HYBRID - Build Your Own AI Inventory Advisor

*** Hybrid workshop hosted by Aarti Gupta (LinkedIn) ***

🎟️ RSVP here & Complete your registration via: WS Registration - Intelligent Inventory Advisor – Fill out form

• 🪑 In-person seats capped at 15 · online at 10
• 💶 Early bird €25 (first 10 seats) → then €38
• 🏷️ First 5 Learn & Build members get a special price. Register early to claim it
• 💻 Online attendees: the MS Teams link will be posted in the event comments on the day — please check there before we start!

🧰 Build a working AI decision tool and walk out with it running.

You’re about to spend €1,199 on the new phone—but is it actually better than the one in your pocket, or just newer? Or the €180 AI tool subscription that just auto-renewed, when you already pay for two tools that do most of the same job. Both times, comparing properly takes an hour you don’t have. So you do the maths in your head (badly!) and buy it anyway.

In this hands-on afternoon, you’ll build a tool that does that comparison properly—your personal Inventory Advisor. Point it at anything you’re about to buy or renew, and it checks what you already own, compares, and gives you a straightforward, reasoned verdict: buy it, or skip it.

But the inventory tool is only the vehicle! What you’re really learning is a repeatable method for building intelligent decision tools with AI—the kind of thing you can point at any problem in your work or business afterward. Pricing. Hiring. Which supplier. Which feature to build next.

The trick is the *“delta engine” pattern*: instead of letting the AI chat at you, you make it score the gap between what you have and what you’re considering—and justify the call. Once you’ve built one, you can build ten.

By the end of the afternoon, you will have:
✅ A repeatable method for going from Ideation to prototyping with AI
✅ A working prototype running on your own machine—not slides, a real tool
✅ The full source code, yours to keep, extend, and recycle
✅ A clear grasp of the “delta engine” pattern—how to make an AI weigh options and justify a recommendation, not just chat

What we’ll actually do (3 hours):
1.⁠ ⁠Frame the problem like a builder—data model, capture, the decision logic
2.⁠ ⁠Build the inventory + capture flow together, step by step
3.⁠ ⁠Build the recommendation engine —the part that makes it intelligent
4.⁠ ⁠Test it live with your own examples, and take your questions

Who this is for:
Developers, founders, makers, and the AI-curious who learn by building. You don’t need to be an expert—if you can follow along and aren’t afraid to type, you’ll keep up. Bring your curiosity and one decision you keep making badly.

What to bring:
A laptop, and an open, focused mind.

Looking forward to seeing you there!