- Lead the roadmap and strategy for your product area, from problem discovery through delivery and post-launch iteration
- Lead the evaluation bar for the model-powered surfaces you're responsible for: define eval sets, identify failure modes, and know the rollback plan before a change ships
- Prototype product ideas directly using your own understanding of model strengths and weaknesses, and ship small, production-quality AI features yourself when that's the fastest path to learning
- Lead product decisions about agent autonomy: what the agent should be trusted to decide and act on independently, what needs a human in the loop, and how that line should move as trust in the system grows
- Treat prompting and context design as a product lever you use directly to shape behavior
- Partner with engineers on technical architecture with enough depth to challenge assumptions, propose alternatives, and influence design decisions
- Partner with Design and Research on UX so features are genuinely usable and understandable, not just technically correct
- Partner with Sales, Marketing, and Customer Success around releases — shaping GTM messaging, training, and rollout, and closing the loop on adoption signal afterward
- Track the metrics that actually matter for a non-deterministic system — quality/accuracy distribution, latency, cost-per-task — alongside the usual adoption and growth metrics
Artificial IntelligenceProduct ManagementPrototyping+1 more