Learn how to build an agent -- from choosing realistic task examples, to building the MVP to testing quality and safety, to deploying in production.

Langchain is a publication focusing on programming languages, language design, and compiler development. Readers can explore articles covering topics such as language features, syntax design, and compiler optimization techniques. Additionally, they can learn about programming language theory, language implementation challenges, and practical applications of language design principles.

LangChain

A comprehensive framework for building AI agents from concept to production, covering six key steps: defining realistic tasks with concrete examples, creating standard operating procedures, building an MVP with focused prompts, connecting to real data sources, testing and iteration, and deployment with continuous refinement. The guide emphasizes starting small with well-scoped problems, focusing on core LLM reasoning tasks first, and treating deployment as the beginning of iteration rather than the end of development.

How to Build an Agent

Step 1: Define your agent’s job with examples