Sottiaux's milestone announcement (3485 likes): 'ChatGPT Work officially has overtaken Codex in number of active users. Way to go.' — a real inflection point for OpenAI's productivity suite.

His voice feature endorsement (901 likes): 'Game changer when used from mobile. Available in the ChatGPT app already.' The voice + mobile combination is clearly resonating with users.

His philosophical framing (608 likes): 'It was always possible to speak to your computer. It wouldn't do much in return. But we fixed that bug.' — reframing the AI revolution as a bug fix.

Rauchg's factory thesis (1050 likes): 'The (software) factory is the product. Your product is only as good as the agents you set up to autonomously maintain it. This is what @elonmusk figured out about Tesla, and it's now true for the software world.' — the manufacturing-inspired framing of AI-native development.

His research workflow (772 likes): 'I started doing all my research with agent CLIs and the filesystem. A research/ folder, an AGENTS.md describing the format I like and best practices. Then launch my agent and ask a question. No fancy UI needed.' — pragmatic agent usage that anyone can adopt.

His manifesto on agent.md (604 likes): 'is more fundamental than any other framework we've built. It's the genesis of your company. When you have a new idea, don't think: I'll go to an agent and ad-hoc prompt. [Think: I'll update the agents.]'

Levie on Google joining (1351 likes): 'Now with Google on board, this is a complete endorsement of open weights AI. Pretty big moment for the industry.' The open weights coalition now includes OpenAI, Google, Box, and many others.

Steipete's competitive analysis (1441 likes): '1) Competition is good for the ecosystem. 2) Serving models at scale is hard. Proud that @OpenAI signed the letter. Ant is silent on it.' — noting Anthropic's absence from the open weights movement.

Madhu Guru on consensus formation (33 likes): 'In uncharted territory, answers to hard questions only come from repeated contact with reality. Been thinking about how quickly the US AI community converged on support for open-weight models.'

Steipete's parallel QA session (747 likes): 'Been running codex all day to do massive parallel QA in prep of the next release. Sol got insanely good at really understanding intent and is finding complex behavior issues.' Plus his 12-subagent QA prompt (202 likes): 'Do a full end-to-end QA test of OpenClaw with live API keys. Use 12 subagents to split up functionality.'

Peter Yang's episode preview (146 likes): 'Jason is a DevEx engineer at OpenAI who wrote the official guidebook on how to use Codex for work. In tomorrow's episode, he showed me his complete Codex work system, including how to: run a chief [of staff agent].' Plus model analysis from Kun (269 likes).

Nikunj on CEO power (115 likes): 'No one will admit this but you can only do this sort of thing if a) the CEO has complete control of the company and b) you are as ambitious and crazy as @D[harmesh].' Amjad's chess engine (168 likes): closing in on 1200 Elo with one small finetuned LLM.

Garry Tan on SF housing (184 likes): 'We should prioritize people and a vibrant community and more housing far far far more than some guy's views.' Plus his dad moment (562 likes): 'My dad was cheering real loud from the stands. Dad stop you're embarrassing me.' And his shitpost disclaimer (35 likes).

Matt Turck's chip landscape overview (14 likes): 'Chip landscape 101 with @andrewdfeldman: CPU, GPU, NVIDIA, AMD, TPU, Trainium, Cerebras, etc.' Plus VC Anthropic meme (67 likes): 'VC trying to resist the temptation to buy three shares of Anthropic through an SPV before the IPO.'

Dan Shipper's reaction (233 likes): 'this is crazy.' Zara on AI-native culture (31 likes): 'AI-native companies have a culture akin to an open-source community.' Plus her workflow question (42 likes): 'What do you do when you're waiting for AI output?'

Unsupervised Learning Ep 91: a top AI analyst unpacks today's AI hype cycle. Full transcript (92435 chars) covers the electricity analogy ('AI is like electricity — but what actually happened with electricity?'), Jeff Hinton's job loss warnings, and whether the current hype cycle mirrors previous technology adoption patterns. The conversation digs into logical fallacies around AI doom arguments and historical precedents.