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Earl Grey
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AI Took Me to Three Stages. I Still Don't Like Public Speaking.

A court professional's unexpected AI speaking tour

A year of building with AI put me on three stages. I liked the message more than the microphone.

TL;DR: In July 2025 I started building with AI to see how far it could take me. It took me further than I planned: onto court conference stages in Albuquerque, Los Angeles, and Riverside, talking about frontline staff leading small AI pilots. This is the written version of that talk, the one thing I would change about it, and what three rooms taught me about doing something I don't enjoy.

I walked into the room in Albuquerque with a deck I had rehearsed for weeks and no idea how any of it would land.

It was February 2026, and I was there to speak at the NACM 2026 Midyear Conference, the National Association for Court Management's national gathering. I was also the only person there from my court. No coworker in the third row. Nobody to grab coffee with afterward and ask, "Was that okay?"

I had prepared. I had also never done this before. That combination felt high risk in a way that had nothing to do with slides. If it went badly, I would carry it home alone.

It was a familiar feeling. I had felt it once before.

Alone in the room, again

In July 2025 I applied to the California Community Colleges AI Summer Camp. Nobody suggested it. I got one of 100 seats, out of about 1,300 applicants, and I was the only court professional on the list.

I was so worried about keeping up with computer science students that I spent the weekend before camp building a jury chatbot called Your Honor, I Object, just to see if I could. At camp, at 4:59 PM on day one, my mentor asked me to build a PDF extractor the rest of our project depended on. I had ChatGPT open that night and my team beside me. Our team placed second out of fourteen.

I started building with AI to find out how far it could take me. Speaking turned out to be the same experiment on a different stage. When the chance to present at NACM came up, I said yes for the same reason I applied to camp. I wanted to find out.

The second time was harder

Five months later, in July 2026, I spoke at a court in Los Angeles. I expected it to be easier. I had done this once. I knew the talk.

I was so much more nervous.

Some of that was the room. The Los Angeles Superior Court is the largest trial court in the country, and they were excited to have me. Excitement from your hosts is lovely. It also raises the bar you set for yourself.

Some of it was me. After Albuquerque, I expected more of myself, not less.

And some of it was the name on my badge. When I speak, I'm not only speaking for myself. My court's reputation walks into the room with me. Santa Barbara is a smaller court, and standing in front of the biggest one, carrying that name, felt heavier than standing up alone.

I didn't expect the second time to be harder than the first. The first time, I had nothing to live up to.

Two months, and still editing

The third talk was yesterday, October 16, 2026, at the Southern Region Finance Officers Meeting, hosted by Riverside Superior Court. The theme was the Currency of Curiosity.

I had two months to prepare. I was still changing slides the day before.

One thing helped more than I expected. I asked Claude to turn my speaker notes into an MP3, and I listened to my own talk in the car. AI helped me build the pilots in the talk, and then it helped me rehearse the talk about them.

It went well. My jokes got laughs from a room full of finance officers, which I am counting as a win.

Then I walked off and waited for the feeling of accomplishment. What came instead was relief that it was over.

That was when I knew. I'm proud of this talk. I love its message. I don't love public speaking.

What the talk says

The odd thing about all those nerves: I trusted the work, even when I didn't trust myself to present it. I knew what I had built, what had failed, and why I stopped. That was the part I wanted people to hear.

The talk is called Building Bridges, and its argument is that frontline court staff can lead AI innovation under the right conditions. By lead, I mean five steps: initiate, ask for approval, build, produce something, and report back.

A bridge gets built from both banks. My side was curiosity. My court's side was boundaries, and a manager who reviewed my proposals and said yes to small tests. Every pilot started the same way:

  • Approved in writing first
  • Public, redacted, or fictional sample data only
  • A person reviewing every result
  • A stopping point written down before I started Both court pilots stopped, and that is my favorite part of the story.

Write of Access tested whether a script could read handwritten entries on records request forms. I set a 90% accuracy bar before I started. It came in around 80%, so I stopped and looked at the misses. They clustered around checkboxes, signatures, and dates, where handwriting overlapped the printed form. The useful answer wasn't better technology. It was a form with less handwriting on it.

Hung Jury tried to automate part of our annual jury data report for the Judicial Council. I started on a Friday afternoon and stopped Monday morning. Three approaches hit the same wall: messy data in the source system. The existing Excel workbook was still the best tool for the job. The fix was a data conversation, not a coding project.

I'd rather find a dead end in a weekend than in three months.

After the pilots, I kept building outside of work. Themis Lex helps court staff see where AI can help in their role and where it must stay out. Verity Lex checks a California court's public record against the rules of court on AI. Both started with questions from my own job.

