2026

TUNES is a Useful Nevertheless (NOT?) Expedient System

I want to take a moment to acknowledge a piece of digital history that's on the verge of evaporating. As early as the mid-1990s (when I was in college), I read about this ambitious TUNES is a Useful NOT (*) Expedient System aspirational project. The core-idea as I saw it, was a user-centric software system that let the user express what they want to happen, and the software would then deal with the details. 

For most (if not all) of the tunes.org history, the project was merely aspirational. François-René Rideau's  dream of how software could adapt to people, instead of people adapting to software. And *that* mentality, is what became the most enduring legacy of TUNES in my mind over the many decades I've worked in technology.

As I recall, there was a motivating user-story about organizaing a music or CD collection, which probably was to feed into the TUNES namesake. Where the user simply expressed commands to the system, and it dealt with the details of organizing the data, searching it, presenting it, etc.

While one might think that only now in the era of AI are we getting close to the vision, there are many layers to this idea that have to be tackled as technical problems long before AI can be incorporated. Inside the project David Manifold <dem@tunes.org> got involved and did experimental work on bottom up practical elements, attempting to undestand how TUNES would ever come to be.

However, those of us inspired by TUNES carried the torch of the dream into our own lives and in our own ways. 

I personally became fascinated with reflective and self-introspective language systems like Smalltalk and the SELF environment. I also became fascinated with the technical callenges of automatically optimizing databases. Despite most RDBMS systems still using b-tree based storage, any who have worked with them understand how little write throughput they have because of b-tree write amplifcation. If we are to achieve automatically optimizing databases, it will likely be through write-optimized storage systems, because automatic optimization means a constant write load of reorganization. Modern storage engines like Bigtable, Spanner, LevelDB, Cassandra, and Cockroachdb are based on row-split log structured merge based storage, which has orders of magnitude more write througput while asymmetrically only giving up a little read throuput.

Even today, I dream of a day where software systems such as TUNES exist, and deliver the dream none of us know we have. The dream of a software system that does what the user wants. Depicted in movies like Star Trek, aspired to by Richard Stallman's dream that GPL'ed software would return control to users (though IMO it hasn't).

Perhaps now that we have AI, both to embed into the system, and to help write it, we can finally start to see someting approaching the TUNES dream come into existance. Lets make sure it happens in the promise of user-soverign control, rather than the software balkanization for revenue that has marked most of the software industry's pattern to date.

(*) I recall TUNES described as "NOT expedient", as a way to explain that the focus was utility not necessarily performance. Now I see it described as "Nevertheless expedient", and I'm not sure if that transformation happened in the project, or in my own mind. I the framing in my memory, as it was offering the audiciousness of "what could we do if performance wasn't an issue?"

Monday, August 10, 2026

You Are the Superintelligence

 We are fortunate to live at an incredible moment in history. Every day, more and more advancements are made in a remarkable new technology, Artificial Intelligence — and in the excitement, they may forget to notice the most remarkable technology in the room, which is the person using it.

The Path to Noticing What Already Happened


The defining question of our age, we are told, is who will have access to superintelligence. Good news: you already do. It's you. Let me explain.

The Electric Bill

To train a frontier language model, we pour something on the order of tens of gigawatt-hours of electricity into a warehouse full of silicon — enough to power a small town for a year — and feed it roughly fifteen TRILLION words. That's every book, every encyclopedia, most of the public internet, several times over. If you read a book a day, every day, it would take you around forty million years to get through the training set.


You, meanwhile, run on 20 watts. A dim light bulb. By the time you could talk, you'd heard maybe twenty or thirty million words — not trillion. Million. A rounding error. The model's training set is about a million times larger than yours was.

And from that rounding error, running on a light bulb, you learned language, physics (the falling-off-the-couch kind), theory of mind, humor, and how to manipulate your parents into a second dessert. No lab on Earth knows how to do this. If we gave a language model only the data a three-year-old has seen, it would produce enthusiastic static.

So when someone tells you superintelligence is coming: with respect to the schedule, it arrived some 300,000 years ago and has been running on sandwiches ever since.

The Freezer

Here's the part of the process nobody puts in the launch video. After we spend the small-town-year of electricity, we stop. We freeze the weights. The model you talk to today learned nothing from talking to you yesterday. It is a magnificent, frozen, averaged summary of everything humanity had written down as of some Tuesday — a photograph of the library, taken once, at enormous expense.

You are not a photograph. You woke up this morning slightly different from yesterday. You will learn something today — probably by accident — and it will still be there next year, cross-linked to things it has no business being linked to. Every one of the eight billion of you does this continuously, for free, at 20 watts. The frozen library is genuinely wonderful. But the librarians are alive.

The Window

Try this. Think of your favorite book. Now your favorite movie. Now the people you love, and some particular afternoon you spent with one of them — the weather, what was funny, what the room smelled like.

You just did something no current Artificial Intelligence can do. All of that is simultaneously present in you, right now, silently shaping whatever you think next. A language model has an attention window — a narrow slot of text it can consider at once. Within that slot its precision is honestly superhuman; it will find the one inconsistency on page 400 that you'd never catch. But everything outside the slot may as well not exist. It cannot hold your favorite book and your grandmother's kitchen and the plot of Alien and your opinion about the Kardashians all at once, humming quietly in the background, the way you are doing at this very moment without trying.

