scoped writes only · 0 unauthorized writes
The ServiceNow work your roadmap slots for a quarter,
delivered in a week.
Senior architecture at the speed of a disciplined AI harness — one that reads before it writes, verifies every change on your instance, and is physically blocked from touching anything out of scope. Fast, without breaking production.
Two ways to buy ServiceNow work. Both cost you.
The consultancy
A big firm will protect your instance — behind a statement of work, a bench of rotating juniors, and two quarters of calendar. You pay for caution in months, and in a build shaped by people who won't own it.
Just add AI
Point a generic agent at your system of record and it will move fast — right up until it writes to production it shouldn't, and you learn about it from your users. Speed you can't trust isn't speed. It's exposure.
Senior judgment at AI speed, with production-grade discipline wired in.
The consultancy's caution and the agent's velocity — without either one's price. It reads first, verifies on your instance, and is blocked from anything you didn't sign off on. The one thing the others can't copy: fast without breaking production.
The discipline is the product.
Three things make the harness safe on a live instance. None of them are optional, and none of them are marketing.
Verify everything
Nothing is trusted because a model produced it. Every change is checked against your instance — regression, data integrity, ACLs — and only a result that passes is allowed to stand. If it can't be verified, it doesn't ship.
Guardrails make mistakes impossible
Scope is enforced in code, not in good intentions. Policy hooks intercept every action before it runs: an attribution guard refuses unattributed writes, protected paths refuse edits outside the agreed boundary, and every write is verified by read-back on the instance. Blocked, not warned — the system physically cannot do the quiet wrong thing.
Compounding memory of 100+ platform walls
Every engagement adds to a growing record of the ways ServiceNow bites you — the ACL trap, the update-set gotcha, the flow that scales wrong. 153 entries and counting, 116 of them hard-won platform lessons. Each new build starts already knowing the walls, so it doesn't rediscover them on your instance.
What I actually get moved.
Scoped-app builds
A real application — data model, flows, UI, ACLs — designed and shipped against a fixed scope. No open-ended discovery phase, no scope creep dressed up as agility.
CSM, case & intake orchestration
Case, intake, and Customer Service Management wired end to end: routing, assignment, SLAs, and the automations that make them actually hold under load.
Rescue & remediation
An instance that drifted, broke, or was half-implemented — assessed read-only, stabilized, and brought back to a state you can safely build on again.
AI-enable your team
Stand up the same disciplined harness for your own admins — with the guardrails and verification that keep it safe once it is in your hands, not just mine.
Live data migration & feeds
Data-model re-shapes, record migrations, and inbound integration feeds — staged, masked, deduplicated, and executed on a live instance behind an end-to-end verification pass.
Something else stuck?
If it lives on your instance and keeps sliding down the roadmap, it qualifies. Book a working session →
The loop, every time. No exceptions.
Scope — read-only
I connect with read-only access first and map what is actually there. Nothing is written until we agree the boundary in writing.
Design
A concrete change plan: what moves, what it touches, and where the guardrails sit. You approve it before anything is built.
Build behind guardrails
Work happens strictly inside the agreed scope. Anything reaching for production outside the plan is blocked at the boundary, not flagged after the fact.
Verify on your instance
Every change is tested against your real configuration and data — not a generic sandbox — until regression, integrity, and ACL checks pass.
Hand off with an audit trail
You receive the working build plus a signed log of every action taken. Nothing about the run is a mystery, and nothing depends on me staying.
Every run, signed and on the record.
Every run below is a real, dated delivery — dated kickoff to live-verified ship, evidence on file. Nothing here is invented.
Real figures from the current engagement record, as of 2026-07-24.
When it goes wrong, you watch it get fixed.
Mid-run, an update-set capture incident put real changes in the wrong change-tracking container. It was caught in-run, every record re-parented, and both update sets verified clean — all of it on the record, same day. The audit trail includes the mistakes, because that is what makes the rest of it believable.
Adam.
I build enterprise ServiceNow the way it should be built: senior judgment on the design, a disciplined AI harness doing the heavy lifting — safely. I work alone, on your instance, in the open. You see every action as it happens, and you keep the audit trail.
I've spent the better part of a decade building on enterprise platforms, most of it ServiceNow. [ BACKGROUND — ONE SENTENCE ] The harness exists because coding agents are great in a sandbox and dangerous on a live system — the write that returns 200 but silently did nothing, the change made under the wrong identity, the mistake a team already paid for three weeks ago. So I packaged the discipline senior engineers apply automatically: read-only first, every write verified by read-back, everything attributed and logged, and every burn recorded once — so no client's instance pays for the same lesson twice.
Bring one thing on your instance you want moved.
A stuck workflow, a rescue, a scoped app you keep deferring. We'll spend a working session on it — read-only, on your terms — and you'll watch exactly how the harness behaves on real ServiceNow.