AI-Native Teams Are Collapsing the Engineer/PM Split
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AI-native software engineering teams operate very differently than traditional teams. The obvious difference is that AI-native teams use coding agents to build products much faster, but this leads to many other changes in how we operate. For example, some great engineers now play broader roles than just writing code. They are partly product managers, designers, sometimes marketers. Further, small teams who work in the same office, where they can communicate face-to-face, can move incredibly quickly. Because we can now build fast, a greater fraction of time must be spent deciding what to build. To deal with this project-management bottleneck, some teams are pushing engineer:product manager (PM) some teams are pushing engineer:product manager (PM) ratios downward from, say, 8:1 to as low as 1:1. But we can do even better: If we have one PM who decides what to build and one engineer who builds it, the communication between them becomes a bottleneck. This is why the fastest-moving teams I see tend to have engineers who know how to do some product work (and, optionally, some PMs who know how to do some engineering work). When an engineer understands users and can make decisions on…

Context
When implementation becomes faster, waiting for product decisions can become the next delay. Andrew Ng describes small teams using coding agents in which engineers also learn users' needs and make some product decisions. Combining those responsibilities can shorten the handoff between choosing a change and building it.
This develops Ng's earlier argument about specification work: more capacity to build creates more work deciding what to build. The newer essay emphasizes broader individual roles as one response. Its observations concern teams of roughly two to ten people, so the supported point is about reducing coordination delays in small teams, rather than prescribing a staffing ratio for every organization.
postCheap Code Makes Specification the Scarce SkillAndrew Ng
postThe Product Management Bottleneck in Agentic CodingAndrew Ng
articleBeyond code generation: rethinking engineering productivity in the age of AI agentsIlya Yakovlev,Andrew Cheung,Binoy Dash,Simran Jumani,Dmitriy Meyerzon,Mark Breitenbach,Ishan Mishra,Kazuaki Okumura
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