AI Development for Dummies (I’m the dummy) - plus resources from the real experts

It seems like every product on here these days is AI.

And every AI team is outstanding (I’ve even spotted a few in the same category as Meet-Ting - which I actually love, nothing better than building to save people time and bring humans together).

But let’s say you’re in the 0.1% not already building with AI - or you’re on the non-technical side of the founder house, like me.

What’s it really like to move from prototype to closed beta with an AI product?

Some of this might be basic for a lot of esteemed brains here, but if you’re a “dummy” like me, hopefully this guide helps:

• Your devs need to know how to work with AI. Experience really matters - it’s not traditional software development.

• AI isn’t binary. You need an eval framework to measure progress across multiple possible outcomes.

• It’s all about constant testing - and you need real human data to do it.

• Our biggest challenge: every new “golden set” (learning example) comes from a customer having a rough experience. If anyone has ideas on how to expand real-world testing without burning user trust, my DMs are open!

• You can’t get to “delightful” without an eval framework - and you also need to define clearly what delightful means (ongoing discussion with Ting CTO...).

Wrote more about this (from the POV of a first-time founder, aka the dummy, me) on Substack here: https://chiefting.substack.com/p/ai-development-for-dummies-im-the