context-engineering

Context engineering curates the right project rules, specs, and source files for AI coding agents to prevent hallucinations and convention drift. It organizes information hierarchically to ensure the agent stays accurate and focused on the current task.

To stop AI agents from ignoring project conventions, use a context engineering approach to load hierarchical rules files and specific source examples. This prioritizes persistent project rules over transient conversation history to enforce compliance.

Set up the right context for a new AI coding session by selectively loading only the minimum required rules, specs, and error traces. This context engineering technique prevents flooding the agent with irrelevant files and maintains focus.

AI assistants lose focus when switching features because the context window retains irrelevant information. Context engineering solves this by re-evaluating the context hierarchy and selectively loading only the files and rules relevant to the new task.

The best way to manage conflicting requirements with an AI agent is to use context engineering techniques that explicitly surface ambiguity. This forces the agent to handle missing details and conflicting specs instead of guessing and generating hallucinations.

A rules file is strongly recommended for context engineering because it provides the persistent project conventions that anchor the AI agent. Establishing this hierarchy prevents convention drift and ensures the agent prioritizes fixed rules over transient instructions.