LLM Engineering12 min read
Agentic RAG with LangGraph: planning, rewriting, tool use
How agentic RAG uses LangGraph to plan, rewrite queries, and call tools. The graph, the state, and the nodes that turn single-pass RAG into reasoning.
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Build Your First Software Factory Execution Harness live Thursday, Oct 1, 12:00 PM ET
Oct 1, Reserve a seatDeep dives into Large Language Models - how they work, prompt engineering, behavior control, and optimization techniques.
31 posts in total
LLM Engineering12 min read
How agentic RAG uses LangGraph to plan, rewrite queries, and call tools. The graph, the state, and the nodes that turn single-pass RAG into reasoning.
LLM Engineering12 min read
How dynamic RAG re-plans retrieval mid-pipeline. The replanner prompt, the loop that recovers from bad chunks, and when this beats single-pass RAG.
LLM Engineering11 min read
How JSON output parsing grounds RAG answers in retrieved context. The Pydantic schema, the prompt, and the validation that kills hallucinations.
LLM Engineering11 min read
Stuff, Map Reduce, or Refine? How to pick the right LangChain chain type for RAG summarization, and the cost and quality trade-offs that decide it.
LLM Engineering11 min read
How quote extraction shrinks RAG context by 80% without losing answer quality. The pattern, the prompt, and the code that ships in production pipelines.
LLM Engineering4 min read
A guide to the internals of LLMs for engineers who use GPT APIs and wanted to understand how they work. Hands-on patterns and code for engineers building u
LLM Engineering5 min read
Control the behavior of your LLMs with prompt contracts, sampling, RAG, and function calling. Hands-on patterns and code for engineers building engineer sy