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Capture the phased owner-to-AI audit wedge (promise, verify, dual scores, self-serve loop, demand, graph-as-Northstar) so it is durable on a branch off planning-rev2.
2026-10-01 09:15:49 -07:00

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Self-serve “Am I discoverable by AI?” — execution plan

Branch: planning-selfserve-audit (from planning-rev2)
Status: Working draft — captured from strategy conversation 2026-10-01
Scope: Ideas, concepts, and strategic direction turned into actionable phases. Not an artifact inventory from the old tree.

Related durable context lives in BUSINESS_PLAN.md. This file is the methodical build plan for the self-serve audit wedge.


Strategic spine

  • Spine: Agent-era local SMB discoverability.
  • Pipes: MCP (or other transports) are implementation choices, not the product.
  • Northstar (not v1): An industry-wide graph others can use. Do not block v1 on the graph.
  • v1 wedge: A self-service check where a business owner asks: “Is my business discoverable by AI?”
  • Channel: Flexible — standalone web portal and/or inside a business’s own chatbot. One audit engine; shells can differ.
  • Positioning: As much business-owner-to-AI as possible. Human-in-the-loop exists but will not scale — design must minimize human dependency.
  • Demand: Advertising (and similar) drives small businesses to the portal for self-initiated audits.

Owner flow (target experience)

  1. Initiate — Owner (or their AI / trusted helper) starts the check on the outcome promise, not on plumbing.
  2. Stakeholder verify — Prove they are a stakeholder in the business (e.g. six-digit code to a known email on file). Unverified users do not get the deep audit.
  3. Deep audit — Goes beyond NAP consistency across major providers to categorical information and relevance.
  4. Dual outcome — A holistic picture of:
    • Presence: Are they on the map?
    • Recommendability: If they are, would an AI engine likely recommend them when someone asks about something in their genre?
  5. Self-serve next steps — Plain-language findings and ranked DIY fixes; optional re-check. Human expert path is an escape hatch, not the default.

Phases (sequence)

Phase 0 — Lock the promise

  • One-sentence value prop owners understand without jargon.
  • First wedge genre (who we speak to first).
  • Plain-language definition of “recommendable.”
  • v1 shell decision: web, chatbot embed, or both sharing one engine.

Success: The promise can be said in one breath without naming a transport (MCP, etc.).

Phase 1 — Trust gate

  • Claim-a-business + stakeholder verification (email code first; other signals later).
  • Minimal PII, clear consent, rate limits / abuse controls.

Success: Verified owners reach the audit; unverified cannot.

Phase 2 — Audit engine (the product)

  • Presence score: On the map across major providers + category consistency.
  • Recommendability score: Likelihood an AI would surface them for genre-relevant queries.
  • Start with a thin, explainable rubric — not a black box.
  • Outputs: plain-language findings + ranked owner-actionable fixes.

Success: Same business twice ≈ same scores; owner understands why.

Phase 3 — Self-serve loop

  • Results page / chat readback, fix checklist, optional re-check.
  • No mandatory human review.
  • Optional “ask an expert” as escape hatch only.

Success: Majority complete without human touch.

Phase 4 — Demand

  • Lightweight campaigns that send SMBs to the portal for a self-initiated audit.
  • Funnel metrics: start → verify → complete → recheck.

Success: Acquisition cost and completion rate are known; creative/genre can iterate.

Phase 5 — Toward the graph (later)

  • Only after audits produce structured, consented business truth worth composing.
  • Graph remains Northstar; does not gate v1.

Build order (what ships first)

  1. Promise + wedge genre
  2. Verify gate
  3. Presence score
  4. Recommendability score
  5. Self-serve results / fixes
  6. Recheck
  7. Then ads / demand programs

Do not wait on the industry graph or a single wire protocol.


Open decisions

  • First v1 genre
  • Web vs chatbot shell (or both)
  • Which providers feed “on the map”
  • How “would AI recommend” is measured without overclaiming
  • Source of “email on file” for verify
  • Free vs paid audit
  • What never goes to a human

v1 success bar

  • Owner can finish alone
  • Two clear scores with explainable why
  • Actionable DIY fixes
  • Repeatable recheck
  • Ads can point at it without a sales call

Workstreams (parallel once Phase 0 is clear)

Workstream Owns
Promise & wedge Positioning, genre, “recommendable” language
Trust & verify Claim flow, codes, consent, abuse
Presence engine Provider coverage, NAP + category checks
Recommendability engine Rubric, explainability, genre relevance
Experience shell Web and/or chatbot UX on one engine
Growth Campaigns, funnel metrics
Graph (later) Composition of consented structured truth

Capture note

Drafted in conversation 2026-10-01; written here so the plan is durable and not call-only. Revise in place as Ty locks decisions.