Discover & define. Talk to users, understand real workflows, identify pain points, and convert ambiguous asks into transparent problem statements and requirements.

Shape solutions. Write crisp PRDs, user stories, acceptance criteria, workflows, edge cases, and MVP scopes. Partner closely with UI/UX.

Prioritize. Maintain the backlog and recommend priorities using user impact, business impact, effort, urgency, and strategic value.

Drive delivery. Work with engineering through development, clarify decisions, review builds, test workflows, and ensure release readiness.

Own adoption. Plan launches, demos, training, release communication, and follow-up improvements to drive user adoption.

Measure & improve. Track usage and adoption, identify drop-offs or friction, and translate data and feedback into product improvements.

AI-first product thinking.



Use AI tools and LLM APIs throughout discovery and delivery to test ideas quickly, improve workflows, and identify high-value AI product opportunities.

AI PRDs. Define expected model behavior, inputs/outputs, guardrails, fallbacks, edge cases, success metrics, and human-in-the-loop requirements for AI features.

AI prototyping. Build fast proofs of concept using LLMs, agents, APIs, no-code/low-code tools, and AI-assisted coding before committing significant engineering effort.

AI evals. Create representative test cases and evaluation criteria for quality, relevance, reliability, latency, cost, and failure modes; use results to iterate before and after launch.

📌 Product Manager (Mumbai)
🏢 Flipspaces
📍 Mumbai