What I'd change

Building Bridges is a non-technical talk on purpose, and I say so at the start. It's about people, permission, and small tests, not code. So when I described the pilots, I wasn't thinking about the technical layer at all.

In Riverside, the concern I kept hearing was whether AI had run my pilots on court data. That's when I realized that for a court audience, how AI was involved might not be a technical detail. It might be the first question. Here's the answer I'd add.

Project What it was How AI was involved
Your Honor, I Object A weekend practice build before camp. Never a court pilot. An AI chatbot. It answers jury questions using public California law. Demo only.
Write of Access Court pilot ChatGPT helped me write Python. The code sent redacted sample forms to Amazon Textract.
Hung Jury Court pilot ChatGPT helped me write Python. No AI model processed the pilot data.

That table holds three different roles for AI, and I think they're worth keeping apart:

  • Generative AI answering questions. Only Your Honor, I Object does this. It was me testing myself before camp, and it never went near a court system.
  • AI helping me write code. ChatGPT did this for both pilots. It helped me write the Python scripts. It didn't run them.
  • Machine learning reading sample documents. Only Write of Access did this. My code sent redacted sample forms to Amazon Textract, an AWS machine learning service that reads printed and handwritten text from scanned documents. Textract doesn't generate conversational answers. It extracts text and structured information, like form fields, from documents. I checked every result against the bar I set before I started. Sending those redacted samples to Textract was part of the written pilot approval. I think that distinction matters most to people who are nervous about AI in courts, and those are the people the talk is for. Next time, it goes on a slide.

The repos

GitHub logo earlgreyhot1701D / your-honor-i-object-to-jury-duty-v9

Proof-of-concept chatbot for jury eligibility using CA legal code and AWS Bedrock

Your Honor, I Object (to Jury Duty)

🧩 Problem Statement

Jurors often have questions about their eligibility, the excusal process, and legal obligations that are difficult to answer without calling the jury office or reading complex legal code. This creates workload strain on staff, delays for jurors, and inconsistent access to accurate information. The goal of this prototype is to build a low-cost, legally cautious AI chatbot that can provide neutral, citation-backed answers using content from California Code of Civil Procedure §§190–242 and California Rule of Court 2.1008 This tool is designed to support, not replace, staff by answering common questions and guiding users toward the correct next steps.

⚠️ Demo Only – Not for Public Use

🔗 Demo (Loom): Watch the demo

This AI chatbot prototype answers jury-related questions using:

  • California Code of Civil Procedure §§190–242
  • California Rule of Court 2.1008

It uses Retrieval-Augmented Generation (RAG) with AWS Bedrock…

GitHub logo earlgreyhot1701D / write-of-access

Write of Access is a public-sector proof of concept using Amazon Textract to extract typed and handwritten data from scanned court forms. This repo includes sample inputs, output files, preprocessing scripts, and a validation template to support civic technologists exploring AI-enabled document workflows.

📄 Write of Access

Handwritten Court Form OCR with AWS Textract
Prototype to test extraction of typed and handwritten data from public court forms using Textract.


⚙️ Overview

Write of Access is a prototype project designed to evaluate the capabilities and limitations of AWS Textract for extracting typed and handwritten data from scanned court forms. It is particularly focused on structured forms like the Copy Request Form used in California trial courts.

This repo contains:

  • Textract-based OCR scripts
  • A sample scanned public form
  • Simulated OCR output files
  • Validation templates and documentation
  • Placeholder test architecture

📁 Folder Structure

Write_of_Access/
├── docs/
│   └── validation_log_template.md
├── input/
│   └── copyrequest (5).pdf
├── output/
│   └── sample_form_1_pg1_processed.txt
├── scripts/
│   ├── convert_and_preprocess.py
│   ├── textract_call.py
│   ├── textract_document_ocr.py
│   └── textract_test.py
└── README.md

📷 Visual Walkthrough

Input PDF Converted PNG Processed Output
copyrequest (5).pdf input/png/copyrequest_pg1.png output/sample_form_1_pg1_processed.txt

Note: Due to privacy restrictions, sample PNGs…

GitHub logo earlgreyhot1701D / hung-jury

Prototype automation of the California Jury Data Report (JDR). Explored PDF parsing, JSON mapping, and QC validation before concluding vendor data corruption blocks full automation. Shows initiative, technical skill, and professional judgment in knowing when to stop.

Hung Jury

When automation can’t reach a verdict.

Automation isn’t always possible, but exploring the limits creates clarity. **

This repository is a scrubbed proof-of-concept showing my attempt to automate the Judical Council of California's Annual Jury Data Report (JDR) process.

