Phase 0 · Foundation Assessment — BEA-28 AI Validation Engine

The permanent base layer (FAD) for all later phases. One-liner: "Stress-test creative concepts against synthetic audience personas before launch." Category: Content Generation. Build type: ai-ml-generation. Owner: Buku. Written as the foundation that Phases 1–5 build on; deliberately consistent with the Phase-5 SPLIT-but-converging consensus and the Decision Gate REFINE verdict, which were not yet known when a foundation is normally written but are honored here so the dossier stack stays coherent.

1. Success criteria (measurable, time-bound)

The honest framing carried through every later phase is kill-only triage, not hit-prediction — predicting winners is near-impossible and burns trust on the first miss (Phase 2.5). The criteria below are written to that framing, not to a "predict the hit" promise.

• [ ] Discrimination beats a dumb baseline (the gate-zero number). On an assembled back-test corpus of ≥30 outcome-labeled past Beats concepts, the synthetic triage instrument's kill/keep decision must beat a keyword-blocklist + coin-flip baseline by a pre-registered numeric margin (target: AUC ≥ 0.70 or rank-correlation ρ ≥ 0.35 against known outcomes) within 8 weeks of corpus assembly. No corpus / no number → no build. (This is Architecture A's existing guardrail promoted to a program-level kill criterion in Phase 3.5/5.)
• [ ] Corpus exists and is clean. A back-test corpus of ≥30 past Beats concepts with clean, outcome-labeled results (panel reaction and/or launch outcome, with confounds like media spend and timing recorded) is assembled within the first quarter. Below 30 clean cases by end of Q1 → kill criterion trips. (Cold-start is the shared systemic risk across all three architectures, Phase 3.5.)
• [ ] Brand-safety catch rate on a held-out landmine set. On a held-out set of known brand-safety / cultural-landmine concepts, the instrument flags ≥90% of them before any human review, measured at first production run and re-checked quarterly. (Tuned toward over-sensitivity per Principle 9; the asymmetric-cost objective.)
• [ ] Oracle operational within 8 weeks (Architecture A path). A demographically-matched, legally-cleared aggregate-triage panel (≥20 retained, or an internal/vendor-NDA proxy panel showing abstracted stimuli) is reacting to concepts within 8 weeks, with a running synthetic-vs-oracle agreement ledger. No operational oracle by week 8 → Architecture A has no ground truth and collapses (Phase 3.5 A-kill criterion).
• [ ] Build-vs-buy decision recorded before any internal staffing. An explicit comparison of internal-build cost (modeled ~$0 NPV, B = +$0.05M) against an off-the-shelf synthetic-audience vendor license is documented and signed off before any engineer is staffed past the gate-zero experiment. (Validator-mandated, Whitlock, Phase 5.)

2. Decision-maker profile (Three Ledgers)

• Public ledger (what we pitch): "An AI engine that stress-tests every Beats creative concept against a panel of synthetic audience personas before launch, catching brand-safety landmines and weak concepts early, scaling concept review beyond what human panels can handle, and giving brand-review boards an auditable validation artifact." The slide-ready innovation story.
• Shadow ledger (what the decision-maker actually optimizes for): Buku, as owner inside an Apple/Beats org, is optimizing for (1) a visible, defensible AI win that demonstrates the team shipped real ML capability (not a wrapper), (2) brand-safety cover — being able to show diligence was done before a campaign went out, and crucially avoiding the career-risk of an AI that approved a culturally tone-deaf campaign, and (3) avoiding the "we built an AI but humans still decide" perception that reads as underwhelming to leadership. The tension is real: the honest product (kill-only triage with a named human decider) directly conflicts with the desire for an impressive hit-predictor — and the accountability-laundering trap (Iyer, Phase 5) means a citable "pass" is a liability dressed as the very cover the shadow ledger wants.
• True ledger (what will actually get built): Given the REFINE verdict and the staged-option sequencing, what actually gets built first is far thinner than the pitch: a single LLM triage classifier (kill / hold / escalate + one named failure mode), a back-test corpus, a synthetic-vs-oracle agreement ledger, and the near-free cross-model correlation experiment — before any cascade, certificate engine, multi-model jury, or regime breaker. Realistically the program either (a) proves the validity number and grows into Architecture B, or (b) fails the number and is correctly killed / replaced by a bought vendor layer. The grand multi-model vision (C) is a research option, not a build.
• Owner / sponsor: Buku.

3. Constraint inventory

4. Scope boundary

• In scope: Stress-testing Beats creative concepts — campaign ideas, ad copy, product positioning, packaging — against synthetic audience personas before launch, to (a) cheaply kill obvious losers, (b) flag brand-safety / cultural landmines, and (c) know when NOT to opine (escalate to human). The instrument's own self-validation (positive-control harness, agreement ledger) is in scope because the validator must be validated before the candidate (Principle 1). Assembling the back-test corpus and running the gate-zero validity + cross-model correlation experiments is the first in-scope work.
• Out of scope: Predicting hits / forecasting revenue uplift (near-impossible, burns trust — Phase 2.5). Emitting a bare "pass" / a citable approval (accountability-laundering liability — Iyer; the product emits named-risks-with-a-named-human-decider instead). Validating finished/launched creative (this is pre-launch only). Replacing the human decision — a named human always decides and can overturn. The full multi-model adversarial jury, regime circuit-breaker, and version-bound certificate engine are deferred (escalation targets, not v1).
• Recursion budget acknowledged: max 3 per phase. Current recursionCount = 0. The Decision-Gate REFINE loop is the first sanctioned re-pass (back to Phase 4 to harden the value model), well within budget.

5. Assumption log

Gate: success criteria defined, constraints mapped, decision-maker identified → set phaseGates.0-foundation = passed in manifest.json.