When something works exactly as expected, there usually isn’t much mystery left.
Was the problem in the interface, the network, the database, the user, or somewhere deeper?
Most people do not care how a request is routed, how authentication is validated, how a database transaction is handled or how an AI model receives context.
I want to know what assumptions the developer made and what happens if those assumptions are wrong.
Security often lives in the gap between what a system appears to do and what it actually allows.
One of the strangest things about programming is that the more I learn, the less I feel like I know.
Then you start learning about authentication, caching, queues, rate limits, browser behaviour, network failures, accessibility, search engines, deployment, monitoring, observability and security.
A model can be extremely intelligent and still be useless if the system around it is badly designed.
I’ve never been very good at learning something just because I’m supposed to know it.
I’ll probably make mistakes that someone with more experience would avoid immediately.
There is a big difference between reading that something is a bad idea and spending six hours discovering why it is a bad idea.
My main project, Zenith, is technically a website monitoring and improvement platform.
It makes programming feel less like writing instructions for a computer and more like working inside a system built by people.
Not just how to build them, but how they behave when something unexpected happens.
That matters more to me now than memorising every framework or programming language.
I build software, experiment with AI, contribute to open source and spend an unreasonable amount of time trying to understand why things behave the way they do.