An AI governance product and operating archive built around BECAUSE-grounded elicitation, provenance-first schema, eval-driven development, and reusable Claude skill infrastructure.
FieldRules is designed so claims about trust, judgment, and AI governance become inspectable. The interface, schema, evaluation loop, and artifact archive all point at the same thing: human reasoning has to stay structurally present before agents can reuse it.
The strongest FieldRules proof is not a single polished screen. It is the connected system of strategy, schema, Notion and Obsidian knowledge work, pilot scripts, quality judges, Jira snapshots, design-system updates, automated component test scripting, seed-library generation, and recurring coherence checks. The seed-library-generator took a two-hour setup task down to roughly 18 seconds by intaking a company or domain, running discovery, proposing categories, and producing reviewable IF/THEN rule candidates with provenance. Component work also moved into an automated quality loop with Storybook updates, annotation refreshes, parity checks, drift reports, PR summaries, and follow-up tickets.
This Obsidian graph capture shows the FieldRules operating archive as a living knowledge system: strategy, product surfaces, schema, evals, pilot rituals, skills, Jira snapshots, and decision logs building relationships over time. It is a visual proof of the AI-native process behind the product: not scattered notes, but a connected body of knowledge agents and humans can reason from.