Use the /goal Command to Run AI Coding Tasks Autonomously
Learn how to set up a self-supervising AI agent in Claude Code or Codex that completes coding and research tasks without interruptions, using a simple command and clear success criteria.
Practical Summary
This method uses the '/goal' command in AI coding environments like Claude Code to create an autonomous loop. A primary agent executes the task, prints its work as proof, and a secondary agent evaluates it against pre-defined, explicit completion criteria. If the proof fails, the agent loops to correct its work. This removes the need for a human to periodically check progress or provide 'keep going' prompts, turning a multi-interruption task into a single, unattended run.
Why It Matters
For professionals building products or services with AI, this workflow directly translates to time savings and increased output. By eliminating the 'babysitting' overhead of AI coding sessions, teams can run more complex tasks in parallel, reduce human-in-the-loop bottlenecks, and accelerate development cycles—all factors that contribute to faster product iteration and potential revenue growth.
Step 1: Understand the Two-Agent System
The system uses two logical AI roles: a 'worker' agent that performs the task (e.g., writing code, researching, drafting) and a 'checker' agent that evaluates the output. The worker prints its results into the chat. The checker only reads this chat output; it cannot open files or run commands. It grades the work against your explicit goal.
Step 2: Define an Explicit, Verifiable Goal
The key to success is writing a goal that the checker can objectively verify. Vague instructions like 'make it good' will fail. Instead, use specific, binary criteria: "Every claim has a source link, zero placeholders, all six sections present." This gives the checker agent a concrete rubric to grade against.
Step 3: Execute the /goal Command
In your AI coding tool (e.g., Claude Code), type '/goal' followed by your detailed, verifiable goal description. The command initializes the autonomous loop. Setup is reportedly quick—around ten seconds. The post mentions a config flag is needed for Codex.
Step 4: Walk Away and Monitor the Chat
After entering the command, the agent will work independently. It will produce output (proof) in the chat. The checker evaluates it. If the proof meets all goal criteria, the task ends. If not, the worker agent takes another turn to correct its work based on the checker's feedback, continuing the loop without human intervention.
