> Most abstractions in software exist because humans need help...It's not clear yet which abstractions are truly foundational and which ones were just crutches for human cognition... We took an API contract, a build tool, and an AI model, and the AI wrote everything in between.

I have a couple questions:

1. I think this quote should be raising *many more* eyebrows.

> The astounding thing about Goliath wasn’t that is was a huge leap in performance, it was that the damn thing functioned at all. To this day, I still don’t understand why this didn’t raise more eyebrows.

You put a cat's brain into a dog's head and its still breathing! It didn't flatline immediately! Is yesterday's news? This seems like the biggest take away. Why isn't every attempting LLM-surgery at this moment? Have you noticed any increasede discourse in this area?

2. You mentioned you spent the beginning of your career looking at brains in biotech. How did you end up in a basement of GPU's, working not in biotech, but still kind of looking at brains?

Again, great post!

I wonder if this is similar to Chess and Go getting 'solved'. Hard problem spaces that only the biggest brains could tackle. Maybe it turns out creating highly performant, distributed systems with a plethora of unittests is a cakewalk for LLMs, while trying to make a 'simple web app' for a niche microscopy application is like trying to drive around San Francisco.

> In practice, that means more logic fits in context, and sessions stretch longer before hitting limits. The AI maintains a broader view of your codebase throughout.

This is one of those 'intuitions' that I've also had. However, I haven't found any convincing evidence for or against it so far.

In a similar vein, this is why `reflex`[0] intrigues me. IMO their value prop is "LLM's love Python, so let's write entire apps in python". But again, I haven't seen any hard numbers.

Anyone seen any hard numbers to back this?

[0] https://github.com/reflex-dev/reflex

I'm not diminishing the ethics debate, but it's crazy to me how easy it was for two non-technical rich dudes in a garage to build Clearview AI (And before vibe-coding!):

  1. scrape billions of faces from the internet
  2. `git clone` any off the shelf facial-recognition repo

[0] https://en.wikipedia.org/wiki/Clearview_AI#History

I want to highlight what I believe is the coolest innovation: their novel O-Voxel data structure. I'm still trying to wrap my head around how they figured out the conversion from voxel-space to mesh-space. Those two worlds don't work well together.

A 2D analogy is that they figured out an efficient, bidirectional, one-shot method of converting PNG's into SVG's, without iteration. Crazy.

I don't know if TLA+ is going to suddenly appear as 'the next language I want to learn' in Stackoverflow's 2026 Developer Survey, but I bet we're going to see a rise in testing frameworks/languages. Anything to make it easier for an agent to spit out tokens or write smaller tests for itself.

Not a perfect piece of evidence, but I'm really interested to see how successful Reflex[1] is in this upcoming space.

[0] https://simonwillison.net/2025/Dec/15/porting-justhtml/ [1] https://github.com/reflex-dev/reflex

But isn't the drama between the billionaire heiress and her starving-artist lover more interesting than the lawyer girlfriend deciding whether she wants to marry her below-average-salary boyfriend?

Or maybe I don't understand your complaint.

> Omnilingual ASR was designed as a community-driven framework. People around the world can extend Omnilingual ASR to new languages by using just a few of their own samples.

The world just got smaller

I'm curious if you mean they're running a raytracer on the back end, and you interact with an HTML UI, or if it runs browserside, maybe via WASM. AFAIK CUDA isn't directly compilable to WASM (yet?)

The only catch is that generating blue noise is a roughly O(n^2) algorithm. Its not feasible to be generated on the fly, so in practice you just pregenerate a bunch of blue-noise textures and tile them.

If you google 'pregenerated blue noise' you find plenty of them: https://momentsingraphics.de/BlueNoise.html

I wonder if Google's got some tricks up their sleeves after their decades of having to tease signal from the cacophony of noise that the internet has become.