I wish he went back to writing educational blogs/books/papers/material so we can learn how to build AI ourselves.

Most of us have the imagination to figure out how to best use AI. I'm sure most of us considered what OpenClaw is doing like from the first days of LLMs. What we miss is the guidance to understand the rapid advances from first principles.

If he doesn't want to provide that, perhaps he can write an AI tool to help us understand AI papers.

AI from first principles has not changed. Fundamentally it is: neural nets, transformers and RL. The most important paper in recent years is on CoT [https://arxiv.org/pdf/2201.11903] and I'm not even sure what comes close. And I think what's more important these days is knowing how to filter the noise from the signal.

This is probably one of the better blogs I have read recently that shows the general direction currently in AI which are improvements on the generator / verifier loop: https://www.julian.ac/blog/2025/11/13/alphaproof-paper/

He did. His entire startup is about educational content. Nanochat is way better than llama / qwen as an educational tool. Though it is still missing the vision module.