TierOne assembles small engineering units of operators, selected on the signals the market can't read and force-multiplied by AI. We don't fill seats. We build engines.
Where our operators ship
What we do
The stack is the easy part. Every agency lists the same tools. What's scarce is operators who own the outcome: who decide what to build, what to refuse, and answer for the result. That's what each of these is built on.
We're not a tools-implementation shop. We don't sell seats or licenses. We assemble operators who own what they ship.
Software delivery
AI lets a team produce more code. It doesn't make that code owned, architected, or safe to build on. We embed operators who wield AI as leverage and hold the judgment calls: what to build, what to refuse, what to throw away. Higher velocity, with someone whose name is on the result.
$ git review --ai-diff feature/checkout ✓ architecture review passed owner: @operator ✓ 142 tests green · coverage 91% ✓ AI-generated diff reviewed: 3 changes rejected → merged. someone owns this.
Stack we work in
Agentic systems
Most agentic demos die in production because no one owns the architecture. We build autonomous systems (customer-facing assistants, internal research agents, multi-step workflows) and the operators who can run them, evaluate them, and answer for them when they fail. Reasoning and execution you can put in front of customers, not a prototype.
$ eval run --suite production --agent research-assistant ✓ 1,000 traces evaluated ✓ tool-call accuracy: 98.2% ⚠ 18 failures flagged → routed to operator → no silent failures. someone's watching.
Stack we work in
AI readiness
You can buy every AI license and still move slower than the five-person startup eating your lunch. Adoption isn't a seat count. It's judgment, governance, and people who actually change how they work. We build the operating model, the guardrails, and the capability that make AI stick after the pilot ends.
$ assess --team ai maturity ·········· 2/5 tools bought, habits unchanged governance ··········· 1/5 no guardrails operator coverage ···· 0/5 no owners → verdict: licenses ≠ adoption.
Approach
Why operators
We assemble small disciplined units, not lists of available developers. Every part has a job only it can do.
We select on ownership, accountability, judgment, and AI fluency: the signals resumes and stacks can't show.
We don't talk about AI as force multiplication. We build the systems that make it real.
We add leverage without lock-in: we document as we build, so your team can run the engine after we're gone.
We don't pitch operators in the abstract. The proof is the systems we've shipped and the clients who run them in production.
See what we've builtHow We Work
Most teams scale by adding headcount and hoping it gels. We don't hire to fill a gap. We assemble a unit of operators around your mission, built to get faster every sprint and to hand back cleanly. Four moves turn a stretched team into an engine.
Before anyone writes code, we map the exact operators your mission needs (who owns architecture, who ships, who wields AI as leverage) and why each one is there. The shape follows the outcome, not a generic job spec or a résumé pile.
You get: a unit spec (who's in it, what each person owns, and why) before anyone writes code.
Explore our offersEach unit owns one clear slice (a service, a workflow, a migration) and we write down what's out of scope just as deliberately. That boundary is why delivery stays predictable instead of sprawling into everything and finishing nothing.
You get: a scope agreement with in/out boundaries and a named owner for each area.
Explore our offersEvery change runs our AI-augmented review gates for architecture, code, QA, and security: the five fresh-context reviewers behind our harness (1,652 structural tests across three production repos). For Contractor Commerce, that meant a rebuilt CI/CD pipeline and a self-healing layer that catches and fixes bugs in production, not in a ticket queue.
You get: rising throughput each sprint, with review gates that stop quality slipping as you move faster.
Explore our offersWe work inside your existing engineers, rituals, and stack, and document as we build so ownership can transfer the day you want it. Leverage now; a team that can run without us later. Never lock-in.
You get: integration into your workflow, living documentation, and a clear handoff path.
Explore our offersProof, not theater
Anyone can demo an AI workflow. Almost no one ships systems that survive production. Here's what we've built.
An executive knowledge layer that ingests a company's documents, SaaS apps, and production database, and answers questions in plain language. Self-hosted and multi-tenant, built on Airweave for ingestion and Qdrant for retrieval.
The first system we built with this stack was our own product.
Technical overview (coming soon)An operating profile that keeps AI coding agents (Claude, Copilot, Codex, Cursor, Windsurf) on convention rails inside a real codebase: a priority-ordered router, on-demand skills, and five fresh-context review subagents that gate work with APPROVE / BLOCK / REVISE.
1,652 structural assertions across three production repos. Validated across three different stacks.
How it works (coming soon)For Contractor Commerce we rebuilt the CI/CD pipeline, stood up an AI-assisted delivery unit that raises its velocity each sprint, and shipped an LLM-driven self-healing layer that detects and resolves bugs.
The Agentic Build Sprint and Operator Units, in production.
Read what their VP of Engineering said# the model can't hide behind "it depends" P0 SAFETY deny destructive ops · secrets · force-push P1 IDENTITY operator, not autocomplete P2 CONVENTIONS load on match, not every turn P3 CHANGES smallest diff that passes P4 VERIFY architect · code · qa · security · lessons $ ruler verify qa-validator ............ APPROVE security-reviewer ....... BLOCK missing authz test 1,652 structural assertions · 3 repos · 3 stacks
Operators don't describe AI capability. They ship it, with tests.
Book a Sprint conversation1 week. A deep audit of your team and system, an architectural risk map, and a 90-day plan. The low-risk way to start.
2-4 weeks. Unit design, operator scouting, delivery system, and an AI leverage plan. For founders past the first build.
2-4 weeks. We ship one production-grade agentic workflow on our harness, complete with evals, guardrails, and observability, then leave your team able to run it.
An assembled engine plus fractional engineering leadership, on a monthly retainer. Includes owning agentic systems in production.
Not sure which fits? Every engagement starts with one conversation. We'll tell you what we'd assemble, or tell you honestly if we're not the right partner.
Book a Sprint conversation
Is this you?
We work best with a specific kind of team, and we'll tell you honestly if that's not you.
If the first column sounds like you, let's talk.
Book a Sprint conversationThe Engine Diagnostic · Free
Stop guessing whether you need senior devs, a tech lead, DevOps, or a fractional CTO. The Engine Diagnostic gives you a clear read on which operator signals your team is missing, and the order things tend to break in.
Verdict: High on capability, low on accountability. Three operator signals are missing. Here's what tends to break first, and in what order.
FAQ
Anyone can ship an MVP in a weekend. Almost no one can assemble the operators who can ship AI systems that survive production.
One conversation. 20-30 minutes. We learn where your engineering is breaking and tell you what we'd assemble. No obligation, no deck.