01What Is an Agentic Operating System?

An agentic operating system is a centralized workspace where you build and run AI systems that automate repeat jobs in your business. Instead of using scattered prompts and tools, you give each job its own tab or button. The system connects to your real data, your memory, and multiple AI models.

In this episode, Julian Goldie explains how he built his own agentic operating system using the time machine method. That method has three steps: track where your time goes, automate the biggest repeat job, and iterate until it works without you. Then you move to the next job.

The core idea is to stop doing the same week over and over. Every hour you spend on a repeat job, you will spend again next week unless you automate it. The agentic operating system helps you break that cycle and get hours back.

02Key Features of an Agentic Operating System

Julian's agentic operating system has several key features that make automation practical:

  • One job, one tab: Each repeat job gets its own tab in the interface, like SEO, video, and memory.
  • One-click actions: You can trigger a full automation with a single button instead of writing prompts.
  • Real data connections: It pulls live data from tools like Google Search Console so your automations use current information.
  • Multiple AI models: You can switch between models like Claude, Hermes, Antigravity, Codex, and Kimi GLM depending on the job.
  • Memory system: A memory tab (like an Obsidian vault) stores conversations and learnings so agents don't forget between chats.
  • Human approval gates: You can set up a step where a human approves anything before it goes public.

These features help you think in terms of systems, not prompts. You build a system around the job, and it runs automatically.

03How to Set Up Your Agentic Operating System

To build your own agentic operating system, follow these steps from the episode:

  1. Do a time audit. List the jobs you repeat every week and roughly how long each takes.
  2. Pick the job that eats the most hours. That is your first automation target.
  3. Create a dedicated tab or system for that job inside your AI workspace.
  4. Connect the system to your real data sources, like search console or your memory vault.
  5. Choose the best AI model for that job. Not every model is good at everything.
  6. Add a human approval gate if the output goes public.
  7. Test the automation and iterate until it runs without you.
  8. Move to the next biggest job and repeat the process.

Julian recommends doing this week by week. One system at a time is manageable and avoids overwhelm.

04Using the Time Machine Method in Practice

Julian demonstrates the time machine method with several examples. For SEO, he built a system called Search OS. It has a research tab that finds keywords you already rank for and gaps around them.

You click a button, pick a keyword, and the system generates an article using a model like Hermes. Then it deploys the content to your website.

For video, he built a video agent. You give it a topic, it goes to a director, and it produces finished videos. The system even creates images to go alongside the videos.

Everything is saved in a workspace where you can preview and switch between outputs.

For memory, he created a memory galaxy. Agents capture memories and store them there. Then you can turn those memories into projects like apps, articles, videos, guides, or social posts.

You just pick a type, and the system runs on a loop.

The key is to track your time first, then automate, then iterate. Julian uses his Obsidian vault as a memory system to get recommendations on what to automate next.

05Results and Case Studies from the Episode

Julian shows real results from his agentic operating system. For SEO, he ranks number one for the keyword 'best geo experts'. He discovered that keyword in his search console dashboard, generated content, and deployed it.

That got him the top spot.

For video, he replaced his video editors with the system. After Opus 5.5 came out, he built a system that edits videos automatically. He says the quality is better than what his editors produced.

He also mentions that he iterates weekly. He started the SEO system in May and kept improving it through June and beyond. Each week he finds a new way to make it better.

These examples show that the method works in practice. It turns repeat work into automated systems that deliver results.

06Tips, Limits, and Mistakes to Avoid

Julian shares several tips and warnings:

  • Don't automate at random. Focus on one job at a time.
  • Don't abandon an automation when it breaks. Fix it and turn the fix into a rule so it doesn't break the same way twice.
  • Don't let AI forget between chats. Use a memory system to store important context.
  • Give yourself a week to get an automation to work. Don't expect perfection on day one.
  • Use human approval gates until you trust the system.
  • Track your time honestly. You can't get back time you don't see.
  • It's okay if you're not technical. You can get a ready-made agent OS from Julian's community, and he offers training and support.

The biggest mistake is getting overwhelmed and doing nothing. The three-step process keeps it simple and repeatable.

07Why an Agentic Operating System Matters

An agentic operating system matters because time is the one thing you can't get back. Automating repeat jobs compounds over time. Week one, you have one system.

Week two, you have two systems working together. Soon you have multiple systems running automatically.

This approach also gives you control. Instead of guessing where your time goes, you track it. You decide what to automate next.

The system works for you, not the other way around.

It works for almost any business. Even if you think your work is too unique, you'll find a handful of jobs that repeat every week. Those are the ones to automate first.

Julian's message is clear: stop doing the same week over and over. Use the agentic operating system to get hours back and move forward.