Field guide
Build software fast
Most teams do not ship slowly because they lack talent. They ship slowly because they optimize for completeness instead of momentum. Here is how to fix that, and how I help teams do it.
Not ready to commit? Book a free 15-minute call. I will tell you honestly whether a 3-day build is realistic.
The real bottleneck
Engineering teams are drowning in choice. AI coding assistants generate more code than ever, but that code still needs tests, review, integration, and a production home. The result is not faster shipping; it is a wider surface area to maintain.
The teams that ship fast have one thing in common: they treat scope as a weapon, not a negotiation. They pick a small, real problem, solve it in days, and put it in front of a user. Then they iterate.
This page is a short field guide to that approach. If you want someone to execute it with you, I am available.
Four rules for fast builds
Start with the demo
Do not design the architecture first. Pick the one-screen demo that proves value, and build toward it. Everything else is a distraction until that demo works end to end.
Scope to three days
If a first version cannot ship in three days, cut scope until it can. Three days forces clarity. It also forces you to reject nice-to-have features that do not serve the demo.
One sharp toolstack
Use one language, one framework, one database, and one deployment target you already know well. Novelty is the enemy of speed. Prove the idea first, then optimize the stack.
Ship to a real user
Internal demos do not count. Put the work in front of a real user on day one. The feedback you get is the only compass that matters for what to build next.
How AI changes the equation
AI is not a replacement for judgment. It is a multiplier for execution. The right way to use it is to automate the parts of building that are repetitive but low-risk: scaffolding, tests, docs, deployment plumbing, and boilerplate.
The wrong way is to let it generate the whole system and hope it hangs together. That produces impressive demos and brittle production systems. Fast builders use AI to remove friction, not to make architectural decisions.
My own workflow combines agentic coding tools with rigorous CI/CD, memory-safe languages, and hermetic builds. The goal is not more code. It is less time between a decision and a deployed result.
Where I fit in
I work with technical leaders and small teams who need a senior engineer to build with them, not talk at them. Typical engagements look like:
- Prototype to production. Take an AI or infrastructure idea from sketch to working system in under a week.
- Performance and safety. Rust, CUDA, LLM inference optimization, and memory-safe system design.
- CI/CD that stays green. Dagger, GitOps, Kubernetes, and reproducible pipelines so deployment stops being scary.
- Embedded fractional support. A monthly retainer for steady, prioritized work without the overhead of a full-time hire.
Proof points
150+
Public repos shipped in 2026 across AI infrastructure, tools, and experiments.
4
NVIDIA certifications in AI Advisor, AI Infrastructure, Agentic AI, and AI Operations.
24h
Typical reply time on project inquiries.
0
Lock-in on the monthly retainer. Cancel anytime.
Ready to ship faster?
Tell me what you are building and I will reply within one business day. Start with a single project, a live session, or a monthly retainer.
Not ready to commit? Book a free 15-minute call. I will tell you honestly whether a 3-day build is realistic.