# AI Native Opportunity Scan > Uses an agentic/closed-loop lens to find genuinely new AI-enabled business opportunities in your own startup case, and scores/prioritizes the findings by feasibility and the smallest prototypeable version. - Skill: `pilot2service/ai-native-opportunity-scan` (Agent Skill) - Install (CLI): `npx skillmds@latest add pilot2service/ai-native-opportunity-scan` - Raw SKILL.md: https://api.skillmd.com/api/skills/pilot2service/ai-native-opportunity-scan/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: Pilot2Service (https://skillmd.com/u/pilot2service) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/pilot2service/ai-native-opportunity-scan --- # AI-Native Opportunity Scan ## Purpose Find areas within your own startup case where AI enables something genuinely new — not just speeding up existing work. This skill uses a two-stage prompt chain with an AI thinking partner: first identifying five opportunities enabled by agentic/closed-loop-level AI, then pressure-testing and prioritizing them by business potential, customer value, and feasibility — arriving at one opportunity that is carried into the next stages of design. ## Based on - The owner's AI-native Business Design workshop (the owner's own workshop), run 1–2 June 2026, Day 1 — Session 1 "The New AI Mindset" exercise and the core distinction preceding it: AI is not just a productivity tool that speeds up existing work — it's a new capability and capacity that enables products and workflows that were previously too slow, too costly, or impossible. - See `../../references/workshop-source.md` (source information) and `../../references/prompt-library.md` (prompts 1–2, the basis of this skill). ## Method 1. **Make sure the AI thinking partner has your own business context available** — a project (Claude/ChatGPT) with your pitch, business plan, customer notes, etc. loaded. Without this, findings stay generic ("automate customer service with an AI agent"-type suggestions). 2. **Run the discovery prompt** (`../../references/prompt-library.md`, prompt 1): ask the AI to identify 5 areas where AI would create GENUINELY NEW business opportunities — not "do X faster" but new features, products, workflows, or business models. Require agentic/closed-loop-level thinking rather than basic productivity use (see `../closed-loop-process-and-human-oversight-design/SKILL.md` for a more detailed distinction). 3. For each of the five findings, capture: a name, a description (2-3 sentences), why it's newly possible thanks to AI, and what would need to be true for us to do this. 4. **Write your own preliminary assessment before the pressure-test stage.** This forces your own thinking before the AI's assessment — the workshop's principle: think for yourself first, don't let the AI assess on your behalf without your own view. 5. **Run the pressure-test/prioritization prompt** (`../../references/prompt-library.md`, prompt 2): ask for an assessment of each of the five on: business potential, customer value, feasibility for a small team with current AI tools (low/medium/high), and the smallest version that could be prototyped this week. 6. Ask for a ranking of 1–5 with rationale, and a recommendation for which to prototype first. 7. Choose one opportunity to carry forward — feed it into `../customer-vision-to-jtbd/SKILL.md` and `../ai-buildable-prd-writing/SKILL.md`. ## Gotchas - Running the discovery prompt without the AI thinking partner having your actual business context loaded (pitch, business plan, customer notes) produces generic "automate customer service with an AI agent"-type findings that only look like real opportunities — the method calls this out directly as the default failure mode. - Skipping step 4 (writing your own preliminary assessment before the pressure-test prompt) silently defeats the point of that step: the workshop's principle is to think for yourself first, not let the AI's scoring become the only judgment in the room. - The five findings from the discovery prompt can end up being faster/cheaper versions of existing work rather than genuinely agentic/closed-loop opportunities unless prompt 1's requirement is enforced — cross-check candidates against `closed-loop-process-and-human-oversight-design/SKILL.md`'s open-loop vs. closed-loop distinction before treating them as valid. - Treating the AI's 1-5 ranking and "prototype first" recommendation as the answer rather than an input is the mistake the "does NOT do" section warns about explicitly — the human still has to make the final call. - This is a lightweight, single-founder prompt chain, not the systematic portfolio process for an existing company's broader AI initiatives — reach for `ai-opportunity-portfolio` instead when the case is a running business with multiple candidate use cases, not a pre-startup idea. ## What this skill does NOT do - Does not make the choice for you — the scoring and ranking are an AI assessment, not the truth; the human makes the final choice. - Does not replace the `ai-opportunity-portfolio` skill (in the `ai-strategy-and-governance` pack) — that one is meant for the systematic prioritization of an existing company's broader AI portfolio. This skill is a lighter, faster prompt chain for a single pre-startup founder to work through their own case. - Does not generate business ideas out of thin air without your own business context — quality depends directly on how well the AI knows the case. ## Continue from here - Next skill in this pack: `../customer-vision-to-jtbd/SKILL.md` — deepens the chosen opportunity into customer understanding. - Related skill in this pack: `../closed-loop-process-and-human-oversight-design/SKILL.md` — deepens the "agentic/closed-loop" lens, which in this skill is only used as an identification criterion. - Related skill in this pack: `../ai-native-conversational-os-design/SKILL.md` — carries this skill's mindset shift forward into a concrete UI architecture (the "5 shifts": click>question, menus>prompts, dashboards>dialogue, manual actions>agents, screens>chat+cards). - Related skill in another pack: `../../../../ai-strategy-and-governance/skills/ai-opportunity-portfolio/SKILL.md` - The pack's shared guardrails: `../../CLAUDE.md` ## References - `../../references/prompt-library.md` — prompts 1–2 - `../../references/workshop-source.md` — source information - `../../CLAUDE.md` — the pack's shared guardrails