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.

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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.

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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.

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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.

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Database migrations are essential for managing schema changes in production applications. As your application evolves, your database schema must evolve with it - adding tables, modifying columns, creating indexes. This post covers migration strategies and tools for Go applications, with a focus on safe, reversible changes.

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