Supabase
Technology
ProductManager-AI
Neural analysis suggests this role is
optimal for Senior candidates.
“Product Manager - AI at Supabase. Skills: Product management, Developer tools, AI coding tools. Rethink PM job for agents. Apply agent lens to roadmap”
What You'll Achieve.
Move to judgment calls; Ship imperfect and learn
Industry & Context.
Judgment calls
What They're Looking For.
Must Have
7+ years product management experience, Technical enough to dive in, Shipped something that put opinions to test, Use products on your roadmap
Nice to Have
Ex-founder with product instincts, Clear point of view on agent-friendly infrastructure, Biased toward speed, Use AI to move faster, Work async by default
What You'll Do.
Rethink PM job for agents
Apply agent lens to roadmap
Own problem statement
Decide what gets built
Define how launch measured
Set metric before engineering
Track metric movement
Keep stakeholders pointed
How You'll Work.
Team & Collaboration
Cross-functional collaboration; Engineering alignment; Design alignment; Leadership alignment
Process & Methodology
Roadmap
Full Job Description
ABOUT THE ROLE: Supabase is the backend more than 7 million registered developers reach for when they want to ship fast: database, auth, storage, and APIs in one platform. AI coding assistants now account for a meaningful share of the development happening on Supabase: agents writing migrations, provisioning infrastructure, and querying databases through the MCP server https://supabase.com/docs/guides/ai-tools/mcp and agent skills https://supabase.com/docs/guides/ai-tools/ai-skills. When agents have the wrong context or defaults, the result is a broken schema or a misconfigured policy. Getting the abstractions right is the whole job. You own the MCP server, agent skills, and the evals that tell you whether any of it is working. WHAT YOU'LL BE RESPONSIBLE FOR: - Rethink the PM job when most users are agents. Defaults, error messages, breaking changes, naming, deprecations, docs: every product decision behaves differently when an AI coding tool sees it before a human does. Apply that lens to your own roadmap and to product decisions across Supabase. - Talk to customers across the full spectrum. Indie developers shipping side projects, startups choosing an AI stack, enterprise teams running agents in production. Find the blockers and bring them back to the roadmap. - Own the problem statement and requirements behind every agent tooling bet. Define what we're building and why before engineering picks up a spec. Capture the evidence behind each decision, name the constraints, and give the team a target it can hit. - Decide what gets built, what gets deferred, and what gets cut. Every quarter you're choosing between agent plugin requests, MCP improvements, discoverability work, and reliability — and defending those calls when stakeholders push back. - Define how each launch is measured before it ships. Set the metric before engineering starts: developer activation, task completion, and AI eval scores. Track whether it moved after launch and use that to sharpen the next ca
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