How To Delegate To An Agent Like You Would An Employee?
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About this episode
OpenAI's Codex developer experience lead sits down with a former comedian turned ML engineering lead for a conversation about what happens when computer use agents stop being a novelty and start actually running your day.
The conversation moves through building an AI-powered morning brief that reads every email, Slack message, and tweet before you've even opened your laptop, letting pinned threads check in on themselves every 30 minutes, and a skills system built to mirror how a person actually writes and reviews code. There's a close look at the guardrails and permission layers that keep an autonomous agent from pushing to the wrong repo or replying to the wrong tweet, how a codebase merging thousands of pull requests a day survives thanks to self-healing review before anything hits CI, and the idea of AI deference - when an agent should push through a task alone versus stop and ask for help.
The back half gets personal: why developing taste and vocabulary now matters more than working harder, what it actually takes to delegate to an agent the way you'd onboard a new employee, and why this might be the year voice-orchestrated computer use finally makes everyone feel like they're talking to Jarvis.
OpenAI: https://openai.com
Monaco: https://www.monaco.com
Jason Liu: https://www.linkedin.com/in/jxnlco
Mihail Eric: https://www.linkedin.com/in/mihaileric
Demetrios: https://www.linkedin.com/in/dpbrinkm
Timestamps:
[00:00] Intro and guest backgrounds
[01:36] Why computer use beats plain API calls
[09:11] Building an AI-powered morning brief
[10:17] Self-monitoring threads that check in on their own
[18:26] How OpenAI reviews thousands of PRs a day
[19:42] Self-healing pull requests before CI even runs
[23:07] Building review skills from teammates' habits
[30:52] Why hard work stops being the differentiator
[35:03] Introducing the idea of AI deference
[42:44] Learning to delegate like hiring your first assistant
[46:22] Why voice beats typing for giving agents context
[50:56] The Tony Stark Jarvis analogy for this year
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