lingxling/agentic-bundle-llm-application-developer

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

Architecture and integration sketches for LLM applications, with explicit retrieval, tool, privacy and verification boundaries.

Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation)

RAG (Retrieval-Augmented Generation) implementation workflow covering embedding selection, vector database setup, chunking strategies, and retrieval optimization.