Agent skill · software engineering · personamanagmentlayer
ai-engineer-expert
Expert-level AI implementation, deployment, LLM integration, and production AI systems. Use when the user mentions AI engineering, LLM, deployment, production AI, or integration, or when the task involves LLM Patterns, LLM Integration, or Production Systems.
Why this skill is useful
Adds executable scripts for LLM integration and deployment strategies that are not commonly found in public documentation.
What it needs
Requires anthropic, langchain, openai installed locally. Requires anthropic, openai account access. About 5k tokens when loaded. Last updated 2026-03-30. 41 stars on the source repository.
What this skill does
AI Engineer Expert Expert guidance for implementing AI systems, LLM integration, prompt engineering, and deploying production AI applications. Core Concepts AI Engineering LLM integration and orchestration Prompt engineering and optimization RAG (Retrieval-Augmented Generation) Vector databases and embeddings Fine-tuning and adaptation AI agent systems Production AI Model deployment strategies API design for AI services Rate limiting and cost control Error handling and fallbacks Monitoring and logging Security and safety LLM Patterns Chain-of-thought prompting Few-shot learning System/user message design Function calling and tools Streaming responses Context window management LLM Integration RAG Implementation Prompt Engineering AI Agent System Production Deployment Best Practices LLM Integration Implement fallback providers Use streaming for better UX Cache responses where appropriate Handle rate limits gracefully Monitor token usage and costs Version prompts and track changes Production Systems Implement circuit breakers Add comprehensive logging Monitor latency and errors Use rate limiting Implement retry logic with backoff Test edge cases thoroughly Security Validate and sanitize inputs Implement authentication/authorization Never expose API keys in logs Use environment variables for secrets Implement content filtering Monitor for prompt injection Anti-Patterns ❌ No error handling or fallbacks ❌ Exposing raw LLM outputs without validation ❌ No rate limiting or cost controls ❌ Storing API keys in code ❌ No monitoring or logging ❌ Ignoring token limits ❌ No testing of prompts Resources OpenAI API: https://platform.openai.com/docs Anthropic Claude: https://docs.anthropic.com/ LangChain: https://python.langchain.com/ LlamaIndex: https://www.llamaindex.ai/ Weights & Biases Prompts: https://wandb.ai/site/prompts
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills personamanagmentlayer/ai-engineer-expert