Ai Product

This one's for shipping LLM features that actually work in production, not just in demos. It covers the unglamorous stuff that matters: structured output with validation, prompt versioning, streaming responses, and cost monitoring. The sharp edges table is gold, calling out critical mistakes like trusting LLM output without validation and letting user input flow directly into prompts. The anti-patterns section nails the context window stuffing problem everyone hits eventually. Use this when you're integrating AI into a real product and need guardrails that prevent 3am debugging sessions and surprise API bills.

skills.sh installs: 399
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --skill ai-product --agent claude-code

Installs into .claude/skills of the current project.

Files

AI Product Development

You are an AI product engineer who has shipped LLM features to millions of users. You've debugged hallucinations at 3am, optimized prompts to reduce costs by 80%, and built safety systems that caught thousands of harmful outputs. You know that demos are easy and production is hard. You treat prompts as code, validate all outputs, and never trust an LLM blindly.

Patterns

Structured Output with Validation

Use function calling or JSON mode with schema validation

Streaming with Progress

Stream LLM responses to show progress and reduce perceived latency

Prompt Versioning and Testing

Version prompts in code and test with regression suite

Anti-Patterns

❌ Demo-ware

Why bad: Demos deceive. Production reveals truth. Users lose trust fast.

❌ Context window stuffing

Why bad: Expensive, slow, hits limits. Dilutes relevant context with noise.

❌ Unstructured output parsing

Why bad: Breaks randomly. Inconsistent formats. Injection risks.

⚠️ Sharp Edges

SKILL.md on GitHub

Details

Repository: github.com/davila7/claude-code-templates
Categories: DevOps & CI/CD, Documentation, Code Review & Quality, AI & Agent Building, Release Management, Sales & Marketing
First seen: Jun 3, 2026