Selected work
Six things I designed, built, and shipped — products people pay for, and systems that keep themselves honest.
A live B2B SaaS with real subscriptions and a free trial — built and operated solo.
Helps tipped-industry employers track and document the “no tax on tips & overtime” deductions under the One Big Beautiful Bill Act — automatic Treasury Tipped Occupation Code assignment, FLSA overtime, W-2 Box 14 exports (ADP/Gusto/QuickBooks), an audit trail, multi-tenant role-based access, and an analytics dashboard.
Improvements are earned behind a 7-tier verification gauntlet — not hallucinated.
An autonomous system that improves its own code behind that gauntlet (parse, unit, property, mutation, benchmark, sealed holdout, fresh-context critic). A panel of specialized agents — planner, coder, tester, reviewer, critic — plus meta-improvement loops, all sandboxed.
The autonomous inner research loop is ported from Udit Goenka’s autoresearch (MIT, based on Andrej Karpathy’s work); the meta-improvement architecture and the verification stack are my own.
25 checks, 0 exceptions on a published report — the model never does the arithmetic; tested code does.
Turns a government audit statement (PDF) into clean structured JSON, then re-derives every total (foot, crossfoot, articulate) to prove the extraction is correct, with a golden-file regression test. No OCR for born-digital text. Inject one wrong figure and it’s caught.
Try it yourself: the interactive demo runs entirely in your browser on real public Auditor-of-State reports — pick a report, watch every total get re-derived, and toggle a figure to see the check fail. Nothing leaves your machine.
Audit-ready 2 CFR 200 grant-compliance reporting, end to end.
Full-stack B2B SaaS that auto-categorizes nonprofit grant spending into 2 CFR 200 budget categories, tracks budget-to-actual per grant, and generates audit-ready compliance reports, with QuickBooks/Xero integration.
Nineteen Connect-4 agents ranked by strength per byte — and the honest answer wasn’t the one I expected.
Connect 4 is solved, so perfect play is a known target. NeuroFour ranks 19 agents by strength per byte under a 5M-FLOP budget, scored against an exact solver (the solver itself is the 20th entry, over budget by design). Zero leads optimality, ladder Elo, and NeuroFour Score among those 19 under-budget agents — at 0 bytes and 0 parameters, ahead of all 14 learned-net entries (6 distinct weight files, largest ~24 KB). Ladder Elo 754 vs 631 and NeuroFour Score 96.45 vs 74.25 are clear margins — though that score divides strength by a size penalty; optimality 0.960 vs 0.957 is one move in 300 on a single seed. Each comparator is the strongest learned entry on that axis (a tie, for optimality) — four entries across two weight files, none leading on all three. It doesn’t lead everywhere: Zero ranks 4th of 19 on soundness, 15th of 19 on latency, and 18th of 19 on FLOPs/move, spending 4,999,028 of the 5M-FLOP-per-move budget. Best net per byte: 0.950 at 2,867 bytes.
Free-tier API — first move may take ~30–60s to wake.
~3,000 lines of native C++20 — four distinct ghost AIs, co-op multiplayer, cross-compiled to an ARM handheld.
Built from scratch with procedural chiptune audio and sanitizer/coverage/strict build presets and tests.