Years of pattern recognition
From 8-bit BASIC to distributed systems, product code, data tools, and modern AI-assisted development.
Programming since Apple ][+ BASIC. Shipping with AI now.
I help small teams turn AI coding tools into production code: fast prototypes, real releases, fewer theatrics, and code that can survive Monday morning.
The unfair stack
The trick is not coaxing an LLM into writing files. The trick is knowing what to ask for, what to delete, what to test, and what should never have been generated in the first place.
From 8-bit BASIC to distributed systems, product code, data tools, and modern AI-assisted development.
High-volume output matters only when it passes review, lands cleanly, and makes the team faster after the merge.
Low-maintenance, collaborative, production-minded help for founders and engineering teams that need leverage.
Clickable proof
A few public trails from the current workbench: AI evaluation, MCP usability testing, network telemetry, browser automation, embedded devices, local LLM infrastructure, and writing about the strange new practice of pairing with machines.
Utilities for comparing one-shot prompts across LLMs and agent CLI tools.
View repository GitHub / MCP usabilityA dual-agent harness where one model uses the tools and another watches for friction.
View repository GitHub / Browser automationA headed Playwright crawler for first-pass UI exploration and practical web inspection.
View repository GitHub / Rust network scannerRust packet capture, Nmap device enrichment, SQLite persistence, and a Leptos dashboard.
View repository GitHub / Local AI stackLocal LLM stack on Intel Arc Pro B70: llama.cpp SYCL, llama-swap, opencode, and pi.
View repository GitHub / Embedded Telegram botA Raspberry Pi Pico W wellness bot that pings people and alerts a buddy if they miss.
View repository LinkedInArticles, career context, and older receipts that live better on the professional timeline.
Open LinkedIn BlogNotes from the front line of AI-assisted development, judgment, workflow, and taste.
Read the blog
What this actually looks like
I use AI to fan out implementation, tests, refactors, data wrangling, UI passes, and debugging. Then I bring the grown-up parts: architecture, taste, sequencing, review, and the nerve to say no.
Ways to use me
Find where AI can speed your team up without flooding your repo with expensive confetti.
Turn a messy idea into working software, then harden the parts that need to last.
Add practical AI coding horsepower plus decades of engineering judgment, without a full-time hire.
Use AI to map, refactor, test, and retire old code carefully, with someone who remembers why it exists.
The ask
A feature stuck in planning, a codebase nobody wants to touch, a team curious about AI but allergic to hype. I will help you make it move.