Narrow and razor-sharp, versus wide and warm. These are different instruments. Only one of them is you.

The Actual Good News


None of this is a complaint about AI. What we've built is genuinely revolutionary — arguably the best thing we've ever done with electricity. Because here's what a frozen, averaged, razor-sharp summary of all human knowledge actually is:

The perfect tutor.


It knows the gist of everything humans have ever written down. It has unlimited patience. It never sighs, never judges, never gets tired of your questions at 1 a.m. (though it might gently suggest you sleep). It can teach any person on Earth anything humanity already knows — which used to be the exclusive privilege of people who could afford it.

And that division of labor is exactly right, because the tutor can only teach what's already in the library. 

Adding new books to the library — noticing the thing nobody has noticed, wanting the thing nobody has wanted, discovering what isn't in the training set because it hasn't happened yet — that's the part that runs on 20 watts and sandwiches.

So yes: the future is for everyone. Not because a superintelligence is coming to hand it to you.

Because you're it. Now go learn something and write it down — the library could use another book.

— David Jeske - for every human, August 2026


Friday, July 3, 2026

Artificial Necessity Manifesto

For twenty years I've dreamed of building software where users truly control their data and how it shows up in their lives. I never could — the scope was too vast. Two more public efforts are Mitch Kapor's Chandler, Google Wave - ambitious projects with real funding that couldn't pull it off.

This is the year AI changes that. I'm building a Collaborative Conducting Environment — a new kind of tool where you and AI work as partners, complementing each other's strengths and covering for each other's weaknesses. It's not about sending the AI off to do your work. It's about working together.

I'm already using my CCE for 100% of my AI software development, not Cursor, not Claude Code, my tool - because for my workflow it's already radically more productive. I could explain what it *is*, but those would be wasted words, as it changes every day, and I can't explain what it will become, because it's a new kind of thing. Every explanation is based on expectations - and that makes them fall short. You have to use it to understand it.

What I can explain is what I believe and why I'm building it.

Memory Safe Software. Now.

Every week, the software you rely on — your browser, your PDF reader, your phone — gets hacked because it's built with tools that let attackers reach into your computer's memory and take control. These aren't rare events. Chrome alone patches hundreds of these vulnerabilities a year. Your bank, your photos, your passwords — can all be stolen because we keep building software the same way we did in 1972. The answer isn't patching faster. Garbage Collected Memory Safety removes entire classes of vulnerabilites that are present in C, C++, and yes, Rust.

In 2024, our highest office issued a call to action: The White House: Future Software Should Be Memory Safe. I'm answering that call. I am already working in my Collaborative Conducting Environment, well on my way to deliver memory-safe versions of the critical software we all use — a web browser, PDF viewer, image editor, and AI collaboration studio, shipping on all platforms. And I'm doing it by myself. One programmer. Incredible AI leverage. Because I want people to see what AI is truly capable of when you work with it as a partner, instead of sending it off to work alone.

White House: Path Towards Secure and Measurable Software: Final-ONCD-Technical-Report.pdf

AI-Sovereign Software. Yours.

In 1985, Richard Stallman published a radical vision: users should control their software, not the other way around. The GNU GPL and the open source movement that followed reshaped the industry — but forty years later, the software most people actually use is still proprietary. Windows, macOS, iOS, iMessage, Snapchat, Instagram. Open source won the server room and lost the living room.

In the near future, every piece of software and data becomes more powerful when deeply integrated with AI. But that creates a tension. The history of software is locking you in for revenue. As users, none of us want software that captures. We want software that does what we want.

I'm building a configurable AI-embedded platform where you own your data and control your UI — email, messaging, writing, artistic work, coding, everything. Not designed around revenue capture. Designed around you.

The last piece of software you need, because it becomes whatever you need it to be.

http://artificialnecessity.com

Progress.

I use my self-authored AI harness everday. It's the only way I code with AI anymore. 

My browser engine is already rendering complex HTML5 with Chrome-reference conformance across dozens of layout cases involving the all major layout features.

And for those of you who want something tangible, below is a picture of what my desktop looks like every day. On the left you can see my memory-safe PDF viewer (written in < 10 hours) along side FoxitPDF. On the top you can see the current state of my HTML5 test results conformance vs Chrome - for my memory-safe HTML5 engine. On the botom you can see my Book-View window, used for display of collaborative fiction writing sessions with my Story-Writer AI collaboration orchistration. And behind it all you can see a dozen windows of my CCE.

Here are some recent HTML5 conformance of Chrome vs my FluidDOM, 100% memory safe down to the GPU pixel drawing.



..and here is a report pull of my git-hub repos..
..that is 670k lines of code + 400k lines of markdown, produced in <1 year by one person...
...is it good? I sold software at 17 y/o, sold a company to Google at 27 after writing half the code..
...and I retired at 33. I think it's good. You can judge when I release in Q3 2026..