Everyone is already cloning the app layer. There are 30+ claude-code clone, and codex work already cloned cowork, grok and gemini is doing the same.

Once for each arrival.

China is obviously in the GPU/RAM race. Heard of Huawei, Moore Threads, Lisuan Tech, CXMT?

> Many providers build their proxy pools by partnering with device owners who agree to share their bandwidth, while others use embedded SDKs in free apps or VPNs.

WTF. That's just botnets.

Source: https://www.fbi.gov/investigate/cyber/alerts/2026/evading-re...

The responses I get from pro don't feel like ensembles. They are often very one directional.

Mathematics is a social activity. The research cultures of different branches matter.

Not sure exactly what you're proposing, but if the noise is added independently to different people, you can just buy multiple copies to reduce it.

There are a lot of ways to do this wrong, which is why so much analysis has gone into differential privacy.

I ran a bunch of different compilers on it, including some open source ones.

Some of them failed some tests, and it was natural to have my LLM (Claude Fable 5) root-cause the issues, and to double-check my test bench wasn't to blame.

But now I stood with all these patches that I couldn't just throw at the upstream maintainers all at once. I ended up just filing a few issues and moved on to other things.

It felt weird to just file issues when my LLM had already spent a lot of time root-causing and fixing the issues. But then, maybe they could just have their LLMs do the same.

Still not sure if it was the right call?

To me it definitely feels like it's still accelerating, with the most impactful recent discovery being RL training reasoning models (late '24, early '25).

There's an interesting article called "sigmoids won't save you" https://www.astralcodexten.com/p/the-sigmoids-wont-save-you which argues that (unless you have privileged information) you should always assume a process will continue about as long as it’s continued already. (Lindy's Law)

With that in mind the current disruption should last another 10-15 years (assuming it started in '10 or '17.)

Building compilers has a _lot_ of parallel tasks agents can work on.

Wish me luck..

I use more than 150B/month with just 15 codex accounts.

60 accounts is "just" $12,000/month. So Peter could "save" 100x by using monthly accounts.

Of course, he doesn't have to, as he works at OpenAI now.

I'm considering between SVA, TLA+ and Lean. With the former being more domain specific and the later more general.

Do you think we'll move towards "Lean for everything" or do domain specific formalisms still make sense?

The AI won't even know where the page of text it's seeing came from, and people will avoid your book as they can just ask the AI. So you make less money. (Talking about specialized technical books here.)