Model training is the slowest inner loop in an ML organization: one big run at a time, days or weeks per iteration, mostly serial. Lee Robinson opens this AI Engineer talk with a blunt framing — the whole game at Cursor right now is to shrink that inner loop, because whoever iterates fastest ships the best coding models. Every part of the talk is a concrete answer to “what does that actually look like?...
The Latent Space “Cooking with…” series put OpenAI’s Chief Research Officer Mark Chen in a kitchen and got him to talk through the things research-org leaders rarely say on the record: where scaling laws actually live in 2026, why post-training and RL are the real bottleneck now, how OpenAI structures evals against a moving frontier, and what “AGI” means when you’re inside the org that named the goal. This is one of the higher-signal AI Engineering interviews of the year — partly because Chen is unusually specific, partly because the format (informal, no slides, no PR minder) catches him in mid-thought....