This workflow provides a step-by-step guide for running an interactive workshop to get non-technical team members excited and comfortable with using generative AI tools, fostering a culture of experimentation.
with Claire Vo
Create a dedicated time for hands-on learning, such as a bi-weekly 'Product AI' session. Supplement this with an asynchronous space, like a public Slack channel, for continuous sharing of articles, experiments, and questions.
Choose a simple, accessible tool for a live exercise. Brian used bolt.new, where you can create an app from a text prompt. The goal is to get everyone to *use* AI, not just listen to a presentation.
Have everyone in the workshop use the exact same prompt to create a simple app (e.g., a to-do app). This will show how AI can generate wildly different results from the same input, which is a key learning.
Example prompt for bolt.new: 'Create a simple to-do list application.'When some of the AI-generated apps have errors or don't work, frame it as a positive. This becomes a practical lesson on the iterative nature of working with AI and the importance of refining prompts and outputs.
After the initial exercise, encourage participants to 'go wild' with creative modifiers. This helps them see AI as a creative partner and makes the experience fun and memorable.
Try modifiers like '...add a retro 8-bit pixel art theme' or '...make it look like MySpace from 2007.'
Follow Sahil Lavingia's method for delegating small but impactful maintenance tasks, like fixing an internal Slack report, to the AI agent Devin. This workflow shows how to use simple, clear prompts to fix code and update system prompts without distracting your engineering team.
Learn Gumroad CEO Sahil Lavingia's process for rapidly prototyping a UI with v0, then using the AI agent Devin to autonomously code, implement, and submit the feature for review, turning a multi-day task into a one-hour workflow.
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