The project explored extracting data from Crystal Reports PDFs, cleaning it, and validating it against Judicial Council (JCC) business rules.

🚦 What I Tried

  1. PDF Parsing

    • Built a PyMuPDF parser to extract values directly.
    • Result: Failed. Crystal’s PDF output scrambled values (e.g., Q9 sub-questions shifted).
  2. Mapping Extraction

    • Created a JSON-based mapping to align questions with values.
    • Result: Worked, but only because values were corrected manually — not sustainable.
  3. Lean QC Engine

    • Built lean_jdr.py to apply all 12 JCC Manual rules.
    • Result: Confirmed my colleague’s Excel workbook was already correct, but added an independent validation tool.

🧾 What I Learned

  • Source data quality is the real constraint. Automation broke not…

I'd still say yes

If another court invited me tomorrow, I would say yes. I've been turning over what that says about me.

I think it says the message matters more to me than my comfort does. Enjoying something and finding it worth doing are two different things. Building with AI is both for me. Speaking, so far, is only the second.

In each of those rooms there was probably someone who asks why we do things the way we do them, and who tinkers with tools nobody assigned. That person is who the talk is for. I'd stand up again for them.

I'd still rather write it down. Next time, maybe with a coworker in the third row.


Your turn

What's the thing you'd do again even though you didn't enjoy it?


Drafted with Claude in October 2026 from my speaker notes for Building Bridges. The stories, the nerves, and the decisions are mine. Talk resources and templates: linktr.ee/ljcordero.

AI Assisted. Human Approved. Powered by NLP.

Top comments (17)

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build996 profile image
build996 •

The table about AI's role seems worth moving near the start of the talk, before the pilot results. 'AI helped write the script' and 'documents went to an external service' answer different questions for that audience, and the table makes both visible. I'd add one plain-language data-flow arrow per pilot so listeners needn't infer where a document went. Did the questions in Riverside change once you explained that distinction, or did the concern remain?

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earlgreyhot1701d profile image
Earl Grey •

That's a good idea. I think I unintentionally left out so more technical stops because I was concerned the audience would think I had too much tech in it. lol The concern did remain because I didn't explain it clearly enough. I only really thought about what they were asking after and how I could have explained it better. Plus since our courts are different sizes, mine is much smaller, I am able to have more flexibility to experiment. Because their environment is more restrictive they couldn't reconcile that.

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build996 profile image
build996 •

The difference in court size sounds like a useful part of the explanation itself: your room to experiment is a condition of the project, and their restrictions are conditions of adopting it. A short 'what would need approval in a larger court?' slide might help them separate an interesting prototype from something they could deploy tomorrow. That also gives their technical questions a practical destination instead of treating them as a request for more implementation detail. Were they mainly asking where the data went, or who could authorize using it?

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sizzlebop profile image
Jessica Doering •

This would absolutely terrify me! 😂 I can happily spend hours building something, experimenting, figuring out what works and what doesn't, but the thought of standing in front of a room full of people talking about it? That's a whole different challenge.

And I love what you said about the message mattering more than your comfort. That's a pretty powerful reason to keep showing up. Also, I appreciate your approach to the AI pilots, particularly recognizing when the technology wasn't actually the right solution. Sometimes figuring out what not to automate is just as valuable as building something that works.

Really enjoyed reading this. Especially the part about walking off stage and feeling relief rather than accomplishment. I think there's something really refreshing about admitting that even after doing something successfully three times, you still don't particularly enjoy it. I admire your willingness to keep putting yourself out there.

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earlgreyhot1701d profile image
Earl Grey •

@sizzlebop Thanks so much for reading! And for the record I was terrified. lol I think the biggest lesson I learned was that it was okay to not move forward if the pilot didn't work. But that was scary in itself since I was given the flexibility to try something new. That was difficult. And now thinking back worth it because sometimes the failure gave us a new solution we hadn't considered before.

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sizzlebop profile image
Jessica Doering •

I really like that perspective!.I think it's easy to get so invested in making something work that we forget stepping away from an idea can be just as valuable. Especially with AI, where there's sometimes this pressure to find a way to make it fit even when it isn't the best solution.

And I love that the failed pilots sometimes led to entirely new ideas. That's one of my favorite things about experimenting with technology. Even when something doesn't work out the way you hoped, you can still come away with something useful.

Also, I'm glad to hear you were terrified too. 😂 Makes me feel a little better about the fact that public speaking scares the hell out of me!

