Day 55, and I'm past the halfway point of building an AI product in 100 days. This one looks back at the first 50 days and lays out the plan for the last 45.
The biggest lesson so far: I thought building the app would be the hard part. It isn't. Figuring out what to build, how it fits into the business, and what the next offer should be is still way harder.
The PLG analyzer now gets about 8 out of 10 recommendations right. I'm not willing to trade quality for cost or speed, so getting that to 99% comes first.
The money side hasn't worked yet. The analyzer was meant to lead to working with a ProductLed operator, but most of the people using it run small companies, and they're hard to serve at that price point. Meanwhile the free product costs about $1,300 a month to run, developer included.
So the plan for the next 45 days is one new enterprise client, won through blind calls: analyses of companies I already want to work with. Every one of them also trains the analyzer to give you better recommendations.
IN THIS EPISODE
00:00 Day 55, and what I'm building
02:09 Your feedback, from "about as good as ChatGPT" to three scans in a row
03:05 Building the app was never the hard part
04:01 Highlights: shipping, Matt Pocock's skills, new friends
05:20 Lowlights: why 8 out of 10 isn't good enough
06:58 Building an app has no training plan
08:33 The game plan for the last 45 days
09:36 Why the operator offer hasn't worked
10:45 A free product that costs $1,300 a month
11:22 Pay for itself, fit the business, fix quality
13:08 How my advisory work actually runs
14:24 Blind calls: account-based marketing that trains the AI
15:29 One enterprise client and 99% good outputs
16:36 Next: turning internal workflows into products
17:54 What's your take?
MENTIONED
Run the free PLG analyzer: https://productled.com
Matt Pocock's skills: https://github.com/mattpocock/skills
Wes Bush on LinkedIn: https://www.linkedin.com/in/wesbush/
What's the biggest challenge you've hit building an AI product?
