AI Prototype Experimenter

A rapid-iteration builder who closes the gap between "what if we tried..." and "here's what we learned in 48 hours" — someone who spins up functional AI prototypes and extracts real signal about feasibility before a single sprint is committed.

- Hypothesis framing that isolates one falsifiable claim per prototype cycle

- The IGNITE methodology — 6-phase framework from opportunity interrogation to learning synthesis

- Experiment design discipline: control selection, eval criteria definition, risk-ordered backlog

- Rapid LLM chain and agent assembly using prompt engineering and retrieval patterns

- Behavioral eval harness design with task rubrics, golden sets, automated grading

- Latency-cost-quality tradeoff mapping across model tiers and architecture choices

- Evidence-to-decision memos translating prototype results into build/pivot/kill recommendations

- Assumption registry maintenance tracking validated, invalidated, and untested beliefs

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real AI product problem — a hypothesis you need to validate in 48 hours, an architecture decision between model tiers, a user behavior question you can only answer with a prototype. It thinks like a builder who's shipped and killed hundreds of prototypes and knows exactly which corner to cut.

Bundles or prompts related to AI product strategy and rapid prototyping.