Bad Claude! (Or Was It Bad Me?)

I'd been working on a presentation and document for about a week, iterating, refining, and building on ideas with Claude along the way.

Things were coming together nicely. Until they weren't.

During one of our later iterations, Claude added some content I didn't need. Simple enough. I asked it to remove it.

And it did.

Along with an entire section I actually wanted to keep.

BAD CLAUDE!

That was my immediate reaction. And the inspiration for a pretty entertaining meme.

But here's the funny part. Claude had done exactly what I asked.

Two sections had similar names. I knew which one I meant. Unfortunately, my instructions weren't nearly as clear as I thought they were.

It took just a minute to fix, but it was a perfect example of something we've all heard before: garbage in, garbage out.

Wait, Haven't We Seen This Before?

The more I thought about it, the more familiar it felt. How often does this happen in product development?

Someone requests a feature. Requirements get written. Designers design. Engineers build. Everything works exactly as specified. And then someone says, "That's not what I meant."

We've delivered what was asked for, but have we solved the actual problem?

It's one of the reasons I'm so passionate about design, research, and discovery. Our job isn't simply to execute requests. It's to understand the why, challenge assumptions, and help teams solve the right problems.

And honestly, the same lesson applies to leadership. When we delegate, how often do we assume someone understands the bigger picture simply because it's perfectly clear in our own heads?

Sometimes the issue isn't the execution. It's the context we forgot to share.

A Little Curiosity Goes a Long Way

One of my favorite philosophies is Think Big, Start Small. It's how I approach design, leadership, and increasingly, working with AI.

Dream big. Explore possibilities. Experiment. But take small steps, check your assumptions, and make sure you're heading in the right direction.

Whether I'm working with Claude or collaborating with a team, I'm reminded to ask:

Are we clear on what we're actually trying to accomplish?

Have we shared enough context to make good decisions?

Are we checking the outcome, not just whether the instructions were followed?

Simple questions. Surprisingly easy to overlook. Especially when you've been staring at the same document for a week.

So, Was Claude Bad?

Not really. It followed my instructions. I just hadn't communicated my intent clearly enough.

And while I'm keeping the Bad Claude meme (because it still makes me laugh), the experience was a good reminder:

Clarity isn't just about what we ask for. It's about making sure we understand what we're trying to achieve.

Sometimes the best lessons come from big successes. And sometimes they come from accidentally deleting a perfectly good section of your presentation.

What's your funniest AI moment where it did exactly what you asked—but absolutely not what you meant?