A small AI lab in public. Notes, tools, and experiments.

Most AI work lives under uncertainty. Treat it like a first-class constraint: state assumptions, bound risk, and iterate in tight loops. Progress becomes legible, and failure gets cheaper.

Assumptions, stated

Write down what must be true for your approach to work: data freshness, model latency, budget limits. This anchors debate and avoids hidden constraints.

Bound the risk

Contain blast radius. Start with low-stakes tasks, guardrails, and human review. Expand as evidence accumulates.

Iterate in tight loops

Weekly changes beat quarterly “big bangs.” Ship small improvements, measure, and keep a changelog.

Examples

Checklist

References