When should you let AI agents loose on your processes, and when should you keep them on a tight leash? Peter and Dave explore the messy reality of using agentic AI for process improvement.
They dig into why the processes you can easily map might not be the ones where AI agents add the most value. From recruitment pipelines that need human intuition to DevOps workflows that demand zero variation, not every process is created equal when it comes to AI intervention.
This week's takeaways:
- Categorize your processes first. Look at your processes and start sorting them. Some need to eliminate variation (like DevOps deployment pipelines), while others benefit from exploring the edges and finding creative solutions.
- Not all processes are equal when it comes to AI. There are many ways AI can help improve processes, but you need to think about whether you want to reduce variability or increase intelligent flexibility in each specific case.
- Train AI to know when to hand off. What you want AI to do is recognize when it can't handle something and pass it to the right system - whether that's a math library for calculations or a human for complex decisions.
- Understand the difference between consistency and exploration. DevOps spent years eliminating variation to create stable, repeatable deployments. Other processes might actually want that variation because it gives you something unusual and valuable.
If you're wrestling with where to apply AI in your organization without breaking what already works, this episode offers a practical framework for thinking through the trade-offs.
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