AI Coding with Trusted Context
A repository explains what exists. Reqode explains what it means.
The agent starts from an explicit engineering memory instead of rebuilding product intent from file names, nearby code, tickets, and stale documents.
Product intent
Requirements, data entities, user interfaces, APIs, and Change Requests explain the behavior that should exist.
Implementation ownership
Software units connect responsibilities to files, dependencies, Unit Types, and unit-specific guidance.
Architecture contract
The subsystem Code Manifest and Unit Type rules tell the agent how this codebase is meant to be changed.
From a stable anchor to an implementation-ready picture
Reqode MCP is read-only and branch-aware. The agent retrieves focused context while product changes remain explicit and reviewable.
1. Load the app manifest
Start with the current subsystem architecture and the rules that apply to each kind of software unit.
2. Anchor the task
Begin from a Change Request, requirement, software unit, module, or source-file path instead of a loose prompt.
3. Follow connected context
Read the relevant specifications, Unit ownership, file mappings, dependencies, and accepted change decisions on demand.
4. Implement and verify
Make a focused code change, then use Reqode verification to find confirmed architecture or specification divergence.
A short prompt can carry precise context
The user supplies a stable key. The agent reads the current branch context and follows Reqode relationships instead of receiving a copied context dump.
Use Reqode MCP as the source of truth. Implement CR-123.
Trusted context stays controlled
MCP access is read-only. Coding agents can inspect accepted context, but they cannot silently rewrite specifications, Units, or Change Requests.
Let coding agents work from engineering context, not guesswork
Connect the product meaning behind your code to the agent that changes it.