Building a Product and Engineering Relationship that Works
summary
Panelists give concrete practices: measure success by shipping and learning, run about a dozen hypotheses at once with A/B tests (deploy to 10% of audience then roll out), use the RACI model and “inception” brainstorms to lock roles and decisions, and surface tech‑debt tradeoffs in OKRs. Claims: clarity + trust + measurable hypotheses beat opinion wars; ML teams explicitly need PMs; companies ≈50 employees require a dedicated PM. Breakdowns trace to unclear roles, poor communication, or low psychological safety.
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chapters (21)
- 0:00Intro
- 2:58What does a good product and engineering relationship look like
- 4:40What makes it work
- 6:28Shipping Value
- 9:31Hypothesis
- 11:42Bringing the teams together
- 15:10The importance of facilitation
- 18:14The importance of input
- 18:58Product and engineering relationship breakdown
- 22:29Signs of dysfunction
- 25:02Biggest mistakes
- 28:34Roles and responsibilities
- 30:20Briefs
- 31:14Definition of PM
- 33:03PMs need to be technical
- 34:24How much time should be spent on technical debt
- 37:59How do you square an inch team with a product team
- 39:22What role do product leaders have in shaping the engineering team
- 41:25How do you recommend structuring project or engineering teams
- 43:29What do you do if an engineer and your team comes to you
- 46:23Rapid Fire
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