Executive summary (read this first)

AI MVPs don’t need to be fragile toys. With the right scope and guardrails, you can launch a useful, safe, and measurable AI app in 8–10 weeks.

This playbook gives you a copy‑and‑paste plan:

• Scope: one persona, one assistant (citations + refusal), one automation (approvals + audit).
• UX: fast acknowledgement, progress milestones, clear hand‑offs to humans.
• Content: clean ingestion → chunking by type → metadata → grounded answers.
• Integrations: connect only the systems needed for the first workflow.
• Governance: per‑tenant isolation, region pinning (AU/US/UK/NZ), PII redaction, usage caps.
• LLMOps: golden tests, canaries, rollback, and dashboards for quality, latency, and cost.
• Commercials: realistic budget bands and a simple go‑to‑market path.

MVP in one page (what you’ll actually ship)

Audience & persona: e.g., Support Manager at a mid‑size eCommerce brand.

Two core features:

1. Assistant that answers questions using your docs and policies, cites sources, and refuses when evidence is thin.
2. Automation (an “agent”) that does one job safely with approvals and audit—e.g., returns triage or invoice draft posting.

Admin:

• SSO + RBAC (Admin/Manager/Agent/Viewer).
• Usage page (answers/tasks this month; caps & alerts).
• Region setting (pin to AU/US/UK/NZ).

Observability:

• Traces for every interaction; dashboards: grounded answer %, refusal correctness %, P95 latency, cost per successful answer/task.

Outcome: measurable time saved, fewer errors, and a short path to paid pilots.

The 8–10 week plan (week‑by‑week)

Weeks 1–2 — Scope & design

• Choose one persona and two use‑cases (assistant + one automation).
• Define acceptance criteria:
  • Grounded answers ≥ 90% on a test set.
  • Refusal correctness ≥ 95%.
  • P95 TTFB ≤ 1.5 s, total ≤ 2.5 s for Q&A.
  • Approval pass rate ≥ 90% on the automation.
  • Cost per successful answer/task tracked weekly.
• Draft workflow for the automation (thresholds for approvals; who approves).
• UX sketches: chat/sidebar patterns, progress milestones, and human hand‑off.

Weeks 3–4 — Content & assistant

• Ingest policies, FAQs, manuals; clean & chunk by type; add metadata (owner, last updated, region, precedence).
• Stand up hybrid retrieval (semantic + metadata + optional keyword).
• Build assistant with citations + refusal; baseline with a golden set of 100 real questions.

Weeks 5–6 — Automation & integrations

• Define tool schema (inputs, validation, idempotency, spend caps).
• Wire one integration (e.g., eCommerce or accounting).
• Implement approvals + audit; dry‑run mode first; then switch on real actions.
• Add SSO and RBAC; set usage caps & alerts.

Weeks 7–8 — LLMOps & hardening

• Traces end‑to‑end; dashboards live.
• Canary prompt/config updates; prove rollback.
• Performance tuning: shorten prompts, cache frequent answers, route simple steps to smaller models.
• Privacy pass: PII redaction, region pinning, deletion flow.

Weeks 9–10 — Beta & go‑live

• Pilot with 10–30 users; monitor quality, speed, cost daily.
• Triage misses; improve content and thresholds.
• Prepare case snapshots and a simple pricing page for paid pilots.

Scope it so you win (how to avoid bloat)

• One persona, two jobs‑to‑be‑done. Anything more slows you down.
• Assistant and one automation only. The assistant teaches you content gaps; the automation proves ROI.
• Integrations: choose the single source of truth for the automation (not five systems).
• Language: start in one language; add others later.
• Mobile/web: pick the primary channel your users live in (helpdesk sidebar, portal, or website widget).

UX patterns that build trust (copy these)

• Fast acknowledgement: “Reviewing policy & your order…” (≤ 1.0 s).
• Milestones: “Found policy v3 → Verified order → Drafted return.”
• Citations inline: “Returns Policy v3, §4.2 (updated 1 June 2025).”
• Refusal that helps: “Not enough evidence; I need your order number or this form.”
• Approvals: banner with amount, reason, and one‑click approve/decline.
• Human hand‑off: make “Talk to a person” a first‑class action; pass the transcript.

Content: the hidden MVP accelerator

Most delays are content, not code. Do this once; it pays back:

• Structure: clear headings, short paragraphs, one idea per section.
• Type‑specific chunking: FAQs (80–180 tokens), policies (220–380), manuals (350–700).
• Metadata: owner, last updated, region, product/version, precedence (Contract > Policy > FAQ).
• Tables → statements: “Pro plan in AU includes…” so the model can cite properly.
• Retire stale docs or mark lower precedence.

