I Didn’t Think This Was for Me—So I Applied Anyway

Editor’s Note

I didn’t plan to start this journey. I saw a post. I applied. Now I’m writing about what happened—mostly for myself, maybe for anyone wondering if something like this could ever be for them, too. The only plan I’ve ever really stuck with is this: keep learning.

A Post, a Pause, a Choice

The Calbright College announcement was brief: an AI Summer Camp hosted by Cal Poly and Amazon Web Services. No prior AI experience required.

That stopped me. Because that’s me. No machine learning background. No Python. No technical title. Just curiosity—and the momentum I’ve been quietly building.

I supervise jury operations at the court. That means managing jurors across courtrooms, helping the public navigate their service, and troubleshooting the real-world logistics that keep civic duty moving. It’s a job rooted in law, people, and process.

AI didn’t seem connected to that.
But I didn't let that stop me. 

Continuous, Not Sudden

I didn’t pivot into tech overnight. This has been slow, steady, and deliberate.

At 45, I earned my MPA.
At 46, I completed the Google Data Analytics Certificate.
At 47, I was selected for this AI Summer Camp.

I’m sharing it because applying didn’t come naturally. Saying yes took effort, not confidence.

I was busy, outside my lane, and ready to self-reject. 

But I’ve learned this much: never take yourself out of the running.

The Work Behind the Work

Public service is a strange mix of urgency and routine. There’s no such thing as “downtime” when you’re short-staffed. Legal mandates. Operational demands. Real people. Repeat.

On a typical morning, I might coordinate four jury panels across three buildings, answer last-minute courtroom requests, and help a member of the public navigate deferral policies—all before lunch.

That’s access to justice. Not in theory. Not in automation. In motion.

So when I think about AI, I don’t see disruption. I see potential:

• To support overstretched teams

• To make information clearer

• To reduce rework so we can focus on real judgment calls

But change doesn’t come easy. We’ve lived through transitions before.

Typewriters once worked. So did paper files. But neither could stretch to meet what came next. 

Change didn’t come from failure. It came from recognizing our tools no longer met the moment. 

That’s where we are now with AI.

We may not have the budget or infrastructure. But the tools are here.
And public institutions need to do more than catch up. We need to help shape the adaptation.

Not a Mold, But a Fit

I don’t write code. But I build clarity, structure, and tools in their own right and I know what I bring. 

The imposter voice? Still there. But it doesn’t get the final say.
It never has.

I’m not attending this camp to prove anything.
I’m attending because I’ve earned the right to be curious, to grow, and to bring it back to the people and processes I care about.

What’s Next

I’m working through AWS’s foundational materials—learning how tools like Bedrock, S3, and Lambda connect. I’m not pretending to be an expert. But I’m also not pretending I don’t care.

I’m imagining small but real applications—like a staff chatbot powered by our onboarding manual. Something to help new jury clerks look up policies without waiting on a supervisor. Not everything will translate. But some of it will.

And that’s enough to keep going.

AI-assisted, but human-approved, just like any good front office move. Chat GPT the sixth person off the bench editor for this post. Every take is mine.