Agentic loops are already running in your business. If you have given an AI tool a research question, walked away, and come back to a finished brief, you have used one. The same mechanism fires a payment reminder after checking whether an invoice has actually cleared, keeps Claude Code testing its own fix until the bug is gone, and sends meeting notes straight into your to-do list the moment a call ends.
In this episode, Jess and Kyle get into how an agentic loop actually runs, how it connects to AI agents and AI workflow automation more broadly, and what separates it from a basic automation. They cover the three types of loop, the compounding maths of how a loop can get expensive fast, and how to build in the right amount of human oversight without losing what makes loops useful in the first place.
This is also where the vibe coding series starts to pull together: everything covered so far, the tools, the project structures, the files and folders, has been setting up for this.
We also cover the launch of the ChatGPT 5.6 models.
Use these links for a discount on the tools we recommend (and it supports the pod!)
Vibe Coding Series:
What You'll Learn:
Timestamps:
00:50 Introduction and Personal Updates
07:36 What an Agentic Loop Is and Why It Powers Vibe Coding
11:01 The Three Things Every Loop Needs to Work
15:23 Scheduled, Event-Triggered, and Goal-Based: The Three Types of Loop
16:32 Loops vs Basic Automations
18:56 The Importance of Human In the Loop
20:43 Improving Your Loop Over Time
24:55 What loops look like in practice
30:52 What loops take off your plate
31:46 Where loops go wrong
36:46 The Importance of Oversight in Automation
37:43 Keeping Loops Simple and Effective
41:39 Practical Takeaways for Implementing Loops
45:11 News of the Week: ChatGPT 5.6 Models
47:05 What's next in the vibe coding series
Resources:
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