AI Product Strategy

Scope

Covers

• Defining an executable product strategy for an AI/LLM/agent product or AI feature portfolio
• Translating AI uncertainty (non-determinism, emergent risks) into an empirical plan with evals + instrumentation
• Choosing product form factor (assistant vs copilot vs agent), autonomy boundaries, and a safety/security posture
• Setting kill criteria so you know when to pivot or stop investing
• Producing a strategy pack leaders and teams can use to align and execute

When to use

• "Define our AI product strategy / LLM strategy / agent strategy."
• "Prioritize AI use cases and turn them into an AI roadmap."
• "We're adding AI to an existing product—what should we build and how do we measure it?"
• "We want to ship an agent; define autonomy, security, and rollout."
• "Should we keep investing in our AI feature, or kill it?"

When NOT to use