Move to an online deliverable without mistaking a prototype for a product

Lesson objective

By the end of this lesson, you will be able to choose between a page, a small app, a shared assistant and an automation for your need, and list what remains to be done before opening the result to customers.

Topics covered

• prototype
• automation
• shared AI assistant
• AI agent
• going live

Where it fits

Capture it and share it with the team

How do I turn a good result into a reusable, shared method without losing control?

Lessons in this module

1. Turn a good result into a reusable workflow
2. Move to an online deliverable without mistaking a prototype for a product (this lesson)
3. Write your team's AI policy
4. Your 30-day plan and resources

What you will learn in the course

This lesson is part of the course Put AI to work in your business

• Explain, on a concrete case, why an AI assistant makes things up, forgets or misses recent information, and decide how to use it accordingly.
• Sort data before giving it to an AI tool (allowed, anonymize first, forbidden) and configure the tool to match.
• Choose which tasks to hand to AI and how to work with it (automate, assist, delegate) based on value, risk and the data involved.
• Write a complete request (task, context, examples, format, constraints) and improve it over at least two documented iterations.
• Pick the right tool for a deliverable and justify the choice on data, cost, licensing and integration.
• Check AI output against an explicit checklist (facts, figures, sources, tone, compliance) before using it.
• Turn a successful use into a reusable workflow with human checkpoints, and set the team's rules of use in an AI policy.

Related courses

• Understand what LLMs do well, and where they failAll levels · ~2 hr
• Choosing and using AI tools at workAll levels · ~1 hr 40 min
• Prompting for product managers: delegate, describe, verifyJunior · ~2 hr 45 min