I shipped enterprise software for decades without AI. Then Claude Code changed how I build — forever.
For 20+ years I delivered Fortune-500 systems the long way — every design doc, every line, every test by hand. The past couple of years I’ve gone all-in on AI tooling: research, architecture, diagrams, code, tests, and whole-codebase migrations now run through Claude Code, Gemini CLI, and custom MCP servers, and I review every pass myself. The result on real engagements: roughly 4× delivery acceleration — judged by an engineer who knows exactly what the output should look like. This page is about how I build with AI; building AI into products lives on my AI & Machine Learning page.
How I Work AI-First
Six practices, applied on every engagement.
AI-Accelerated Engineering
Research, spikes, and scaffolding in minutes instead of days — so I iterate and test faster, explore more options, and spend my time on the decisions that matter instead of the boilerplate.
Agentic Migration Pipelines
AI agents that analyze and port whole codebases — multi-pass loops that generate documentation, feed it back to the model, and iterate — producing deterministic output that I review on every pass.
Custom MCP Servers
I build Model Context Protocol servers that extend Claude with client-specific tools and context — your repositories, your APIs, your domain knowledge — so the model works inside your world, not a generic one.
Multi-Model Fluency
Claude, Gemini, ChatGPT / Codex-style code models, GitHub Copilot — I pick the model per task and benchmark them against each other on real work, not vendor slide decks.
AI-Assisted Architecture & Docs
Design docs, C4 and Mermaid diagrams, deployment diagrams, and Confluence documentation produced with AI and reviewed by me — documentation that keeps pace with the code instead of trailing it.
Team Enablement
I set up Claude Code for engineers and PMs, teach MCP architecture, and coach teams on prompt engineering — so the acceleration stays with your team after I’m gone.
The Daily Toolchain
The tools I actually build with, every day.
Daily Drivers
Built by Me
The Practice on Real Engagements
Not a lab exercise — how I deliver.
An AI Agent Porting 350+ Codebases from AWS to GCP
For a national healthcare technology platform, I built an AI agent in TypeScript running Claude on AWS Bedrock with custom MCP servers to analyze and port 350+ FHIR/HL7 codebases — multi-pass documentation loops, three Claude models routed per task, roughly 4× faster than manual porting, with me reviewing every pass.
See the engagement My Product · AI-First BuildGrade My Investments — 195K Lines, One Architect, Six Months
My own SaaS is the receipt for the practice: I built the entire 195K-LOC system AI-first, solo, in six months — and Claude is also built into the product as the language layer over a deterministic ML.NET core, with a monthly cost cap on production AI spend.
See how it’s builtAI-Accelerated Delivery Inside Fortune-500 Engagements
The everyday practice: evaluating container scanning, observability, and cloud services with AI research loops; producing architecture diagrams and design docs with AI; and teaching client engineers and PMs to set up and use Claude Code and MCP on their own work.
The daily default on every engagementThe Governance Behind the Speed
Acceleration without oversight is just faster mistakes. Mine comes with rules.
Nothing ships unreviewed
AI output never goes to production without me reviewing it — every migration pass, every generated diagram, every scaffolded service. The model accelerates the work; it doesn’t get the final word.
Deterministic cores where it counts
Where correctness matters, I build deterministic cores with AI language layers on top — the pattern running in Grade My Investments, where ML.NET does the repeatable math and Claude handles the language.
Cost-capped in production
Production AI usage runs under hard spend limits — GMI enforces a monthly Claude cost cap — so the AI-first practice never turns into an open-ended bill.
Looking for AI inside your product?
This page is about how I build software with AI tooling. LLM features, AI agents, RAG, and machine learning built into products live on my AI & ML page.
Want your delivery to move this fast?
I bring the AI-first practice — and the architect who reviews every pass — to your next build or migration. Corp-to-Corp engagements out of Dallas / Ft. Worth.