Before asking an AI coding agent to change a complex project, make the project’s constraints easy to find and review a plan based on them. The useful “file order” is an order of information and work—not a universal rule about alphabetical filenames or which file an agent must read first.
Why constraints and a plan come before code
An AI coding agent does more than produce a single code response. It gathers context, takes actions through tools, evaluates the results, and repeats. The quality of that work depends in part on whether the agent can find relevant project facts and whether the requested change is clear. Visual Studio Code describes this agent loop and recommends researching the codebase, clarifying requirements, and proposing a plan before code changes begin for complex tasks: Understand AI agents.
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This is practical workflow guidance, not proof that a particular file arrangement guarantees better code. The official guidance cited here does not quantify an improvement in accuracy, speed, or defect rates from writing constraints first.
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What to put in the repository
Give the agent a concise, navigable account of the project rather than expecting it to infer important rules from scattered code. VS Code’s context-engineering guidance discusses project Markdown and custom instructions as ways to provide context: Set up a context engineering flow in VS Code. GitHub recommends that repository instructions clearly summarize the codebase and what the software does: Using GitHub Copilot cloud agent to improve a project.
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- Project map: explain the main components and where relevant code lives.
- Product and architecture context: record behavior, boundaries, and design principles an agent should preserve.
- Contributor practices: document conventions, dependencies, and local build, test, or verification commands.
- Scoped rules: put folder- or file-specific requirements where they apply instead of making every rule global.
- Deeper sources: link from the short entry point to fuller architecture, product, or contributor documents.
Keep the entry point short; put detail where it belongs
A repository-level AGENTS.md or the equivalent instruction file supported by the selected tool can serve as a project map: state the stable, project-wide constraints and point to the detailed sources. OpenAI’s account of its Codex workflow warns that an oversized instruction file can crowd out the task, code, and relevant documentation, and describes a concise AGENTS.md as a map into a structured knowledge base: Harness engineering: leveraging Codex in an agent-first world.
Do not assume every agent, editor, or feature loads the same filenames or instruction formats. GitHub notes that support varies among Copilot features. Check the documentation for the tool and feature you are using before relying on a file being read automatically. A sensible illustrative layout is:
AGENTS.mdor a tool-supported repository instruction file: brief project map, hard constraints, and links.- Architecture, product, and contributor documents: detailed context and practices.
- Path-specific instruction files: conventions limited to particular folders or file types.
- A task plan: requirements, proposed edits, and checks for substantial work.
- Source and tests: implementation and verification.
This is one practical organization, not a required standard. The relevant distinction is between stable repository knowledge, narrowly scoped rules, and the plan for the current task.
Use the right amount of planning for the change
Small, self-contained change
For a limited change with clear scope, provide the necessary task context and use the agent’s normal work loop. A separate, elaborate plan may add little when the intended edit and its checks are already straightforward.
Complex or multi-file change
For work involving several components, unclear requirements, or meaningful design choices, separate planning from implementation. VS Code recommends using its built-in Plan agent for complex tasks to research the codebase, clarify requirements, and propose an implementation plan before code changes begin. That advice is specific to VS Code’s documented feature; other tools may offer different planning capabilities.
A useful plan reflects both the request and the codebase. It can state the intended changes, important constraints, expected outputs, and checks that would demonstrate the work is complete. Review and refine it before asking the agent to implement.
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A practical sequence from repository context to integration
- Gather current project facts. Identify the relevant architecture, conventions, dependencies, authoritative documentation, and local build or test practices. Ask the agent to inspect these sources rather than guess.
- Write or update the concise entry point. Put stable, project-wide guidance and links to deeper sources in the instruction file the chosen tool recognizes.
- Scope specialized rules. Add instructions for a particular path or file type where they apply. GitHub documents repository-wide instructions and path-specific instructions as distinct mechanisms for Copilot: Using GitHub Copilot cloud agent to improve a project.
- Ask for a plan when complexity warrants it. Have the agent research the relevant code, clarify ambiguity, and propose intended edits and useful checks. Review the plan before implementation.
- Implement against the reviewed plan. Keep the agent’s work tied to the agreed requirements and project constraints; address a changed assumption by revising the plan rather than letting scope drift silently.
- Inspect and verify before integrating. Review the diff, check assumptions, edge cases, error handling, and security, then run relevant tests. VS Code’s best-practices guidance covers planning for complex work, code review, testing, and concise scoped instructions: Best practices for using AI in VS Code.
- Maintain the documentation. Update the project map or deeper docs when the project’s actual conventions or structure change. OpenAI describes recurring documentation maintenance and mechanical checks for freshness and cross-links in its workflow: Harness engineering: leveraging Codex in an agent-first world.
What the file-order idea does—and does not—mean
Put stable constraints and pointers before the task-specific plan in the workflow; make implementation follow the plan, and validation precede integration. That is the useful interpretation of “the file order is the plan.” It does not mean every repository must use a particular filename, alphabetical sequence, or filesystem layout. Official guidance supports context layering and planning, not a universal operating-system rule about which file an agent reads first.
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