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

AI agents shift the source of truth from code to runtime traces because decision logic happens inside the model, not in your codebase. Unlike traditional software where code documents behavior deterministically, agent code is just scaffolding that orchestrates LLM calls. This fundamental change means debugging becomes trace analysis, testing requires continuous evals in production, performance optimization focuses on decision patterns rather than algorithms, and collaboration moves to observability platforms. Without structured tracing to capture reasoning chains, tool calls, and decision points, you're working blind since the actual intelligence lives in traces, not code.

In software, the code documents the app. In AI, the traces do.