Context is the New Code

In traditional software development, the most important artifact is code. In AI-native development, the most important artifact is context. The CLAUDE.md file, the system prompts, the agent definitions, the workflow protocols -- these documents are more valuable than any single function or component because they determine the quality of everything the agents produce.

Context engineering is the discipline of structuring information so that AI agents can use it effectively. It is part documentation, part architecture, part communication design. Done well, it produces agents that consistently deliver high-quality output with minimal human intervention. Done poorly, it produces agents that are unreliable, inconsistent, and expensive to correct.

The principles of good context engineering mirror the principles of good writing. Be clear. Be specific. Be structured. Anticipate misunderstandings. Provide examples. Define success criteria. Every ambiguity in your context is a potential failure mode in your agent's output. Every undefined edge case is a bug waiting to happen.

We maintain context documents for every project -- hundreds of lines of structured information that tell our agents who the client is, what the product does, what the technical constraints are, what the quality standards are, and how to handle common situations. These documents evolve with the project. They are versioned, reviewed, and refined with the same rigor we apply to code.

The developers who will thrive in the AI era are not the ones who can write the most complex algorithms. They are the ones who can write the clearest context. Who can decompose a business requirement into a structured prompt that an agent can execute flawlessly. Who can anticipate the ways an agent might misinterpret instructions and preemptively address them.

Context engineering is not prompt engineering. Prompt engineering is about getting a single good response from a model. Context engineering is about building a system of interconnected documents that enable reliable, consistent, high-quality output across an entire project lifecycle. It is infrastructure, not a trick. And it is the most important skill nobody is teaching yet.