LLM bootcamp + design sprint

Who it is for

• PMs, designers, and engineers building AI features together
• Teams starting from zero and needing a practical baseline fast
• Teams with prototypes who want a path to production quality

What we cover

The goal is fluency and good judgment, not prompt tricks.

• LLM fundamentals (capabilities, failure modes, and constraints)
• Product patterns: copilots, agents, RAG, and workflow automation
• Evaluation and quality: what to measure and how to test
• Reliability: latency, cost, fallbacks, and monitoring
• Safety and policy: guardrails, data handling, and review paths

Sprint outputs

• Prototype concepts from the sprint (UI, flows, or lightweight demos)
• Evaluation criteria and what good looks like
• Next experiments plus an execution plan
• Risks, dependencies, and a path from prototype to production

Inputs and prep

• A short context doc: users, workflows, goals, constraints
• Sample data (redacted if needed) and policy requirements
• Known edge cases and existing quality issues
• Stakeholders who can make decisions during the sprint

Format

1. Bootcamp: shared baseline and vocabulary
2. Sprint: generate concepts, pick winners, and prototype
3. Review: evaluation plan, risks, and next steps