Tice Labs is an independent consultancy turning manual operations into resilient AI-augmented workflows — backed by production AWS and Kubernetes done by one engineer who's been on call for it.
// SERVICES
Most consultancies will sell you one of these and quietly subcontract the others. This is one engineer, working across the stack, with the scars to prove the seams are real.
Greenfield landing zones or rescue work for accounts that grew faster than they were planned. Multi-account orgs, networking, IaC, and cost discipline.
EKS, on-prem, and hybrid Kubernetes. GitOps, observability, autoscaling, and the boring operational work that determines whether the cluster runs you or you run the cluster.
LLM systems wired into the work that already pays the bills. Evaluation harnesses, observability, and the unsexy reliability engineering that turns demos into dependable internal tools.
// COUNTER-POSITIONING
The kinds of work I turn down — not because I can't, but because someone else would do them better. A short list of “no” is the most useful thing a consultant can publish.
If a chatbot is the answer, you don’t have an infrastructure problem. Hire a UX team.
Most pilots aren’t worth productionizing. I’ll tell you up front, not at week six.
I wire production systems around models. If you need researchers, I know good ones.
You hired one engineer. You get one engineer. The whole point of hiring me.
I don’t show up, write a deck, and leave. The deliverable is shipped code and runbooks.
Engagements end on a date we agree to. The relationship can continue — the meter stops.
// OUTCOMES
// HOW I WORK
Tice Labs is one engineer with a decade of production scars. The operating model is shaped by what works at that scale — and what doesn't.
No project managers, no tickets routed through three teams. You get the engineer doing the work — in your Slack, every day of the engagement.
Infrastructure, pipelines, runbooks, evals — committed to your repo, reviewable, reversible. You own a system at the end, not a dependency on me.
The team after me should operate what I leave behind without a phone call. Docs, observability, and on-call posture are part of the deliverable.
Engagements have a defined outcome and an end date. If we need to rescope, we do it openly. No retainer creep, no parked invoices.
// ENGAGEMENT
A 60-minute call, then a written scope: outcomes, deliverables, fixed fee, end date. No-fit answers come back in 48 hours.
Read-only access. I produce a written assessment with what’s working, what’s shaky, and the order to fix things. Numbers, not vibes.
IaC, pipelines, observability, eval harnesses — whatever the spine of the engagement is. Shipped to a staging environment you can poke at.
Cut-over plan, on-call posture, runbooks. We ship behind flags, with rollback. I stay on call until the SLOs hold for a full week.
A live walkthrough recorded for the next engineer, plus written runbooks for the top 10 things that can go wrong. Then I leave.
// THE ENGINEER
I spent the last decade as a staff/principal engineer building the backend systems that other engineers depend on — multi-region AWS footprints, EKS at scale, the boring reliability work that keeps pagers quiet.
In the last two years that work shifted toward AI: agents answering tier-1 support, pipelines that turn unstructured intake into clean records, evaluation harnesses that keep all of it honest. The interesting part is that the engineering looks the same — observability, budgets, rollback. The hype is loud; the practice is familiar.
Tice Labs is what happens when I stop doing that inside one company and start doing it across a small number of clients per year, in scoped engagements I can fully own.
// FAQ
// CONTACT
Send a paragraph or two on what you're building, what's broken, or what's stuck. I'll reply within two business days with whether it's a fit — and if it isn't, who I'd point you to instead.