Stage 3 — Execute

Autonomous implementation, one component at a time.

The execution loop runs your AI coding tool in a cycle: pick the next incomplete component, implement it, verify, commit, and exit with fresh context.

See how Verify works →

The problem

Context windows fill up and output quality degrades mid-task
Agents lose track of cross-cutting decisions across long sessions
No structured memory means the same mistakes repeat across iterations
Manual orchestration of agent work does not scale beyond simple tasks
Not everyone knows what an execution loop is or how to use or build it

What ContextRail enables

1
1

Fresh context window per component—no accumulated hallucinations

2
2

File-based progress tracking persists state across iterations without LLM memory

3
3

Cross-cutting decisions documented in decisions.md carry forward automatically

4
4

Gate failures documented with root cause and retry strategy for the next run

5
5

Standard checked through every iteration of the execution loop

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6

Works with Cursor, Claude Code, Codex, Aider, and any MCP-compatible file-editing agent

Tools & integrations

MCP Server
Claude Code
Cursor

Each component gets the AI's full attention. The loop handles the orchestration.