Running is not the same as ready.
A system can be running and producing real evidence without yet being ready for UAT, release, production or the next meaningful action.
Read Journal #9TechJinni Journal
Notes from building real products with AI agents.
What worked, what failed, what changed my thinking, and what I am still trying to understand. Written from experience, without pretending the work has produced a finished doctrine.
I don’t want more automation. I want less unnecessary human work.
As AI agent workflows become more autonomous, I’m becoming more interested in which human involvement reflects real judgment and which is only operational plumbing.
Read Journal #8
Working with AI has less ego. I’m not sure that’s always an advantage.
One of the things I have come to appreciate about working with AI is how little ceremony there is around changing my mind.
Read Journal #7
A rubber duck that evolves with usage, not time
Repeated use can make an AI assistant more useful before the model changes at all, because less of the working context has to be rebuilt from zero.
Read Journal #6
Ask why you need AI before asking where to put it
Using AI to build a product and building AI into the product are separate decisions; what matters is the improvement it creates.
Read Journal #5
AI stopped being just a coding tool for me
Somewhere between implementation, product decisions, debugging and delivery, “coding assistant” stopped describing how I was actually using AI.
Read Journal #4
When a small internal tool starts becoming a product
The first version solved the problem I could see. Real use revealed the workflow around it.
Read Journal #3
HoursKZ started as a very small problem
I wasn't trying to build workforce software. I wanted to stop tracking employee hours manually in my coffee shop.
Read Journal #2
I started keeping notes on what AI changes in product work
The product changes were easy to record. What changed my mind was harder to keep.
Read Journal #1