When you build a retrieval-augmented system, most of the tuning work happens before the LLM ever sees a document. How you split text determines what gets retrieved — and bad splits mean bad answers, even with a great model.

The problem with long documents

LLMs have a context window. You can't …

Standard RAG retrieves chunks of text and hands them to an LLM. Graph RAG retrieves a structured slice of a knowledge graph instead — entities, relationships, and the paths between them. That shift changes what kinds of questions the system can actually answer.

Why vector search runs out of road

Chunk …

Every LLM app that wants to read a file, query a database, or call an API needs some way to describe that capability to the model and route the model's requests back to the right system. Before MCP, every vendor built that wiring differently. MCP is Anthropic's attempt at a …

A chain follows the map you drew. An agent draws its own.

LangChain gives you two ways to wire an LLM into a workflow: chains and agents. Both connect prompts, tools, and models into something useful, but the control flow works in opposite directions.

Chains: fixed routes

A chain is …

The trick that turns a language model into a research assistant.

Large language models are great at reasoning and writing, but they only know what they were trained on. Ask one about a document it's never seen, or something that happened after its training cutoff, and it will either say …

Most people's first LangChain project looks the same. They copy a snippet, swap in their API key, run it, and get a working chatbot in about ten minutes. Then they try to add memory, or connect a second tool, or make the thing reason through a multi-step task, and the …

It sounds like the obvious next step for any serious AI product. In practice, it's one of the most misunderstood — and most expensive — decisions in AI development.

It sounds like the obvious next step for any serious AI product. In practice, it’s one of the most misunderstood — and most …

If you’ve ever Googled “best AI model” and ended up more confused than when you started — you’re not alone.

GPT this. Llama that. Claude, Mistral, Phi... it can feel like you’ve walked into a hardware store where every tool looks the same but nobody will tell you …

Building reliable AI agents isn't just about picking the right model — it's about the patterns you wire around it. Here's a concise reference of 15 agentic system design concepts worth knowing. Two lines each — just enough to understand what they do and why they matter.

Resilience & Failure Isolation

Agent Circuit …

Claude Code is not a chatbot. It lives in your terminal, reads your actual files, writes code, runs commands, and executes multi-step workflows — all with your permission. Here are 30 concepts you need to understand it properly. No fluff, no hand-holding.

The 30 Concepts

1. The Terminal — Claude Code doesn't …