I have one of those careers that requires a slightly longer explanation at parties.
I've worked across technology, consulting, business intelligence, public health, organizational strategy, education technology, product development, and artificial intelligence.
The job titles changed. The work, strangely enough, didn't change that much.
I tend to end up somewhere between a complicated problem and the people trying to solve it.
I'm fascinated by how organizations actually work.
Not how the org chart says they work. How they actually work.
Every organization has a second operating system underneath the official one: relationships, spreadsheets, institutional knowledge, workarounds, email chains, old processes nobody remembers creating, and that one person everyone quietly knows you have to call when something breaks.
Understanding that system is often more important than understanding the technology sitting on top of it.
My work has included strategic planning, organizational performance, executive leadership structures, funding strategy, operational improvement, program design, and building teams and systems capable of carrying all of it.
I came to technology through problems rather than technology itself.
That's probably why I still approach it differently.
I'm comfortable moving between the strategic and technical layers of a problem—from talking with leadership about what an organization needs to building a prototype to see whether the idea actually works.
Business intelligence led deeper into data. Data led into software. Software led into AI. And AI blew the doors off the workshop.
Today I spend a significant amount of time building with modern AI systems, experimenting with AI-assisted software development, developing AI-enabled products, and thinking about what this technology changes beyond the obvious chatbot sitting in the corner.
I like making things.
Software. Systems. Teams. Strategies. Dashboards. Products. Occasionally unnecessarily elaborate spreadsheets.
Building forces clarity.
A PowerPoint can hide a fuzzy idea surprisingly well. Working software is less polite. It either does the thing or it doesn't.
That's one reason AI-assisted development interests me so much. It has dramatically reduced the distance between thinking about an idea and testing one.
When prototypes become cheap, curiosity becomes a development strategy.
Before much of this, I was a professional musician.
Which sounds unrelated until you've spent enough time building things.
Music taught me iteration, collaboration, improvisation, performance, obsession, and the uncomfortable reality that something can be technically correct and still not work.
Those lessons transferred surprisingly well.
Organizations have rhythm. Products have composition. Teams improvise. And every once in a while, despite everyone's careful planning, the drummer counts off and you discover you're all playing a different song.
You learn to listen.
Jason Matthew Howes