ProductMap AI

ProductMap AI ships agents grouped by purpose: nine for PM tasks, three for early-stage startup guidance, and fourteen for personal growth. Each agent carries its own prompt, memory, and scoped knowledge files, and can spawn sub-agents for specialised work. Different agents can run on different language models, which lets research, drafting, and scoring each use the model that fits.

You describe your product, users, goals, stage, and constraints once, and every agent draws on that shared context. Pro plans add version-controlled context, which matters when your product shifts and you need to trace what changed. Precise context is what lets agents act without step-by-step instructions.

ProductMap AI organises work through TASK: Topics, Agents, Skills, and Knowledge. Topics define the operating space, agents execute inside them, skills set the human quality bar, and knowledge captures the artifacts. It runs as a continuous loop in which each pass gets faster as accumulated knowledge sharpens the next decision.

An AI assessment reads your experience, from a CV or LinkedIn profile through to certificates, then reports your skill level and gaps. You get a personalised growth plan mapped to the five PM skill areas, and the tool tracks progress as you close each gap.

The catalog covers more than 60 product management topics across five domains: strategy, generation, analysis, delivery, and people. Curated frameworks, guides, and templates sit behind each topic, giving agents domain context and giving you a reference when a task needs a method you don't know yet.

The flow moves from context to a decision checklist to generated artifacts. The tool answers the question most PM tools skip, which is what your product needs to decide right now, then hands you a PRD, research plan, prioritization, or go-to-market strategy rather than another blank page.