LCEL chains are powerful but limited - they can’t loop, branch dynamically, or maintain complex state between steps. LangGraph solves this by modeling agent workflows as state machines: graphs where nodes are processing steps and edges define control flow. This explicit structure enables cycles, conditional routing, and persistent state that production agents require.

Read More

The LangChain Expression Language (LCEL) transforms how we build LLM workflows. Instead of managing execution flow manually, LCEL lets you compose components declaratively - like Unix pipes for AI. Combined with tool integration, LCEL enables building agents that reason and act in the real world.

Read More

If you’ve been building with LLMs, you’ve likely encountered the gap between simple API calls and production-ready agent systems. LangChain and LangGraph bridge that gap, providing the abstractions and patterns needed to build reliable, maintainable AI applications. This series takes you from LangChain fundamentals to production multi-agent systems, focusing on practical implementation over theory.

Read More

Authentication verifies who users are, while authorization determines what they can access. This post covers implementing JWT (JSON Web Token) authentication in Go - the most common approach for stateless API authentication.

Read More

Middleware and concurrency are two powerful features that make Go excellent for backend development. Middleware enables cross-cutting concerns like logging and authentication, while Go’s goroutines and channels provide elegant solutions for concurrent processing. This post explores both patterns in depth.

Read More

Your browser is out-of-date!

Update your browser to view this website correctly. Update my browser now

×