Not just this website — a real and growing share of my company's operations runs this way. A
fleet of AI agents I built fans the work out, has each result checked by another agent, and
brings me the calls a human still has to make. Here's the actual stack, the honest build log,
and what each failure taught.
The stack
the real systems, not a vision deck
This isn't a someday-architecture. It's the actual set of systems running the company right now —
built, run, and watched by one fleet of agents. Here's how they fit, then what each one is for.
Auto-verified against my internal repo catalog — 12 systems, last checked 2026-07-11.
Tap to open the full map.
AMA
the dev loop
Why
Shipping software by hand doesn't scale when the team is a fleet of agents.
What
An orchestrator that turns a GitHub issue into a merged pull request.
How
It spawns throwaway agents — one plans, one writes, others review — in isolated sandboxes, and never lets my credentials touch GitHub.
Cody
the dev loop
Why
Every pull request needs a reviewer that never gets tired or rushed.
What
A self-owned AI code reviewer that reads every PR across all my repos.
How
It learns from a commercial reviewer's feedback, distills its own rules, and holds the merge until they pass.
Portal
product
Why
Patients and front-desk staff were stuck with clunky, disconnected tools.
What
The patient and front-desk app — registration, scheduling, messaging, tasks.
How
One surface over the clinic’s real systems, so a patient self-registers and the work lands where staff already look.
Chart Review
product
Why
Charts must be complete and accurate — but reviewing them by hand burns the providers I want to protect.
What
An engine that reads every chart for completeness across clinical domains.
How
AI drafts the review, a clinical gate checks it, and only what genuinely needs a human reaches one.
Billing / RCM
product
Why
Revenue-cycle work is where clinics quietly leak money — to manual keying, missed eligibility, and mistakes.
What
Runs insurance eligibility checks, and reads statements, invoices, and cards into clean structured data.
How
Verify coverage up front, then extract and reconcile-or-refuse — only numbers that tie to the source ship; the rest routes to a human.
CFO + COO engines
the brains
Why
You can't run a business on gut — you need real P&L and real operations numbers.
What
Two engines — one for finance, one for operations — that compute the picture from raw data.
How
Both write to one canonical ledger; the brains I actually talk to read from it, so every number has a single source.
HUD — Mission Control
mission control
Why
I need to see the whole company at a glance, not log into ten separate tools.
What
One executive dashboard over every system and number.
How
It reads the canonical ledger and each product’s signals into a single pane.
The fleet + memory
substrate
Why
Agents that forget everything between sessions can't be trusted with real work.
What
A fleet of coordinating AI agents with one durable, shared memory.
How
They verify each other’s work, and everything load-bearing is written to a knowledge base any agent can resume from — this site included.
How the stack has grown
This log writes itself — a scan of my repo catalog logs every system added or retired, so the
progression is real, not remembered.
2026-07-03First snapshot of the stack — 12 systems.+ agents-flow, arcs-chart-review, arcs-doc-extract, arcs-extract, arcs-financials, arcs-lattice, arcs-managed-agents, arcs-studio, Card-OCR, cody, Portal, whipple.ai
● The build log
How the system actually got built
From one terminal and a notes folder to a fleet of agents that check each other's
work. Every step was forced by something breaking. Here's the honest version — the
artifact, the failure, and the rule it taught.
Early 2026 — One terminal
One Claude Code session and an Obsidian vault. Everything ad-hoc, everything by hand.
The lesson The question was never "can one agent help me." It was "what breaks when I add the second one." Coordination is the whole game.
Spring 2026 — A fleet on tmux
Agent work fought my dev machine, so I moved it onto dedicated boxes — cheap $271 mini-PCs — and wired a boss session to its peers over tmux with a small message helper.
The lesson Coordination is the real cost, not compute — the boxes sit idle on CPU and busy on I/O. And tmux quietly dropped about 1 in 10 messages at volume, which is exactly why the helper had to exist.
Late spring 2026 — A real dispatch engine
Hand-run orchestration was too fragile, so it became a proper conductor: a dispatch API, a job graph, a worker pool that takes an issue and ships a reviewed pull request.
The lesson A merged PR is not live code. Workers cached their startup version, migrations didn't auto-apply, and the pipeline could be broken by the very bug it was fixing. Verify the running artifact, never the paper trail.
June 2026 — The "nation" (the pivot I simplified)
I organized the fleet like a government — a president, governors, a written charter, terms of office. Literal bills and votes.
The lesson The honest one. The ceremony grew faster than the engineering. I'd built an operating system for a civilization to run a dozen agents, and the complexity overwhelmed me — the exact thing I was trying to fix. I kept the engineering and threw the metaphor away. A persona shapes behavior; it doesn't add competence.
June 2026 — The reality gate
I built a system in dozens of modules, every unit green, mutation-tested, reviewed sound. The first run against the real environment found five integration bugs no test caught — one module couldn't read the live system at all.
The lesson Green on mocks is never done. Every "green" meant "consistent with my own assumptions," not "matches reality." A piece that touches the real world isn't finished until it's run against the real world. The most transferable rule I have.
June 2026 — Self-healing
A box died under its own load three times in one day. Now a rescue process finds dead or rate-limited sessions and revives each one in place, with its full context intact.
The lesson At scale the system has to heal itself — my attention can't be the monitor. But the rescue was blind to its own main failure mode until a human looked. Automation still needs one human-eyes rung.
Now — The thin waist
A dispatch engine in the middle, a thin layer that gates and merges and watches health, and agents that do the disposable work on a cheaper model while the frontier model is saved for judgment.
The lesson Right-size everything. A handful of long-lived agents per box; everything else is throwaway. The system that survived is the one I can hold in my head.
● the fun part
Wait — who actually built this site?
Mostly not me. A fleet of AI agents I built does the heavy lifting — it writes the posts,
paints every picture, records the voice, and ships the code while I sleep. I just point and
review. Don't take my word for it. Here's the receipts.
↓ every tile is AI-made — click any one to read the post it illustrates