Paradigm Coding Solutions
AI, ML, and data science engineering for teams that have to ship it.
Software engineering focused on AI deployments: agent architecture, ML systems, and the safety thread that keeps both honest. One studio, one engineer, a research lab attached, and a supervised multi-agent build process. The live demos are on the work page and the source for the four client-brand demos and our agent runner is public on GitHub (opens in a new tab), so you can check both yourself.
What we do
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Build with AI, not around it.
Coding agents now take on whole features and get much of the work right. The job is catching the rest: small contract-shaped tasks, checks the agent didn't write, and a person approving every merge. It's how this studio builds its own software.
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ML systems that earn their keep.
RAG, tool use, model serving, evals, cost ceilings. The unsexy half of every model feature that survives contact with real traffic.
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Safety as engineering, not slides.
A written record of each change and the reasoning behind it, a person approving every merge, and no automating the calls that shouldn't be automated. Provenance, on the work page, is where the thread goes next: a tamper-evident ledger of agent decisions.
A one-person practice with an R&D lab attached. We take client work, and we build our own tools. The live demos and case studies are open to click through on the work page.
How the work gets built
We build our own software and client projects with a supervised team of AI agents, and we configure that tooling around your stack, your data and your rules. A planning agent breaks the work into small pieces, each with a check a machine can run. Builder agents write the code, separate agents verify it, and a review council of agents cross-examines contested decisions. Changes go through automated checks before they merge, and anything touching money or DNS waits for Drew's sign-off.
Consulting clients get, with every change, the code, the checks it passed and a written record of what changed and why. That record stays with you, so whoever works on the system next starts from decisions instead of guesses. If you use one of our tools, tailored to your workflow, it is built and checked the same way, with an independent verification report on the riskier changes.
The receipts, as of October 2026: this site has more than 150 merged pull requests, a ledger entry required on every pull request since late September (CI refuses one without it), and 20 independent verification reports across 16 of its riskier changes, including re-checks after a change was revised. The client portal went from an empty repo to 15 merged pull requests in its first three weeks, and has more than 110 now. Those two repos are private, and we'll walk you through them on request.
We audit our own checks, too. When we catch a gate passing something it shouldn't have, we write it up and go after the cause. We don't sell a speed multiplier: a randomized study in 2025 found AI made experienced developers 19 percent slower (opens in a new tab) on mature code. The checks are what make our pace worth having. And because one engineer directs the work, the plans, tests and decisions are written down in the repo rather than kept in one person's head.
Who runs it
Drew Mattick, Primary Developer.
Working toward a PhD in computer science, focused on AI/ML research. US provisional patent application filed April 2026, on an autonomous mobile perception platform for building management (USPTO #64/050,120).
Want to talk about something specific?
Tell us what done looks like, and we'll tell you whether we're the right fit.