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The Codex feature that works while you sleep

30 min episode · 2 min read

Episode

30 min

Read time

2 min

Topics

Productivity, Health & Wellness, Leadership

AI-Generated Summary

Key Takeaways

  • Goal vs. Prompt Structure: Standard prompting is turn-based — the AI completes one step and waits. The /goal command creates a continuous work-verify-iterate loop where Codex keeps running until it gathers measurable evidence of completion, then reports back. This enables multi-hour autonomous sessions without manual "keep going" prompting between each step.
  • Six-Part Goal Framework: Effective Codex goals require six components: a defined outcome, a verification method, constraints on what cannot regress, boundaries on which tools and files are accessible, an iteration policy for deciding next steps, and a stopping condition that tells the AI when to surface blockers rather than continue attempting fixes independently.
  • Error Elimination Use Case: Point /goal at error logs in tools like Sentry or Vercel, instruct Codex to categorize each error, fix root causes, and replay historical examples to validate fixes. Claire used this approach to reduce a persistent edit-operation error from recurring daily to zero occurrences, with Codex running several hours to produce a systematic rather than patched solution.
  • Non-Technical Productivity Applications: /goal works beyond coding — Claire reduced approximately 3,900 unread Gmail messages to 68 requiring attention in a 3-hour-52-minute session. Codex categorized emails, clicked unsubscribe links, and created labeled folders. A similar approach cleaned hundreds of stale Linear project tasks by applying a consistent rule: cancel any incomplete pre-current-week episode work.
  • When Not to Use /goal: Avoid /goal for single-line edits, vague outcomes like "improve code quality," or tasks without a measurable finish line. The feature is strongest when three conditions exist: a durable objective that stays stable over time, an evidence-based completion condition that can be tested programmatically, and a path requiring multiple investigative iterations to reach.

What It Covers

Claire Vaux walks through Codex's /goal feature, which enables AI to run autonomously for hours without human prompting. She covers the six-part goal-writing framework, demonstrates three real use cases — error elimination, inbox cleanup, and task management — and explains when goal-based loops outperform standard turn-based prompting.

Key Questions Answered

  • Goal vs. Prompt Structure: Standard prompting is turn-based — the AI completes one step and waits. The /goal command creates a continuous work-verify-iterate loop where Codex keeps running until it gathers measurable evidence of completion, then reports back. This enables multi-hour autonomous sessions without manual "keep going" prompting between each step.
  • Six-Part Goal Framework: Effective Codex goals require six components: a defined outcome, a verification method, constraints on what cannot regress, boundaries on which tools and files are accessible, an iteration policy for deciding next steps, and a stopping condition that tells the AI when to surface blockers rather than continue attempting fixes independently.
  • Error Elimination Use Case: Point /goal at error logs in tools like Sentry or Vercel, instruct Codex to categorize each error, fix root causes, and replay historical examples to validate fixes. Claire used this approach to reduce a persistent edit-operation error from recurring daily to zero occurrences, with Codex running several hours to produce a systematic rather than patched solution.
  • Non-Technical Productivity Applications: /goal works beyond coding — Claire reduced approximately 3,900 unread Gmail messages to 68 requiring attention in a 3-hour-52-minute session. Codex categorized emails, clicked unsubscribe links, and created labeled folders. A similar approach cleaned hundreds of stale Linear project tasks by applying a consistent rule: cancel any incomplete pre-current-week episode work.
  • When Not to Use /goal: Avoid /goal for single-line edits, vague outcomes like "improve code quality," or tasks without a measurable finish line. The feature is strongest when three conditions exist: a durable objective that stays stable over time, an evidence-based completion condition that can be tested programmatically, and a path requiring multiple investigative iterations to reach.

Notable Moment

Claire describes sitting idle after setting a /goal task, actively searching for something to contribute because the AI had absorbed the entire workload. She frames this shift — from builder to manager — as both a productivity milestone and a genuinely disorienting change in how she relates to her own work.

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Episode Transcript

Welcome back to How I A I. I'm Claire Vaux, product leader and AI obsessive here on a mission to help you build better with these new tools. Today, I'm gonna walk through my favorite feature in my most recent favorite AI product, goals in codex. If you've been wondering how all these people on the timeline are getting their AI to run, quote, unquote, overnight or handle very complex long running tasks, I'm gonna show you goals is the answer. We're gonna walk through what it is, how I might use it, and a technical use case along with some nontechnical examples of how goals can help you even if you're not coding. Let's get to it. This episode is brought to you by Mercury. As an AI founder, I'm constantly tracking run rate, watching revenue growth, paying vendors, and making sure I'm getting paid on time. Mercury makes all of it feel effortless. The app is genuinely beautiful. It actually looks and works like modern software, which sounds obvious, but apparently isn't when it comes to banking. What I use it for the most, bill pay for my vendors is just clean and easy. And wires and transfers, getting paid from clients, moving money, Mercury makes it so simple. Everything you need is right there. No phone calls, no hunting through menus, no wondering if something went through. I think about how much I've optimized every other tool in my stack. Mercury is the one where I don't have to think about it at all. It just works. Visit mercury.com to learn more and apply online in minutes. Mercury is a fintech company, not an FDIC insured bank. Banking services provided through Choice Financial Group in column NA, members, FDIC. Before I go into how to use Gold, I wanna talk about what Gold is and when it's appropriate and when it's not the right tool for the job. So I'm looking at this blog post by the OpenAI developers team. It's called Using Goals in Codecs. And the first thing that they have in this blog post is this awesome diagram that talks about the difference between a prompt and a goal based loop. In a prompt, you all are used to this. It's sort of the turn based request that we're all used to. You ask the LLM, the model, the harness to do something. It works. It returns to you its result, and then it waits for you to prompt it. Again, if you're like me, the number one thing that you're saying in your coding tool is, okay, what's next? And then it tells you and you say, great, do it. If you find yourself in that process, using slash goal in codex might be a tool that you wanna add to your toolkit. So what's the difference between this turn based, one response, weight, and goal? Well, with goal, when you give codex a goal, it actually has something that it can work …

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Tools

  • A similar approach cleaned hundreds of stale Linear project tasks by applying a consistent rule: cancel any incomplete pre-current-week episode work.
  • Point /goal at error logs in tools like Sentry or Vercel, instruct Codex to categorize each error, fix root causes, and replay historical examples to validate fixes.
  • Claire Vaux walks through Codex's /goal feature, which enables AI to run autonomously for hours without human prompting.
  • Point /goal at error logs in tools like Sentry or Vercel, instruct Codex to categorize each error, fix root causes, and replay historical examples to validate fixes.
  • SPONSORS: Mercury
  • Claire reduced approximately 3,900 unread Gmail messages to 68 requiring attention in a 3-hour-52-minute session.

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