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Roles are expanding, and it depends on the phase
Atlassian CPO Tamar Yehoshua says the PM's job hasn't changed: find product-market fit and build a business people will pay for. What has changed is how the work gets done . Atlassian ran experiments on whether PMs should "row" (write code) or "steer." Her answer is that it depends on the type of product and its phase . She gave three examples:
- New feature in an existing codebase (Confluence): A PM who had never coded used a harness built by an engineer and checked in 26 PRs in a month, mostly UX fixes . The team used Figma MCP and a coding agent to fix about 14 design bugs an hour. Test creation dropped from half a day to 10 minutes . Yehoshua says work that took about 6 months before AI now took 6 weeks .
- New product (Rovoclaw): A PM and a designer vibe-coded a working alpha. Once engineers joined, the PM stopped coding and went back to setting direction and unblocking. The early coding had helped him understand the team's blockers .
- Large legacy codebase (Jira): PMs did not check in production code . Loom recordings became work items that started a cloud coding agent. That produced prototypes in the real front-end repo that already met compliance and design standards . An agent triaged more than 900 pieces of customer feedback . The team shipped 22 user-facing features in about 10 weeks, at about 3x normal throughput .
Atlassian's AI Fluency Index covers six capabilities on a 1–5 scale. It's used for development, not promotion, and the goal is for PMs to reach level 3 in every capability over time . Yehoshua admits they haven't figured out how to measure outcomes. For now they track PRs deployed rather than PRs written, features delivered and used, and throughput for teams and the whole organization .
High-impact ICs need a different org design
Elena Verna of Lovable defines a high-impact IC as someone who finds a problem, decides, executes across functions, ships, and owns the result . Her rule: "When the cost of building falls below the cost of coordinating, the org chart should change" . She lists what an organization needs for this to work:
- Open access to information and fewer management layers
- Authority that comes with accountability, and room to fail. She says her failed experiments have cost Lovable many millions of dollars
- Pay and status that don't depend on headcount
She warns against expecting people to be a manager and an IC at the same time .
Decision-making is now the core PM skill
Robby Stein, head of Google Search, argues that when almost anything can be built, a PM's value comes from judgment and taste, and above all from making decisions . His examples of finding the root cause:
- Instagram Stories: When the team asked why people weren't posting, audience worries came out on top. A survey of thousands confirmed it, and Close Friends only worked once it lived inside Stories .
- Reels in Brazil: The first version disappeared after a day and failed, because creators wanted their posts to last .
Outcomes, not prototype volume
Marty Cagan says that about two years ago, product teams typically had five to eight engineers. Some advanced teams now have one to three, and he considers the growth in what each team owns the bigger change . Now that anyone can prototype, his test is outcomes, not activity. Good teams throw away about 80–90% of their prototypes . To win leadership over to the product model, he recommends a low-cost pilot team that works on a meaningful problem for one quarter .
Also worth noting
- Share what makes AI work good. Hiten Shah says one person knows how to get strong research out of Claude and another knows the context that makes ChatGPT useful for sales, but "very little of what made them good becomes shared" . He adds that the corrections you make to AI output show how the work should be done next time .
- Label how much you checked AI work. At Zapier, people say at the top how much effort went in, for example "done a quick skim." Accountability is now one of four dimensions on Zapier's rubric .
- AI PM pay. Aakash Gupta cites Levels.fyi data showing median total pay for AI PMs from $325K at Amazon to $860K at OpenAI . His advice when comparing offers: ask which layer of the stack the team works on .
- Consumer agents. Scott Belsky suggests that "human in the loop" could become the key differentiator for consumer agents . He was responding to the launch of Fo, which uses humans for tasks AI can't do and claims a 94% trust rate. Those figures are the company's own .