# AI Product Teardown > Structured teardown of AI products (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.). Analyzes product decisions, UX patterns, technical architecture, business model, and competitive positioning. Use when this capability is needed. - Skill: `tomevault-io/ai-product-teardown` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/ai-product-teardown` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/ai-product-teardown/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/ai-product-teardown --- # AI Product Teardown Skill Perform a structured, opinionated teardown of any AI product — analyzing the product decisions, UX, technical architecture, business model, and competitive positioning from a PM lens. ## When to Use - User asks "Tear down [AI product]" or "Analyze [AI product]" - User wants to understand the product thinking behind an AI feature - User wants to build product intuition about AI products - User says `/ai-product-teardown` followed by a product name - Great for: ChatGPT, Claude, Gemini, Perplexity, Copilot, Midjourney, Cursor, v0, NotebookLM, etc. ## Framework: AI Product Teardown (7 Sections) ### Section 1: Product Overview - **What it is**: One-sentence description - **Company**: Who built it, their mission, and strategic context - **Launch date & trajectory**: When launched, key milestones, current scale - **Target users**: Primary and secondary audiences - **Business model**: How it makes money (or plans to) ### Section 2: Core Value Proposition - **Job to be Done**: What fundamental job does this product do for users? - **10x moment**: What's the moment where users think "this is magic"? - **Switching cost**: What would it take to switch away? - **Network effects**: Does it get better with more users? How? ### Section 3: UX & Product Decisions Walk through the key product decisions and evaluate each: - **Onboarding flow**: How does a new user go from zero to value? - **Core interaction model**: Chat? Canvas? Structured output? Multi-modal? - **Information architecture**: How is functionality organized? - **Personalization**: How does it adapt to different users? - **Error handling**: What happens when the AI is wrong? For each decision, evaluate: - What they got RIGHT and why - What they got WRONG or could improve - What trade-off they're making (and whether you'd make the same one) ### Section 4: Technical Architecture (PM Lens) Analyze the technical choices from a product perspective: - **Model strategy**: Which model(s)? Why that capability level? - **Latency vs. quality trade-off**: Where do they sit on the spectrum? - **Context & memory**: How does it handle conversation history? - **Safety & guardrails**: What's their content policy approach? - **Tool use / plugins / integrations**: How extensible is it? - **Pricing architecture**: How do technical costs map to pricing? ### Section 5: Growth & Distribution - **Acquisition channels**: How do users find this? (organic, viral, paid, partnerships) - **Activation**: What gets users to the "aha moment"? - **Retention loops**: What brings users back? - **Monetization**: Free → paid conversion strategy - **Viral mechanics**: Does usage naturally create awareness? ### Section 6: Competitive Positioning - **Direct competitors**: Who else does this job? - **Positioning map**: Plot on 2x2 (e.g., capability vs. safety, consumer vs. enterprise) - **Sustainable moats**: What's defensible? (data, distribution, brand, model quality, ecosystem) - **Vulnerability**: Where could a competitor win? ### Section 7: PM Recommendations If you were the PM, what would you do next? - **Top 3 features to build** (with reasoning and expected impact) - **Top 1 thing to kill or change** (what's not working) - **Strategic bet**: One big swing that could transform the product - **Metrics to watch**: What would you track weekly? ## Output Format Write as an opinionated product review — structured but with a clear point of view. Use screenshots/descriptions of specific UI elements where relevant. Aim for ~2000 words. Be specific and cite real features. ## Research-First Workflow 1. **Research** — Search for latest product updates, user reviews, competitor announcements, company blog posts, and usage data. Do 5-10 searches. 2. **Cite sources** — Include `[linked source](url)` inline for factual claims. 3. **Display** the complete teardown. ## What Good Looks Like - Shows you've done homework on the product landscape - Demonstrates structured product thinking on real products - Reveals your product taste and judgment - Provides concrete examples to reference in product discussions - Builds intuition about AI product patterns across the industry --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/aroyburman-codes) — claim your Tome and manage your conversions.