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Setting Up The First JUVO Lab Town Hall

Tony Wood |

So, this all started with me just sitting down, setting up the very first town hall for JUVO Lab in JUVO. There is a lot to share. What we are doing, how things are working at JUVO Lab, and what we want to get out of these big monthly sessions.

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But the real story is how I got the job done.

On paper, it is a standard leadership task. Align the team, share progress, set direction. In practice, it is a heavy lift. Slides, agenda, narratives, highlights from projects, who needs to speak, who needs context, and how to make the whole thing useful, not performative.

In the past, that would mean days of writing, cutting, rewriting, and chasing updates. This time, I decided to treat the town hall as an experiment in how far I could lean into agentic work.

Choosing An Agentic Crew First

Being agentic first is our way. So, rather than prepping everything by hand or typing up pages of notes, I kicked off by building an agentic crew.

I fed it:

  • The structure of the town hall.
  • The list of projects and owners.
  • Background research and metrics.
  • The attendee list and what they care about.
  • The outcomes I wanted from the session.

It took a little more effort upfront. I had to think clearly about roles, prompts, inputs, and outputs. But the payoff was immediate. Instead of one-off assets, I now had a reusable crew that could:

  • Draft the narrative and key messages.
  • Propose slide outlines and supporting detail.
  • Flag gaps or risks in the story.
  • Package follow up actions and summaries.

Next time, I do not start again. I only update the inputs. Each town hall becomes an iteration, not a fresh mountain to climb.

Interestingly, this is not just my personal hunch. As one major consultancy has put it:

"Agentic organisations—powered by AI agents—are fundamentally altering the way work is structured, making processes more iterative, reusable, and responsive to real-time data."

That sentence could be a direct description of what happened in my morning. I built the town hall once as a crew. Now it is an asset for every future session.

My 2008 Iron Man / JARVIS Moment

While all this was running, I got a full-on flashback to 2008, sitting in the cinema watching Iron Man for the first time.

You know the scenes. Tony Stark in his lab, talking to JARVIS, building the suit in this vivid, living conversation. Holograms. Screens moving in mid air. Constant back and forth as he tweaks, rebuilds, and tests live.

I remember thinking:

I want that. I want to talk to my work like that.

Back then it felt like pure fantasy. A playful version of the future, good for popcorn and nothing else.

What hit me, sitting at my desk in 2025, was this. I am doing the same thing, in a much less glamorous office chair, with an AI stack instead of holograms. The JARVIS moment is not a demo video any more. It is my Saturday morning.

And this is not only my experience. One writer recently captured that shift perfectly:

"What once belonged in the realm of science fiction—talking to your computer and having it understand, advise, or build for you—is rapidly becoming a normal part of digital workflows, thanks to AI agents inspired by visions like Iron Man’s JARVIS."

That is exactly what it feels like. Sci fi as standard operating procedure.

Talking To Cursor Instead Of Typing

The biggest mental shift for me has been how I interact with the work.

Instead of hammering a keyboard, I talk to tools like Cursor and my agentic crew in plain language. I explain:

  • What the town hall needs to achieve.
  • How I want the agenda to flow.
  • Which examples land with which audience.
  • What to cut because it is noise, not signal.

The tooling does the heavy lifting of turning that intent into code, content, structure, and assets.

This aligns with a broader shift in how people are building software and workflows. One description I like puts it like this:

"With vibe coding, you tell the computer what you want in plain English and—almost like magic—the code or component you need is generated before your eyes."

That phrase captures what it feels like when you first drop the habit of “thinking in slides” or “thinking in code” and start thinking in intent.

As a leader, that matters. It means:

  • You can stay in problem and outcome space longer.
  • You can delegate more of the translation work to machines.
  • You can involve more people, because the interface is language, not syntax.

The old gap between “I know what I want” and “I can make it real” is shrinking fast.

From A Week Of Work To Six Hours

So what actually happened with the town hall build.

I started at 6am.

By noon, I had:

  • A working agentic crew for town halls.
  • Draft narratives for each section.
  • Suggested talking points for key leaders.
  • A summary for people who could not attend.
  • A checklist of follow ups and owners.