Clean inputs = fewer hallucinations, shorter prompts, lower cost.

The automation (agent) — make one job boringly reliable

Example: Returns triage

• Inputs: order ID/email; reason; condition.
• Rules: region; window; product class; thresholds (≤ A$250 auto‑approve).
• Tool schema: start_return, create_label, issue_refund_draft (with idempotency keys).
• Approvals: manager for > A$250, finance for > A$1,000.
• Audit: trace includes inputs (sanitised), citations, decisions, approvals, outputs.
• KPIs: success %, approval pass %, P95 latency, cost per successful task.

Build it with guardrails and you’ll trust it quickly.

Budget ranges & run costs (planning‑grade)

• Assistant (citations + refusal): A$20k–A$60k (US$15k–US$40k / £12k–£32k / NZ$24k–NZ$65k).
• One automation (approvals + audit): A$40k–A$120k (US$25k–US$80k / £20k–£63k / NZ$48k–NZ$130k).
• Run costs: start in the hundreds per month; scale predictably with caps, caching, and routing to smaller models for simple steps.

Napkin ROI: Annual value=hours saved/week/user×rate×users×48  (+uplift)\text{Annual value} = \text{hours saved/week/user} \times \text{rate} \times \text{users} \times 48 \; (+ \text{uplift})Annual value=hours saved/week/user×rate×users×48(+uplift)

If payback < 12 months, you’re on track.

LLMOps in MVP (lightweight but real)

• Golden set: 100 questions; 30 task cases with expected outcomes.
• Metrics: grounded %, refusal %, task success %, P95 latency, cost per successful answer/task.
• CI gates: block release on quality regressions or cost spikes.
• Canary & rollback: ship to 5–10% first; auto‑revert if thresholds breach.
• Usage page: show caps and forecasts to month‑end (no bill shock).

Privacy, security & region (do the essentials)

• Tenant isolation everywhere.
• PII minimised; redaction before embeddings/logs.
• Region pinning (AU/US/UK/NZ) for storage, processing, backups, and logs.
• BYOK (bring your own keys) for enterprise.
• SSO/RBAC and audit exports.
• Deletion workflow and certificate of destruction.

These basics pass most stakeholder sniff‑tests.

Go‑to‑market for your MVP (how to get real users)

• Pick 10–30 pilot users who feel the pain your app solves.
• Publish a simple pricing page (starter/pro/enterprise) even for pilots—real prices focus feedback.
• Measure weekly: time saved, deflection %, success %, cost per answer/task.
• Capture two case snapshots (before/after) to fuel sales.
• Onboard with a 30‑minute live session and a two‑page “how we approve/refuse” guide.

Pitfalls (and the fix)

• Bloating scope → One persona, two use‑cases.
• Guessing answers → Citations + refusal always on.
• No approvals → Thresholds by amount/risk.
• Messy content → Clean, chunk, tag.
• Run‑cost surprises → Short prompts, routing, caching, caps.
• No rollback → Canary first; revert fast on breach.

Launch checklist (paste into your tracker)

• Persona defined; two use‑cases agreed.
• Assistant returns cited answers; refuses correctly.
• One automation with tool schema, approvals, and audit.
• Content cleaned; metadata added (owner, last updated, region, precedence).
• SSO/RBAC; usage caps & alerts.
• Traces and dashboards live.
• Region pinning & PII redaction verified.
• Golden set passes targets; rollback demonstrated.
• Pilot users enrolled; onboarding complete.
• Case snapshot template ready.

FAQs (plain English)

Q: Do we need to “train a model” to build an MVP?
A: Usually no. Retrieval with citations + a single approved workflow gets you value faster and safer.

Q: What if the model changes and quality drops?
A: That’s why you ship with tests, canaries, and rollback. Revert within minutes.

Q: Can we cap monthly costs?
A: Yes—set entitlements, warnings at 70/85/95%, and hard caps with admin override. Use caching and routing to shrink spend.

Q: How soon will users feel a difference?
A: Often within two weeks of pilot—faster answers, fewer repetitive tasks, clearer decisions.

Q: Is mobile required for MVP?
A: Not if your users live in a web app or helpdesk. Add mobile when the core flow works.

Q: What about multiple regions and languages?
A: Start with one region/language. Add more after you’ve locked the core experience and content quality.

Talk to a real human about your AI MVP

We build custom AI apps that are useful, safe, and measurable from day one—citations, approvals, audit, and predictable costs included.

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