This project derives from consumer-experience-kernel A-3 (the Experiential Delta is the only defensible metric — must change purchase outcome) and A-8 (Trust Architects validate what LLMs cannot self-verify). It directly serves the chat-expert outcome (currently at-risk: zero return-rate data, zero conversational-grounding categories). The chat-expert evidence criterion requires recommendation-acceptance ≥25% across 3+ categories; you cannot move that number if you cannot see whether non-acceptance is "user found a better answer elsewhere" or "user accepted but verified externally first." The instrumentation forged here becomes the empirical floor under every Phase 1 axiom decision and every Trust Architect calibration. Without it, the Beige Singularity argument collapses to marketing copy.
productai-web (chat surface): define the events to instrument (verdict shown, user acted, user opened external tab, user copied text, user returned, session ended). Coordinate with the engineer who owns the chat surface (currently Phil Larsen on Mobile, but chat-island lead on web — confirm Day 1).aios/dashboard/: add the Behavioral Verification tile to the chat-expert outcome page. Coordinate with the dashboard architect.aios/outcomes/chat-expert.md: propose evidence-criterion update reflecting the new instrument; route via /outcomes if six-test gate passes after edit.A stranger reads the shipped instrumentation spec, opens the chat-expert outcome dashboard, sees a "Behavioral Verification Rate" tile populated with last-30-days data segmented by category and verdict structure, clicks into a session-level view that shows for each chat session whether the user (a) accepted, (b) accepted-and-verified-elsewhere, (c) rejected, or (d) abandoned — and the latency between those states. The stranger can answer "do users behaviorally trust the chat in skincare versus tech?" without asking anyone on the team. The instrumentation is opt-in and respects the kernel's privacy-first commitment (productai-kernel A-7) — no user data leaves the closed loop. The five-element verdict (kernel A-7) is the unit of measurement; verification correlation is computed against verdict structure, not against UX surface.
The robust solution may surface a better cut: maybe the right unit isn't "verification rate" but "abandonment after-which-second-tool" or "trust-closure latency." The candidate is invited to propose. What is non-negotiable: a working instrument by trial end, a baseline measurement on at least one Beat 1 category, and a written spec the chat team can extend.
aios/kernels/consumer-experience-kernel.md (A-3 Experiential Delta, A-5 Calibrated Verdict / Confident No ratio, A-7 five-element verdict, A-8 Trust Architects)aios/kernels/truth-graph-kernel.md (A-7 Glass Box, the 4-tier signal taxonomy, confidence-decay physics)aios/kernels/productai-kernel.md (A-6 Radical Explainability, A-7 Privacy-First Economics, A-9 Knowledge Boundary L1-L4)aios/outcomes/chat-expert.md (currently at-risk — this project unblocks measurement)axioms/Frontier-Practice-2026/data-science-state-of-practice-2026.md (behavioral analytics, experimentation methodology). axioms/Frontier-Practice-2026/product-management-state-of-practice-2026.md (research methodology + JTBD).aios/drivers/operations/recruiting-driver.md §5.1 three-criteria gate.
aios-methods access — the instrument cannot depend on ARC Autopilot infrastructure.---
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The operating principles we work by. If they resonate, the rest of this will land. Open the Codex →
Hireflix, async. Questions are calibrated to this project specifically.
Direct call with the CEO. Strategic alignment and mutual fit. No problem-solving exercise.
1099 contractor agreement, NDA, paid at your stated rate. Day 1 in Santa Monica.