How To Delegate To An Agent Like You Would An Employee?

How To Delegate To An Agent Like You Would An Employee?

Author: Demetrios August 17, 2026 Duration: 55:15

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


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 50

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