Product Builder
Open a video or resource link, watch it, then check its box to track your progress and unlock what comes next.
- Find a painful problem, shape the product and prototype an experience people can actually use
- Build the product end to end and add AI capabilities through clean, evolvable interfaces
- Instrument quality, learn from real users and operate a reliable product through production rollout
Benchmark: OpenAI Enterprise Verticals + Anthropic Staff Software Engineer, Product (current Sep 2026) Market refresh: customer evidence, product judgment, UX craft, modern full-stack build, AI integrations, measurable quality, safe rollout, reliability and retained usage.
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Find a painful problem, shape the product and prototype an experience people can actually use
Customer discovery + product judgment
Coverage: Product Discovery & Customer Research / Design Thinking
UX prototyping + interaction quality
Coverage: UI/UX Design / Prototyping / Usability
Build the product end to end and add AI capabilities through clean, evolvable interfaces
Modern full-stack product engineering
Coverage: React / TypeScript / Full-Stack Development / APIs / Databases
AI agents, tools + product integrations
Coverage: Generative AI / AI Agents / MCP / APIs
Instrument quality, learn from real users and operate a reliable product through production rollout
Product metrics, experiments + retained usage
Coverage: Product Analytics & Growth / Experimentation / Product Metrics
Production quality, evals + reliability
Coverage: AI Evaluation / Observability & SRE / Launch Readiness
Role-Readiness Proof / Capstone
Take one real customer problem from evidence to a bounded production launch. Conduct user interviews, write the problem/value hypothesis and success metrics, prototype and usability-test the experience, then build a responsive full-stack product with React/Next.js + TypeScript, backend APIs and persistent data. Add one useful AI agent/tool workflow, instrument product and AI-quality metrics, create an eval/regression set, define permissions/privacy controls, deploy with observability and SLOs, use a staged rollout with fallback/rollback, run one experiment, and use adoption/retention evidence to drive the next iteration.
Proof Rubric
- Show customer evidence rather than invented requirements
- defend scope, UX and architecture tradeoffs
- ship working frontend/backend/API/data flows
- demonstrate reliable AI/tool integration with evals
- measure usability, latency, quality, cost and retained usage
- test safely before broad rollout
- diagnose one production failure from telemetry
- and show that feedback, experiments and real usage changed the product rather than merely validating the original idea