Adaptive AI Lab · Playbook v0.1.1

The Adaptive AI Systems Playbook, built for deep reading.

An evidence-driven, project-independent methodology for designing, evaluating, optimizing, deploying, and continuously improving AI systems. Every rule carries its evidence and how strong that evidence is — including the rules that rest only on reasoning.

Start with the Quickstart Browse the book See the lifecycle map

What the playbook answers

For a concrete project: what should I do next, why, what evidence do I need, what should I measure, what can I skip, what should force me to stop — and when is an expensive intervention justified?

The bookChapters 00–14: principles, evaluation, experiment design, selection, optimization, economics, deployment, governance.Glossary101 defined terms with hover definitions across the whole site — the fastest way into the methodology's vocabulary.TemplatesNine working artifacts, from the project profile to experiment contracts and the three ledgers.ScenariosTwelve worked scenarios, ten compact examples, and one full walkthrough — every one invented, each built around a mistake that is easy to make.Source ledgerEvery cited source with a verdict (FOLLOW / ADAPT / REFERENCE / DEPRECATED), strength, and verification date.ChangelogRelease history, with the evidence behind each rule change.

How a rule gets in here

Nothing becomes a rule because it sounds right. A claim starts as evidence, gets a strength label saying how far it can be pushed, and only then becomes something the book tells you to do. Scenarios illustrate the rules; they are never the evidence for them.