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The PM job market: fewer hires, higher pay, a different set of employers
Aakash Gupta, working with Live Data Technologies and Levels.fyi, looked at actual offers and hires, not job postings . TrueUp shows postings up 77%, but real hires from February to June were 18% below 2023 . Companies hired 0.92 outside PMs for every PM who left in 2025, down from 1.16 in 2022 . US PM hiring is at 52% of its 2022 level, but median US pay rose from $220K to $250K. Gupta says part of that comes from a shift in level mix .
The employer mix is changing. Capital One (486 hires), JPMorgan Chase (404), Mastercard (339) and Visa (217) are among the 10 biggest PM hirers . Over the last year, hiring fell 31% at Microsoft, 30% at Meta and 21% at Amazon. It rose 55% at Mastercard, 32% at Visa and 17% at JPMorgan . AI PM hires grew from 789 to 1,988 over the same February–June window while total PM hires fell from 52,664 to 29,223 . Still, the AI PM title makes up only about 7% of hires .
Gupta also tracks the shift toward "product builders." LinkedIn renamed its APM program the Associate Product Builder program in fall 2025 . At Laurel, the whole PM and design org is nine people, and senior PMs ship features to production . At Freshworks, AI-native teams have gone from one PM per 10–20 engineers to close to one-to-one. PMs focus on what users need, and engineers own the backend, infrastructure and DevOps . Gupta says roles and ratios are still unclear and specialists still have a place .
Evals are product work
Teresa Torres and Kathy Pham made similar points this week. Torres says an eval suite should measure technology performance, customer value and business value, and teams should define "good" for their own context rather than rely on off-the-shelf evals . A concise answer can be right for an expert and wrong for a beginner. Metrics mature from universal measures like MAU toward a product's real value moment, such as DocuSign getting you to send a document . Her warning: AI amplifies whatever shape you're already in .
At MTP Chicago, Pham said PRDs and prototypes now take minutes, which also "makes building the wrong thing cheaper" . Her four pillars are: solve the right problem, make evals the new acceptance criteria, treat trust as a feature, and orchestrate teams through the change . Old acceptance tests checked whether a user could submit or buy something. AI outputs need checks on whether the answer is actually right, often with input from domain experts . She also says not to take ignored patterns like EHR alert fatigue and make them faster with AI .
AI-written PRDs divide PMs and engineers
On r/ProductManagement, one commenter called AI-written, "grilled" specs from spec-driven toolkits far better than human-written ones . Others called them unedited "slop" and said they don't replace talking to customers . A useful test came out of the thread: if writing a document takes less time than reading and absorbing it, "it's almost guaranteed to be slop," whether or not AI wrote it . A separate post lists checks against bad AI-assisted decisions: read raw feedback weekly, treat every AI output as a draft, and give one reviewer the job of asking "what is this missing?" .
When product leaders own revenue
Run the Business looks at the gap between GTM teams held to quarterly results and product teams working on multi-year horizons . On roadmap commitments, the advice is to lean in: have sales rank its own one-off requests, and pre-agree with the CRO and CCO on size limits, how commitments are written into contracts, and an audit trail . When GTM asks for new products, push back. The real need is often a reason to talk to customers, or more jobs to be done covered within existing products .
Launches and signals
- Hex 4.0 rebuilt Hex as an analytics platform "built for agents," alongside a $100M raise at a $1.2B valuation .
- Stripe pay offers free, instant B2B transfers by Stripe handle . Patrick Collison: "A2A payments will be more important than P2P" .
- Notion Agent can now use a computer to produce Excel, Word, PowerPoint and PDF files .
- Daffy has an MCP server that lets Claude or ChatGPT answer questions about a user's giving and make donations. Adam Nash argues services should be designed for actions taken by AI agents, not only clicks and calls .
- Andrew Chen questions the solo-founder thesis: maybe "coding was never the main bottleneck," and a demo is far from a product that can scale .
- Hiten Shah rewrote his early access playbook around the decision you're making. His new final test asks whether users choose your product again the next time they need to do the job .