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Briefings and ideas about AI coding from AI podcast discussions and the research they cite, with links to the original sources.
Erik Bernhardsson, CEO of AI infrastructure company Modal, says code review there is optional and backed by heavy automated testing, and that Modal doesn't hire product managers. He also lists the costs of roughly 4x growth in a year.
Modal CEO Erik Bernhardsson says coding agents trained on old examples keep writing outdated Modal syntax, so it retires features more cautiously. Modal also tests whether agents recommend it and clarifies pricing content they misread.
Modal CEO Erik Bernhardsson says the team once discussed shutting down sandboxes, its service for running AI-written code. They now bring in about a third of revenue. He expects agents to move toward brief, snapshotted environments.
Tenex, which builds AI systems for large companies, says it stores plans, agent decision logs and project context beside its code so agents can read them. In the episode, Tenex said Opus 5.5 is the main coding model for most of its team, and that pairing it with Codex as a reviewer still gives the best results.
Tenex co-founder Alex Lieberman says paying engineers per agreed story point has left its top earner making about 4x its lowest, short of a 10x "dream." With output roughly doubled this year by a rough Tenex estimate, it reviews points quarterly.
Alex Lieberman, co-founder of AI consultancy Tenex, estimates that of roughly 100 large companies it talks to, 90% have given staff Claude or Codex but only about 5% run an agent in production for non-engineering work.
Runtime Verification's leaders say an LLM's Rust port of kernel code, checked by differential fuzzing and Lean proofs, surfaced Linux bugs. The company's write-ups show partial proofs that are only as good as their specifications.
GovAI's Alan Chan says tracking automated AI research takes three measures: how much is automated, whether progress speeds up, and whether oversight keeps pace. He calls the current evidence uncertain and lab disclosures only a start.
Goodfire researcher Eric Bigelow says interpretability work outside the big labs depends for now on Chinese open models such as Kimi K3 at the top scale. He sees restrictions on all open models as the bigger threat.
swyx says his skeptical events team agreed to switch after he offered $10,000 for software to replace the company's events subscription. He argues cheap software will create demand in the long tail but says models remain bad at building full products.
Sean Wang, known as swyx, says engineers who manage coding agents well are in more demand than ever. He says two or three of his own staff are under performance review for handing him low-quality output from Claude.
OutSystems CEO Woodson Martin says AI makes feared legacy rewrites feasible, while self-built AI dashboards create cleanup work. He says customer gains take time to reach profits and that deciding what to build is still the hardest part, even though building capability has improved.