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PROOF

We don't just describe the work. Here it is.

Real platforms in production, built end to end with AI as the daily toolset.

WANT TO SEE IT RUNNING? ASK. THE DEMO BEATS THE DESCRIPTION.
CASE STUDY 01 · FINANCIAL OPERATIONS

A treasury that ran on manual entry now runs itself.

A statewide athletic association ran its finances by hand. Transactions keyed into spreadsheets, checks written manually, and tax season meaning weeks of assembling records for the CPA. Last season, the mess had a price tag: a $7,000 CPA bill, driven largely by records that arrived scattered and inconsistent.

WHAT I BUILT
  • A multi-tenant financial operations platform that ingests transaction data automatically, replacing manual entry
  • Check printing directly from the system
  • CPA-ready workbooks generated from live data, built to cut that $7,000 bill by thousands this year
  • Role-based access, audit trails, and tenant-level data isolation, because financial data deserves nothing less
WHAT CHANGED

Hours of monthly manual work eliminated, records that stay reconciled all year, real cost reduction at tax time, and a treasurer who runs the whole operation without calling me. The first organization's build now serves additional organizations on the same codebase.

STACK
SVELTEKITTYPESCRIPTPOSTGRESQL SUPABASEVERCELMULTI-TENANT
SECURITY, BUILT IN
ROLE-BASED ACCESS[BUILT IN]
TENANT ISOLATION · RLS[BUILT IN]
AUDIT TRAILS[BUILT IN]
DEMO TENANT · FICTIONAL DATA[SHOWN BELOW]

Client organizations' financial data never appears on a public page; that's a feature of how I work. So the screenshots below come from the Havenfield Soccer Coaches Association, a fully fictional demo tenant running on the same production codebase with the same isolation, seeded with three years of synthetic books. Every name, number, and bank is invented. The live demo is available on request, and it beats the description.

HSCA Command Center dashboard in the demo tenant's turf green branding, showing 6 annual events, 2,022 transactions, 99 percent categorized, and 25 to review
THE COMMAND CENTER · THE DEMO TENANT AT A GLANCE: 2,022 TRANSACTIONS, 99% CATEGORIZED · TAP TO ENLARGE
Finances ledger filtered to the current fiscal year showing bank and card transactions with category chips, needs-category flags, event column, and running net
THE LEDGER · THREE ACCOUNTS, CONTROLLED CATEGORIES, AND THE HANDFUL STILL WAITING FOR REVIEW
Statement upload review screen showing a parsed bank statement with a passing balance chain: 89,541.79 minus 2,481.08 equals 87,060.71, matches statement
STATEMENT INGESTION · PARSED, BALANCE-CHAIN VERIFIED TO THE PENNY, REVIEWED BEFORE A SINGLE ROW WRITES
Event page for the flagship summer coaches clinic showing income of 34,595, expenses of 11,916, net of 22,679 with 98 linked transactions
EVENT ACCOUNTING · THE FLAGSHIP CLINIC WITH 98 LINKED TRANSACTIONS AND A FINAL NET
Invoices screen with status filters showing sponsorship invoices in sent status with amounts, issue and due dates, and mark paid and void actions
RECEIVABLES · DRAFT, SENT, PAID, VOID, WITH THE UNPAID WORK SORTED TO THE TOP
Print checks screen with a new check composer on the left and a check queue on the right holding queued stipend and officials checks across two dates
CHECK PRINTING · COMPOSE, QUEUE (AMOUNT CAN WAIT), THEN PRINT
Print preview of a business check with the association letterhead, payee, amount in words, memo line, and a MICR line, plus printing guidance above it
THE CHECK ITSELF · LETTERHEAD, MICR LINE, AND NOTHING RECORDED UNTIL PAPER IS IN HAND
Contacts screen showing 61 people and organizations as cards with role lines and tag chips like board, coach, sponsor contact, and clinic presenter
CONTACTS · PEOPLE AND ORGANIZATIONS, TAGGED AND LINKED TO WHERE THEY WORK
Board screen showing the executive board seats and regional board groups with role titles
GOVERNANCE · EXECUTIVE BOARD OVER REGIONAL SEATS, DRIVEN FROM CONTACTS
990-PF preparer package screen with a readiness checklist showing three passing checks and cash-at-fiscal-year-end figures per account
TAX SEASON, SOLVED · THE TAX PREPARER PACKAGE BUILDS ITSELF FROM THE BOOKS. THIS IS YOUR CPA BILL SHRINKING
CASE STUDY 02 · EMPLOYEE RECOGNITION

A peer recognition platform, built from scratch.

Companies pay per-user monthly fees for recognition software, then pay the same rate for features they never touch. I believed the core of it, points, recognition, and celebration, could be built better and priced fairer. So I built it.

WHAT I BUILT
  • Peer-to-peer recognition with points, a live activity feed, and GIF celebration
  • Multi-recipient recognition, hashtag values, and a completion moment that makes giving feel good
  • Multi-tenant architecture with configurable branding, one codebase, many companies
  • Light and dark modes, mobile-first responsive design
STATUS

Live in production with demo data, in pilot conversations with its first prospective customer. All names shown are demo accounts.

