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How to Run an Engaging Hands-On AI Workshop for Your Team

Teach a team to use AI by having everyone build the same small app, compare how the outputs differ, repair failures together, and then push the working result in a personal creative direction.

How to Run an Engaging Hands-On AI Workshop for Your Team

Brian combines biweekly Product AI sessions with a public Slack channel, has everyone build the same Bolt to-do app, uses failures as live debugging practice, and ends with playful creative iterations.

Before you start

What you need

  • A recurring session and public sharing channel
  • An approved browser-based builder tool
  • A simple prompt and a finishable exercise
  • Facilitators who can help with access and errors
  • A place to save examples and lessons

What you’ll make

A working first prototype for each participant, shared evidence of model variability and repair strategies, and a repeatable habit of peer learning.

Tools used

Step by step

The workflow

Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.

5 steps

Step01

Establish a Structure for Learning

Schedule a recurring hands-on session and open a public channel for prompts, experiments, failures, and questions. Choose one approved tool and send account setup before the meeting.

Step02

Design a Hands-On Kickoff Exercise

Give everyone the same small, finishable assignment, such as a to-do app in Bolt. State the minimum working behavior and let participants run the prompt at the same time.

Example prompt
Create a simple to-do application. Users can add a task, mark it complete, and delete it. Keep the first version small enough to run in this session. Explain how to launch the preview and report any error in plain language.

Pick a tool with a very low barrier to entry that produces a visual or tangible result quickly to maximize engagement.

Step03

Demonstrate AI's Variability

Compare the results as a group. Note visual and behavioral differences, then repair a few failures live using the error message and observed behavior rather than starting over.

Example prompt
The preview failed with this error: [error]. Inspect the current project, explain the likely cause, make the smallest repair, and confirm that adding, completing, and deleting a task still work.
Step04

Use Errors as a Teachable Moment

Give participants a menu of visual, interaction, media, and playful changes. Ask each person to choose one, improve the working app, and share the prompt plus result in the public channel.

Step05

Encourage Creative Exploration

Close by naming reusable prompting and debugging patterns, assigning owners to capture them, and announcing the next session topic based on participant questions.

Example prompt
Try modifiers like '...add a retro 8-bit pixel art theme' or '...make it look like MySpace from 2007.'

What good looks like

  • Most participants reach a working result during the session.
  • Failures become documented repair examples rather than private dead ends.
  • Participants can explain why identical prompts produced different outputs.
  • The public channel remains active between sessions with useful examples and questions.

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After the steps

Runbook notes

How to recover when the loop fails and where human judgment helps.

Recover

If it goes sideways

Account creation or tool access consumes the exercise
Send setup instructions early, verify access at kickoff, and provide a paired or demo path for blocked participants.
Participants interpret an initial error as proof they cannot use the tool
Debug one failure live, model a concise repair prompt, and let participants retry before changing tasks.
The session turns into a presentation with little tool use
Time-box the introduction and reserve most of the session for building, comparison, and iteration.
Experiments disappear after the meeting
Save prompts, outputs, fixes, and owners in the public channel and open the next session with one reused example.

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