I’m targeting forward deployed engineering and adjacent customer-facing technical roles. I bring 10+ years in enterprise software and customer delivery, including leading 6–12 concurrent Workiva implementations and managing a five-person implementation team.
An operating workspace for a founder running five businesses.
My main project. Each business has its own clients, deadlines, and delivery requirements. I’m building a shared workspace for client records, projects, content, and agent assignments, designed to keep drafts, owner approvals, and delivery records distinct.
Private application in active development. Agent execution and external integrations are still being developed. Preview uses fictional work.
A project workspace that helps people and AI assistants pick up work without rebuilding its context. The first integration supports Workiva reporting.
I own product direction, interface design, and implementation through AI coding tools. My reporting-delivery experience shaped the review workflow: proposed changes show their expected results before they run, with a record of what happened and a way to undo them.
A Workiva consulting practice built around training and client ownership.
I shaped the positioning, website, and reporting resources, translating reporting expertise into a service offering and supporting materials.
How I build with AI tools
I own product direction and implementation for Homebase, Passal, and Leasekite, working through AI coding tools. I define what each workflow needs to do, which actions need approval, and how to check the result. Codex and Claude help implement features, write tests, and review code.
In Homebase, a draft, an approval, and an actual delivery remain distinct. I design the workflow so that a completed task does not automatically count as a customer receiving the result. The Homebase case study shows what exists and what is still in development.
I work in T3 Code with a VPS-hosted backend, and Hermes coordinates ongoing agent work. I publish this Astro site with Cloudflare Workers and Wrangler. GitHub keeps the source history; Playwright and axe check browser behavior and accessibility. My operating stack write-up explains the tools and release process.
At Citrin Cooperman, I managed a five-person implementation team. At Workiva, I led 6–12 concurrent implementations.
At LSL, I scoped consulting engagements, prepared estimates and statements of work, and led Workiva delivery for city and county finance teams through client sign-off. I also directed AI-assisted development of Python reporting tools reused across engagements. I built internal review workflows that compare reports with source records and route discrepancies for human review before client changes.
Try a valid update, a stale source, a wrong calculation, and a lost response. This interactive lesson explains how to check an automated action and recover without applying it twice.
Fictional inventory data. Deterministic checks run in your browser.
How I connect source records, agent tools, review, and recovery. Examples from internal reporting work sit alongside public projects with inspectable code.