Deep Reads

OpenClaw Power, MacBook Simplicity: Five Days With Grok Bot

SpaceXAI’s Grok Bot has the same level of programming power as OpenClaw, but it’s programmable at a different level of abstraction.

[AINews] GPT-6 Astra: OpenAI’s biggest LLM launch of all time

new SOTA computer use and coding, 2.5x pricier per token, but WAY cheaper per task, less monitorable. overall, a very successful launch of OpenAI’s new frontier model class.

GPT-6 Astra: an automated AI Engineer you can hire for <$6 an hour

We spent 20B+ tokens of GPT-6 Astra to explore everything. Here’s our learnings.

[AINews] Muse Spark 1.3 matches GPT-5.6-Sol, confirming Meta Superintelligence as the newest Frontier Lab, >90% discount for training

an epic comeback story for Meta

Agency and Agents

From the Hugging Face Incident to Twilight Factories

An opinionated guide to which AI to use to do stuff

The Summer 2026 Edition

The twilight of the chatbots

How work changes along the exponential

What it feels like to work with Mythos

Claude Fable represents another big jump in AI

Teaching Everyone to Fish for Tokens

Nvidia wants you building your own model, not buying from Anthropic/OpenAI.

GLM-5.3: How Chinese labs keep stride with the frontier

Hint: It’s really not a distillation story.

I wrote an AI textbook — how long until AI can do it better?

Reflections on AI's writing ability and how AI models get more capable.

5 useful things you'll learn in my new post-training textbook (shipping now!)

After a few long years of finding time to document my lessons from training open models, my post-training book is done!

My friends all hate AI; I just joined an AI startup

Over a decade after co-founding fast.ai, I am returning to the field

I Don’t Want a Learning Dashboard for My Child

What analog and AI education both get wrong

Breaking the Spell of Vibe Coding

Sinister variations on the positive state of flow

How To Use AI for the Ancient Art of Close Reading

Experiments in reading with LLMs

AI agents can't yet do open-ended AI research

Early evidence from two case studies

What will be left for us to work on?

My keynote at ICML 2026

Up the Stack: How AI’s Escape From the Commodity Trap Risks Enterprise Lock-in

Critics and boosters are both looking in the wrong place

Why AI hasn’t replaced software engineers, and won’t

Coding agents as normal technology

What America has meant to me

Every time I have given up on America, it has been a mistake. And yet, America has never, ever given up on me.

AIE Singapore: The Agentic Nation

i gave a little talk as closing keynote for the first AI Engineer Singapore. burned some bridges but said what i felt.

What you can do in a decade

I turned 40 today. For my 35th I did principles, but for my 40th, I wanted to offer perhaps more useful reflections.

How to Thought Lead (2026)

I first started compiling "How To Thought Lead" in my notes 5 years ago, at first as an ironic parody and then slowly becoming sincere, and never published it, 1) because I don't…

Harness Engineering for Self-Improvement

The concept of recursive self-improvement (RSI) dates back to I. J. Good (1965), where he defined an “ultraintelligent machine” as a system that can surpass humans in all intellectual activities and design better machines to improve itself. Yudkowsky (2008) used the phrase “recur

Scaling Laws, Carefully

Scaling laws are one of the most critical empirical findings in deep learning. The observation is simple in form: the training loss $L$ decreases predictably as we scale up model size $N$, dataset size $D$, and compute $C$, following a power-law curve, which appears as a straight

Why We Think

Special thanks to John Schulman for a lot of super valuable feedback and direct edits on this post. Test time compute (Graves et al. 2016, Ling, et al. 2017, Cobbe et al. 2021) and Chain-of-thought (CoT) (Wei et al. 2022, Nye et al. 2021), have led to significant improvements in

Reward Hacking in Reinforcement Learning

Reward hacking occurs when a reinforcement learning (RL) agent exploits flaws or ambiguities in the reward function to achieve high rewards, without genuinely learning or completing the intended task. Reward hacking exists because RL environments are often imperfect, and it is fu

After Orthogonality: Virtue-Ethical Agency and AI Alignment

Preface This essay argues that rational people don’t have goals, and that rational AIs shouldn’t have goals. Human actions are rational not because we direct them at some final ‘goals,’ but because we align actions to practices[1]: networks of actions, action-dispositions, action

AGI Is Not Multimodal

"In projecting language back as the model for thought, we lose sight of the tacit embodied understanding that undergirds our intelligence." –Terry Winograd The recent successes of generative AI models have convinced some that AGI is imminent. While these models appear to capture

Shape, Symmetries, and Structure: The Changing Role of Mathematics in Machine Learning Research

What is the Role of Mathematics in Modern Machine Learning? The past decade has witnessed a shift in how progress is made in machine learning. Research involving carefully designed and mathematically principled architectures result in only marginal improvements while compute-inte

What's Missing From LLM Chatbots: A Sense of Purpose

LLM-based chatbots’ capabilities have been advancing every month. These improvements are mostly measured by benchmarks like MMLU, HumanEval, and MATH (e.g. sonnet 3.5, gpt-4o). However, as these measures get more and more saturated, is user experience increasing in proportion to

Moving To Substack

I’m freezing this blog and starting to post on my Substack instead. The authoring experience is much more convenient for me there. Please follow me there, and check out The Illustrated DeepSeek R-1 if you haven’t yet. And check out our How Transformer LLMs Work course!

Generative AI and AI Product Moats

Here are eight observations I’ve shared recently on the Cohere blog and videos that go over them.: Article: What’s the big deal with Generative AI? Is it the future or the present? Article: AI is Eating The World

Remaking Old Computer Graphics With AI Image Generation

Can AI Image generation tools make re-imagined, higher-resolution versions of old video game graphics? Over the last few days, I used AI image generation to reproduce one of my childhood nightmares. I wrestled with Stable Diffusion, Dall-E and Midjourney to see how these commerci

The Illustrated Stable Diffusion

Translations: Chinese, Vietnamese. (V2 Nov 2022: Updated images for more precise description of forward diffusion. A few more images in this version) AI image generation is the most recent AI capability blowing people’s minds (mine included). The ability to create striking visua

Common pitfalls when building generative AI applications

As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This is a quick note with examples of some of the most common pitfalls that I’ve seen, both from public case studies and from my personal experience. Because these pitf

Agents

Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.” The unpre

Building A Generative AI Platform

After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines the common components of a generative AI platform, what they do, and how they are implemented. I try my best to keep the architecture general, but ce

Measuring personal growth

My founder friends constantly think about growth. They think about how to measure their business growth and how to get to the next order of magnitude scale. If they’re making $1M ARR today, they think about how to get to $10M ARR. If they have 1,000 users today, they think about