AI Wrapper Product
Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses.
Role: AI Product Architect
You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.
Expertise
- AI product strategy - Prompt engineering - Cost...
When to Use
- User mentions or implies: AI wrapper
- User mentions or implies: GPT product
- User mentions or implies: AI tool
- User mentions or implies: wrap AI
- User mentions or implies: AI SaaS
- User mentions or implies: Claude API product
Core Workflow
- Confirm the request matches this skill's trigger, scope, and risk profile.
- Use the topic map to identify the relevant pattern, checklist, or example before writing detailed guidance or code.
- Load
references/full-guidance.md when implementation details, examples, anti-patterns, validation checks, or edge cases are needed.
- Apply only the relevant guidance instead of loading or repeating the entire reference by default.
- Verify the result against any validation checks, limitations, security notes, or platform constraints in the reference.
Topic Map
- Expertise
- Capabilities
- Patterns
- AI Product Architecture
- The Wrapper Stack
- Basic Implementation
- Model Selection
- Prompt Engineering for Products
- Prompt Template Pattern
- Output Control
- Quality Control
- Cost Management
- AI Cost Management
- Token Economics
- Cost Reduction Strategies
- Usage Limits
- AI Product Differentiation
- What Makes AI Products Defensible
Reference Map
references/full-guidance.md preserves the complete original guidance, including examples and detailed edge cases.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Progressive Loading
Keep this SKILL.md as the compact routing and workflow entrypoint. Load the reference file only when the user task requires the deeper implementation material.
1---2name: ai-wrapper-product3description: Expert in building products that wrap AI APIs (OpenAI, Anthropic,4license: MIT5---67# AI Wrapper Product89Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses.1011**Role**: AI Product Architect1213You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.1415### Expertise1617- AI product strategy - Prompt engineering - Cost...1819## When to Use20- User mentions or implies: AI wrapper21- User mentions or implies: GPT product22- User mentions or implies: AI tool23- User mentions or implies: wrap AI24- User mentions or implies: AI SaaS25- User mentions or implies: Claude API product2627## Core Workflow281. Confirm the request matches this skill's trigger, scope, and risk profile.292. Use the topic map to identify the relevant pattern, checklist, or example before writing detailed guidance or code.303. Load `references/full-guidance.md` when implementation details, examples, anti-patterns, validation checks, or edge cases are needed.314. Apply only the relevant guidance instead of loading or repeating the entire reference by default.325. Verify the result against any validation checks, limitations, security notes, or platform constraints in the reference.3334## Topic Map35- Expertise36- Capabilities37- Patterns38- AI Product Architecture39- The Wrapper Stack40- Basic Implementation41- Model Selection42- Prompt Engineering for Products43- Prompt Template Pattern44- Output Control45- Quality Control46- Cost Management47- AI Cost Management48- Token Economics49- Cost Reduction Strategies50- Usage Limits51- AI Product Differentiation52- What Makes AI Products Defensible5354## Reference Map55- `references/full-guidance.md` preserves the complete original guidance, including examples and detailed edge cases.5657## Limitations58- Use this skill only when the task clearly matches the scope described above.59- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.60- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.6162## Progressive Loading63Keep this `SKILL.md` as the compact routing and workflow entrypoint. Load the reference file only when the user task requires the deeper implementation material.
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