Speed that does not come back as bugs.
Most teams can go faster. The hard part is doing it without turning the codebase into something nobody wants to touch. These are the three things I bring to every engagement.
Approach
How I work
Three things I bring to every engagement
Composable architecture
I build systems as independently deployable modules on shared foundations: micro frontends, packaged components, Node.js services behind typed API contracts, and Turborepo monorepos where every component is its own versioned package in a registry. New products launch as modules, not new codebases. Teams ship in parallel, and a change in a shared component lands everywhere at once.
AI pipeline with human review built in
Agents do the mechanical work: claim the issue, implement, run tests, and respond to review comments. A reviewer agent checks every change, and a second model challenges the high-risk ones so one model's blind spots are caught by the other. People review design and correctness, and nothing merges without a human signing off.
Standards that hold up after I leave
Strongly typed contracts in TypeScript, composable hooks and data layers, automated testing and CI/CD, and living documentation, including interactive visual guides that onboard engineers onto new patterns. The goal is a codebase your team can keep moving fast in.
The AI pipeline
From GitHub issue to reviewed pull request
Here is one pipeline I have built, as an example of the principle. It is not autocomplete. An agent claims an issue, reads the codebase, implements the change, runs the test suite, and opens a pull request. A reviewer agent reads that PR and pushes back, and high-risk changes get a second pass from a different model, OpenAI Codex. The agent resolves the feedback. Only then does a person look at it.
By the time a human reviews, the change is already built, tested, and challenged by a reviewer with different blind spots than the author. Human review goes where it matters: is this the right design, and is it correct?
Cost stays in check through model routing. Linting, formatting, and test runs go to lightweight models. Architecture decisions and judgment calls go to frontier models. MCP servers and CLI integrations give agents direct, auditable access to the repo, issues, and PRs, so nothing happens that you cannot trace.
- Issue claimed
- Implemented & tested
- AI cross-review
- Human review
- Merged
Working together
How an engagement runs
Call
A short conversation about what you are building and where it hurts.
Proposal
A written proposal: a fixed scope with deliverables, timeline, and price, or a fractional retainer with days per week.
Work
Delivered in small, reviewable pull requests inside your process.
Handoff
Documentation, training, and patterns your team keeps using.
Most of my work runs as either a fixed-scope engagement with clear deliverables or a fractional engagement with a steady weekly cadence. Both start with a conversation about what's slowing your team down.
Terms that fit the work
Short or long
A two-week audit, a three-month build, or a fractional engagement at one to three days a week. Length and terms are negotiated around the work, not the other way around.
Direct, no middle man
You work with me, not an agency or a recruiter. No markup on the rate, and the person on the call is the person doing the work.
1099 or W-2 contract
Fixed-scope proposals, hourly, or a contract through your payroll. Whatever your procurement needs, we can make it work.
Want to ship faster without losing control of the codebase?
A short call is the quickest way to find out whether I can help. No pitch deck, just a conversation about what you are building.