SVELTEKITSUPABASERLSMULTI-TENANT
Recognition platform home screen showing the activity feed, a recognition card with points and a GIF, the points balance, and the leaderboard panel
THE HOME SURFACE · ACTIVITY FEED, POINTS TO GIVE, RECOGNITION CARDS WITH TAGS AND GIFS · TAP TO ENLARGE
Recognition composer showing a recipient chip, points per person, a hashtag value, a written message, and an attached thank you GIF
THE COMPOSER · RECIPIENTS, POINTS, VALUES, AND A GIF IN ONE FLOW
Confirmation screen with a green check reading Recognition sent, showing the recipient got a little lift
THE COMPLETION MOMENT · RECOGNITION SHOULD FEEL LIKE SOMETHING HAPPENED
CASE STUDY 03 · AI JOB SEARCH

A job search assistant that reads the jobs so you don't have to.

Job boards bury good openings under reposts, sponsored listings, and roles that don't fit. So I built a tool that goes straight to employers' own career pages and lets Claude do the first read. I'm using it in my own search right now.

WHAT I BUILT
  • A desktop app for Mac and Windows that reads 2,800+ company career pages, six remote-job sites, and the user's own job-alert emails, then removes the duplicates
  • Claude reads the user's resume to suggest the job titles to search for, then scores every match from 1 to 10 with a one-line reason. Matches start appearing within seconds
  • Spots "thank you for applying" and rejection emails and moves those jobs to Applied or Closed on its own
  • Private by design: no account and no server. The search, the resume, and the notes stay on the user's computer
STATUS

In early access with beta testers, free to download. Built with Claude Code and first released October 5, 2026, with four releases in the first two days. Every release is built and tested automatically on real Mac and Windows machines before it ships.

PYTHONCLAUDE CODECLAUDE HAIKU + SONNET GITHUB ACTIONSMAC + WINDOWS

See Job Scout

Job Scout showing new job matches, each with a fit score, salary, remote tag and a one-line reason it fits, with filters and Saved and Applied lists in the left menu
NEW MATCHES · FIT SCORES, SALARIES, AND THE REASON EACH JOB FITS · DEMO PROFILE · TAP TO ENLARGE
Job Scout mid-search: Still searching, 121 possible matches so far, 645 of 888 career pages checked, with matching jobs already listed and marked not scored yet
RESULTS WHILE YOU WAIT · 18 SECONDS IN, 121 POSSIBLE MATCHES FROM 645 CAREER PAGES
Job Scout scoring matches: 10 of 60 scored, 6 good so far, 4 set aside, with fit scores of 9 and 8 out of 10 and a one-line reason under each job
THEN CLAUDE READS EACH ONE · SCORES AND REASONS FILL IN, WEAK MATCHES DROP OUT
CASE STUDY 04 · HOW I BUILD

How one person ships all of this: a human in the loop.

I build with Claude every day, and I decide what ships. AI drafts and codes fast. My job is the part it can't do: deciding what's worth building, checking the result against the real need, and refusing to ship anything that doesn't hold up. That's the difference between AI-assisted work and AI slop.

WHAT I DO THAT AI DOESN'T
  • I set the direction. Every project starts with what the people using it actually need, written down before any code exists. Claude works from that, not from a guess.
  • I test it like a user. I use what gets built, with realistic data on real devices, and try to break it. If something confuses me, it gets fixed before anyone else sees it.
  • I check the claims. Totals, security rules, and what a tool says it does get verified, not taken on the AI's word.
  • Lessons stick. When something goes wrong, the fix comes with a written rule or an automatic check, so the same mistake doesn't come back.
WHAT THAT LOOKS LIKE ON THIS PAGE
  • The treasury. Bank statements are checked to the penny before a single row is saved, and no check is recorded until it's printed.
  • Job Scout. Every release is tested automatically on real Mac and Windows machines. In its first week, testing caught a Windows crash and a Mac bug that would have broken every search, before either reached more users.
  • Every screenshot. Client data never appears on a public page. What you see here is demo data.
WHY IT MATTERS TO YOU

You get AI speed without AI slop: a solo practice delivering on timelines that used to take a team, with a person accountable for every result. And it's teachable. Helping your team work this way is one of the things I do.

A short walkthrough video is coming to this page. Until then, I'll happily share my screen and build something in front of you.

Communications Work

I influence how leaders' biggest messages reach employees: C-suite company-wide emails, company vision rollouts, internal comms cadence, and leadership guides managers use to talk with their teams. These samples are anonymized.

Manager Communication Guide

One of 23 guides I wrote for a supervising-manager toolkit, showing leaders how to communicate change early, explain the why, and close the loop.

View the guide (PDF)

Company Vision Explainer

The plain-language explainer for a C-suite vision I distilled from three owners' one-pagers and rolled out company-wide, with a SharePoint hub and an AI agent that answered employees' questions about their roles.

View the explainer (PDF)

"Bell Ringing" Company-Wide Email

A recognition email built from recorded new-client announcements. I used AI to summarize each recording, rewrote it in the company's voice, and built the HTML email.

View the email (PDF)

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