Inside PM at Anthropic: Who Makes It, and Who Doesn’t
Nikhyl Singhal with Dianne Na Penn · 29 October 2026
Read the originalDianne Na Penn, who leads product for Anthropic's research teams, expects new product managers to read the history, then challenge researchers and executives, and plans a month at a time.
Nikhyl Singhal, host of The Skip podcast, interviewed Dianne Na Penn, Anthropic's first technical product manager and now lead of product for its research and Labs teams. Singhal's written summary, cross-posted in Lenny's Newsletter, describes how her team hires, starts and keeps product managers. New hires get a demanding assignment, little structure and the expectation that they will question senior people.
- The onboarding plan says the first two months should feel among the hardest of a career, and new hires are advised to read two months of public channels and arrive with a view.
- Deference is the habit that fails: new hires first learn what was tried and why it died, then question researchers and executives.
- The team dropped annual goals that went out of date within weeks, and now sets a short list of assumptions for three to six months and a one-month plan.
- Early-career product managers and forward-deployed engineers who moved into product stand out, because they have little process to unlearn and already know the users.
A product leader can give new hires a hard first assignment and point them to the written history rather than to a sequence of sign-offs. This is one manager's account of her own team, read in the host's written summary and not in the full episode.
Tell each new product manager to read the last two months of the team's public channels, then bring a written view to the team instead of asking for a catch-up.
Replace annual product goals with a short list of assumptions about the next three to six months and a plan rewritten each month.
Derived by Working Surface from the article; more in the Playbook. Source line: Stubborn is her word for the few commitments that survive the monthly replanning.
1 November 2026: Teams putting AI agents to work decide in advance which steps a person must still take, and that person carries more review and a greater duty to push back.