Historically, that would have been a week of my time, minimum. More if I had to:

  • Brief someone else.
  • Wait for a draft.
  • Mark it up.
  • Go back and forth.
  • Fix gaps on the eve of the event.

Instead, I ran about ten iterations in six hours. Each loop, I could see the result, adjust the instructions, and run again.

Outside my little bubble, the data is moving in the same direction. One major engineering team notes that:

"At a high level, more than 60% of developers surveyed reported that AI coding tools make them more productive, freeing up time that is redeployed to higher-value work like learning new skills, reviewing code, or collaborating with colleagues."

That is the real leverage. It is not just that we are faster. It is that the time we win back can be spent on higher quality thinking, better collaboration, and more experiments.

Another research group studying copilot style tools observed that:

"We observed that Copilot integration can decrease the time required to complete programming tasks while increasing overall code quality and documentation coverage."

Productivity without quality is a false win. The encouraging signal here is that we are seeing speed and robustness improve together when people use these tools well.

My six hour town hall sprint is one small example of the same pattern.

Why This Matters For How We Work Now

It is tempting to treat this as a cool personal story. Fun, but not especially relevant to the rest of the organisation.

I think that would be a mistake.

What is changing is not only speed. It is the shape of work.

Agentic crews and conversational tools mean:

  • More work is front loaded into designing systems, not documents.
  • The first version takes a bit longer, because you are building a reusable pattern.
  • Every run after that is cheaper, faster, and easier to adapt.

For leaders, a few implications stand out.

1. You should assume agentic reusability by default

If a task repeats:

  • Design the agentic crew once.
  • Store it where others can find and adapt it.
  • Expect teams to refine, not reinvent.

This is how you compound learning instead of scattering it in people’s inboxes.

2. Natural language is now a core interface, not a gimmick

If work can be steered by language:

  • People closest to the problem can drive the tools.
  • You rely less on translators and gatekeepers.
  • You can have more direct conversations with your systems.

That has big implications for training, hiring, and how you define “technical” roles.

3. Governance has to keep up

When anyone can spin up a powerful crew, guardrails matter. You will need:

  • Clear standards about data, privacy, and compliance.
  • Simple ways to review and approve agentic workflows.
  • Shared patterns so you do not reinvent safety every time.

The good news is that many of these patterns already exist in software engineering and operations. The shift is that they are now relevant to almost every function, from HR to finance to marketing.

Leadership Reflection: What This Means For You

If you are in a leadership role, you do not need to become a full time prompt engineer. But you do need to update a few mental models.

Here are some practical questions to sit with.

  • Where are you still treating repeat work as if it is a one off.
  • Which processes could be turned into agentic crews that anyone can run.
  • How comfortable are your teams with talking to systems in plain language, instead of filling in forms.
  • What would it change if a “week of work in six hours” became normal in your organisation.

This is not about chasing another buzzword. It is about:

  • Shorter cycles from idea to impact.
  • More capacity for experimentation.
  • Less friction between vision and execution.

The Iron Man reference is playful, but the stakes are real. The organisations that learn to work with agentic crews and conversational interfaces will move faster, learn more, and waste less energy on translation.

The ones that cling to slide decks and manual updates will feel slower and heavier every quarter.

A Simple Next Step

You do not have to start with a full town hall.

You could:

  • Pick a single recurring meeting or report.
  • Spend one morning turning it into an agentic crew with a conversational interface.
  • Run it side by side with your old process once.
  • Decide which version you want to live with.

Then, as you gain confidence:

  • Share the pattern.
  • Invite volunteers from other teams to adapt it.
  • Collect stories about what people are now doing in “six hours” that used to take them a week.

At some point, you may look up from your own desk, or your own kitchen table at 6am, and realise you have had your own JARVIS moment.

What used to be a film effect is now just how you work.

Call to Action: Treat one piece of repeat work as your “Iron Man experiment”. Turn it into an agentic crew you can talk to, then see what a six hour sprint can do. What could you try in the next 24 hours and the next few weeks?

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