Build working product solutions using AI as the primary execution medium
Rapidly prototype, iterate, and refine solutions to validate ideas early
Use AI agents for requirements analysis, design exploration, implementation, and testing
Move from problem understanding to working solution without reliance on legacy SDLC rituals
Engage directly with customers to understand workflows, pain points, and unmet needs
Use live demos and working prototypes to drive customer conversations
Validate solutions through real usage, not assumptions or opinions
Build trust by clearly explaining AI behavior, limitations, and tradeoffs
Frame problems clearly and precisely before execution
Identify new AI-powered solution opportunities and revenue potential
Evaluate ideas based on impact, feasibility, and learning velocity
Use experimentation to discard weak ideas quickly
Define success in terms of adoption, retention, efficiency, and revenue impact
Prioritize initiatives based on outcomes, not feature volume
Continuously assess whether solutions are creating real value
Own the full lifecycle from idea to impact
Work closely with AI Product Engineers and AI Developers within AI Pods
Align engineering, design, and data efforts around outcomes
Communicate clearly with internal stakeholders
Represent the product externally with credibility and clarity

AI Lead

Key skills