Open-source AI models and the ecosystems around them
I keep circling back to open models, local-first experiments, and the part of AI work that gets interesting once the hype leaves the room.
Personal portfolio, blog, and open notebook
Charles yapping zone
I lead Quality Assurance efforts at DT One, spend a fair amount of time politely annoying engineers, and remain deeply obsessed with open-source AI models, useful tools, and the kind of experiments that turn into stronger opinions.
Currently exploring
Things on the workbench
Quality systems that make engineers mildly uncomfortable for good reasons
A decent chunk of my brain is occupied by test strategy, release confidence, and the subtle art of bothering engineers until the software behaves.
Experiments that teach faster than a roadmap
Short cycles, sharp feedback, and enough curiosity to ship a prototype before the idea calcifies into a slide deck.
Recent writing
Fresh from the notebook
Learning in public without turning your brain into a vending machine
Notes on sharing work online without reducing every idea to content bait.
The part of AI product work that is still mostly taste
AI can generate, classify, summarize, and autocomplete, but none of that replaces judgment.
Side projects are my favorite small laboratories
Why I keep building tiny things that may never become companies and still feel worth the effort.
Speaking and community
Public-facing, but still a real person
Meetups and community nights
I like rooms where engineers swap notes, disagree politely, and keep the conversation going in the parking lot or Discord afterward.
Talks that favor clarity over theater
I enjoy speaking about engineering practice, AI ergonomics, and the awkward reality between “in theory” and “in production.”
Internet corners with signal
Newsletters, issue threads, open source discussions, and small communities where people still care about taste, craft, and better questions.
Find me online