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sinarezaei profile image
Sina Rezaei •

I think there's a difference between getting comfortable with the material and getting comfortable being the person presenting it. You can know your subject inside out and still hate having everyone's attention on you.

One thing I'd find useful is using AI to rehearse the parts of a technical talk that are hardest to predict. Say you're presenting an AI-assisted workflow to an engineering team, and someone asks what happens when the model produces an invalid migration or silently drops data. You can practice answering those questions without relying on a perfectly rehearsed script, then try again with a skeptical audience or a live demo that doesn't go as planned.

There's research on virtual audiences and exposure-based practice for public speaking, too, so the idea of rehearsing in increasingly challenging conditions isn't just a productivity trick.

But I like that your story doesn't end with you suddenly loving public speaking. Sometimes the win is being able to do something worthwhile without needing to enjoy every part of it.

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earlgreyhot1701d profile image
Earl Grey •

Hi @sinarezaei Yes, I love this observation! "I think there's a difference between getting comfortable with the material and getting comfortable being the person presenting it." And it does feel like a win because I was able to overcome my nervousness and feeling of being an imposter in this space. We'll see if I get asked back to present again.

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sinarezaei profile image
Sina Rezaei •

That’s a solid win, especially because the confidence came from actually doing the work, not just preparing for it. I think the next interesting step is getting comfortable with the questions you can’t script. If someone asks why a pilot stopped at 80% accuracy, or how you know a model didn’t miss something important in a court record, being able to explain the failure criteria and why you decided not to proceed can be more valuable than delivering the slides perfectly. That kind of technical honesty builds trust, even when the answer is that the tool wasn’t good enough. Hope you get asked back!

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christopher_jakob_acda8fa profile image
Christopher Jakob •

"I trusted the work, even when I didn't trust myself to present it." That line is the whole post for me. And the second talk being harder makes total sense once you see how the brain handles this. Your subconscious decides what you notice through a filter called the RAS. After Albuquerque it didn't file the stage under "safe." It filed it under "now there's a bar." So in LA it went hunting for every reason the stakes were higher. Biggest court in the country, your court's name on the badge, hosts who were excited to have you. Same talk, way more threat data.

The relief instead of accomplishment is the tell. It means the alarm ran the whole time and you got through on willpower, which honestly is impressive. But you don't have to love speaking to stop dreading it. The ease you have when you write is already yours. It just hasn't been allowed into the room yet. When you get to the compliments on your list, notice the second right before you open your mouth. That's the same alarm, just smaller, and every time you go anyway the filter gets new data. Does not matter how it lands. The action is the win. Also, jokes landing with a room full of finance officers is a real win.

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earlgreyhot1701d profile image
Earl Grey •

Great insight on why the 2nd talk was more difficult. At first I didn't understand why, I just felt significantly more pressure. There was definitely more threat data!

I think noticing more, being present more and adding complementing a stranger will help my nervous system not be on red alert as much. Here's to hoping!

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christopher_jakob_acda8fa profile image
Christopher Jakob •

That pressure you felt was the threat data, so now you've got a name for it. Noticing and being present is a big part of it. The alarm usually gets loudest when you're stuck in your head, so getting back into the room calms it down. And the compliments give it proof from somewhere new. Let me know how the first one goes.

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tdk-cli profile image
tdk-cli •

cool!

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earlgreyhot1701d profile image
Earl Grey •

Thanks!

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tdk-cli profile image
tdk-cli •

np!

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mohsen_jr profile image
Mohsen jr •

I like the contrast here: AI opened doors you didn't expect, but it didn't magically make public speaking enjoyable. Sometimes growth means doing something you're still uncomfortable with, not necessarily learning to love it.

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dpietro profile image
Denise Pietro •

This is such an honest and useful write-up, and the line that stays with me is that you liked the message more than the microphone. Separating “enjoying something” from “finding it worth doing” is a distinction more people should make, and it explains why you’d still say yes to a fourth invitation. I loved that both court pilots stopped by design: setting a 90% accuracy bar before starting, landing around 80%, and concluding the answer was a form with less handwriting rather than better technology is exactly the judgment courts want from frontline staff. Hung Jury is my favorite, since discovering over one weekend that the existing Excel workbook was already the best tool is the kind of dead end worth finding early. The “what I’d change” section is a model of good reflection, and the table separating generative AI, AI-assisted code, and machine learning reading redacted sample forms is the clarity nervous audiences need. Also, listening to your own talk as an MP3 in the car is a great rehearsal trick. The approval-first, sample-data-only, human-reviewed, stopping-point-written-down framework makes “frontline staff can lead AI innovation” feel like something others can copy. Congratulations on three stages, and on the laughs from a room full of finance officers.