AI Systems
AI implementation engineer for teams that need to ship fast, not hire big
I build AI-augmented systems and production software using Claude API and modern tooling. The goal is compressing weeks of engineering into days — scoped precisely, verified carefully, handed off cleanly.
What I do
Practical architecture, production code, and clean delivery.
Scope AI integration precisely so the system solves one real problem instead of promising everything.
Build with Claude API, AI SDKs, and modern tooling to compress implementation timelines dramatically.
Verify every AI-generated output before it ships — fast delivery without unverified bugs.
Hand off clean, maintainable systems that existing teams can extend after launch.
Approach
I make the constraints visible before the implementation hardens.
Define the problem sharply before touching any implementation — vague prompts produce vague software.
Use AI for implementation load while maintaining full ownership of correctness and product decisions.
Iterate fast, verify each piece, and keep the architecture simple enough that the result is maintainable.
Deliver a working, tested system — not a prototype that requires a second team to make production-ready.
Public proof
Recent work and technical writing.
The projects below were built with a bias toward speed and correctness over process. Each one started with a clear problem definition and ended with a deployed, tested system — not a demo.