Every week, new AI features and automations appear, but the real question isn't whether you can automate something—it's whether you should. In this episode of In The Loop, I break down a framework—from the Department of Product Substack—to help you decide where to start with AI automation in your product. 

We’ll cover the concept of verifiability, how to score opportunities across safety, volume, and ease of validation, and why most AI features should be assistants, not full autopilots.

By the end, you'll have a practical approach to evaluating AI opportunities and avoiding the mistakes that kill adoption before it starts.

⏭️ Episode Highlights

(01:30) – Why automation is AI's biggest superpower right now

(04:15) – The Verifiability Principle: Can you tell if it worked?

(07:00) – Product vs. process: Deciding what to automate for users vs. teams

(09:15) – The three-dimensional framework: Safety, volume, and verifiability

(12:35) – Three reasons AI automation fails and how to design around them

(13:50) – Closing thoughts: Why doing nothing is no longer an option

🔗 Links & Resources

Episode transcript with more resources on the Mindset AI blog

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Jack Houghton

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