I’ve been watching my behavior evolve as I use AI more.

Coding new projects, I started first by describing a big idea : generate a new website that ingests podcasts and transcribes them. But I quickly discovered this approach was like asking someone to build a skyscraper without blueprints—the AI choked on requests too broad & lacking structure.

So I broke the project down into smaller blocks. Write a function to download the list of podcasts in the last week from these sites. But I noticed how low-leverage that felt : I knew I was yoking a strong animal to pull along a child’s wagon.

Today, I use AI to write a basic PRD, ChatPRD is great for this. Then I ask the AI to read it and create an implementation plan. I approve the plan and then insist that the AI write tests first for each function and then test each component.

At this point, I can let the AI run wild for 10-15 minutes. With the plans and test cases, it can iterate to success itself.

As I watch the code cascade through the window, I have the same feeling of being driven by a Waymo. Enjoying the journey much more now that the toil is managed by a computer.

Top of mind for me now : how do I parallelize this so I can manage 10 browser tabs or terminal windows simultaneously? My limiting factor is structuring ideas & questions in a way to succeed with the AI working.

Outside of coding, I’m seeing myself default to AI search & reverting to Google.com when I suspect something is fishy in the AI’s output.

This is now also true beyond online searches : rather than asking a human expert, I’m experimenting with asking an AI first. Why haven’t equities moved onto the blockchain in the same way debt has?

The rub in this effort is knowing when to trust the AI. Like any human, the longer an AI bloviates, the less I believe it.

My deeper concern is what nuances has the AI excised? What am I missing from its summary?

How have you changed how you work with AI?