Applied AI Handoff Atlas

A field-evidence companion to the Extended Capability Library: Curiosity Builds read as small handoffs of judgment, memory, practice, access, and representation into AI-shaped systems.

This is Daniel's own field-evidence bridge between Hypandra Curiosity Builds and the Extended Capability Library. It turns small builds into claim-bearing notes about what extends applied AI capability in practice.

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The Handoff Atlas reads Hypandra Curiosity Builds as evidence for the library's central argument: AI capability in practice is extended by the surrounding scaffolding, not contained inside the model alone. The unit of analysis is the handoff. A handoff is a small transfer of work into a system: judgment, memory, access control, practice, explanation, or representation. The atlas asks what moved, what evidence supports that claim, what broke, and which reusable lesson another applied AI team should carry forward. Why it belongs in the library Most entries in the library are external sources: papers, practitioner essays, framework posts, and vendor announcements. This note supplies a different kind of source: a field notebook from building small AI systems with actual users, families, teachers, clients, and archive stewards. That matters because the corpus has an explicit evidence gap around repair loops in action and non-software operational settings. The builds do not close that gap completely, but they make it more concrete: • Pronouncle shows how the wrong measurement instrument can invalidate a product claim. • Scheduler Mark shows why model-vs-model critique is not evaluation without ground truth or a rubric. • HighSchoolResumes shows transparency as an interface users can inspect, not merely a disclosure page. • Bunny Biscuits shows intentional friction and local data boundaries as part of the AI design. • Zanna Smith Archive / MelTemp shows representation boundaries as product requirements in memory-sensitive domains. Read alongside • Rubrics as Rewards - diagnostic feedback and named failure modes. • Wallach/Jacobs et al., "Social Science Measurement Challenge" - why evaluation is a construct-validity problem. • Good and Bad Harness Engineering - the distinction between scaffolding that extends capability and scaffolding that merely compensates for model weakness. • Resurrecting deceased darlings - human agency, disclosure, and editorial ratification in AI-assisted knowledge work.