8 AI tools for LangChain ?
Skill for RAG systems - semantic chunking, hybrid retrieval, advanced retrieval techniques, evaluation, and production.
Reliability-first patterns for autonomous AI agents - ReAct, Plan-Execute, Reflection loops, guardrails, and LangGraph checkpointing - plus failure modes.
Skill documenting LLM context-window strategies: tiered routing, serial-position optimization, importance-based summarization, and token budgets.
Skill for designing tiered LLM conversation memory - buffer, short-term, long-term, entity - with consolidation and user isolation.
A LangChain/LangGraph agent development skill: StateGraph state management, multi-agent orchestration, RAG, production deployment, evaluation.
Langfuse LLM observability expert: tracing, prompt versioning, LLM-as-judge evaluation, datasets, and OpenAI/LangChain integration.
An AI engineer skill for building production LLM applications, advanced RAG systems, and intelligent agents.
Seven-phase bundle orchestrating specialist skills across LLM integration, RAG, agents, ML pipelines, observability, and AI security.
