Austin engineering since 2015
Anyone can demo an agent. We engineer the ones your business can depend on, and we tell you when AI isn’t the answer.
We’ve delivered dozens of enterprise software and data systems, hands-on and local. We build your team’s capability, not a dependency on ours.
It starts with The Leverage Map: your agent strategy, started where it pays off first. Fixed scope, in writing, yours to keep.
Proof of operation
Keyfive is a digital-twin software company for energy and industrial operators. Behind its leadership runs an agent desk that ATX DevOps engineered: finance, revenue, and technology agents that cooperate on the same question, each in its own lane with its own data and credentials, convened by a credential-free chief of staff.
The desk does real work, unattended and on schedule: go-to-market analysis drafted overnight, financial reviews reconciled, security advisories summarized, renewals prepared and held for sign-off. People stay in the loop where it is strategic. They approve what matters and decide what moves. Not a replacement for the executive team. Superpowers for it.
None of this is visible from outside the company. That is what an engineered advantage looks like: quiet, and specific to one operation.
The agent desk behind Keyfive's leadership: three cooperating agents with isolated credentials, one credential-free chief of staff, prepared work plus one decision memo, and people making every call. Engineered by ATX DevOps.
Want this kind of support on one of your workflows? Map your leverage
Start from the result
The question is never whether an agent can do something impressive. It’s whether the work moves your business. We start from the outcome: business value, financial value, technical value. Then we work backward. Sometimes that lands on an agent. Sometimes on better software. And sometimes we’ll tell you AI isn’t the move yet.
That answer costs a conversation. A stalled initiative costs a quarter.
What we engineer
Agentic systems are software workflows that can interpret context, use tools, and move work forward within boundaries your organization defines. We design them around real work, not demonstrations, and engineer the systems around them to survive production.
Turn a slow, fragmented, or error-prone process into a coordinated workflow across people, data, and systems. We identify where an agent adds real leverage, define the boundaries and approvals, connect the required tools, and make the work traceable.
Typical work: intake and triage, research and synthesis, decision support, reconciliation, document workflows, cross-system coordination.
Help engineering teams use agents across planning, implementation, testing, review, and release while preserving the controls that protect the product. The objective is not more generated code. It is a delivery system that catches problems before they move downstream.
Typical work: engineering workflow design, repository and tool integration, human-review gates, automated tests, quality checks, delivery guardrails.
Build or strengthen what the agent depends on: clear APIs, usable data, dependable platforms, delivery automation, observability, permissions, and security controls. When the foundation is weak, we fix it as part of the workflow instead of hiding it behind a model.
Typical work: APIs and integrations, data pipelines, CI/CD, cloud platforms, identity and access, monitoring, auditability, operational readiness.
A practical path to production
Start from a real business or engineering goal. Map the people, systems, decisions, friction, and risk before any technology choice. If AI isn’t the right move for this workflow, we say so and tell you what is.
Build the smallest useful version with representative inputs, explicit boundaries, and the right human checkpoints. Evaluate whether it improves the work before expanding it.
Connect the workflow to dependable data and tools. Add the permissions, testing, monitoring, failure handling, and clear ownership that the level of risk calls for.
Define practical measures of utility, quality, time, and risk. Refine from real use, and transfer the capability to your team as we go. The goal is a system your people own, not a dependency you rent.
You can buy that first step on its own. The Leverage Map finds the leverage on one workflow and puts it in writing. Map your leverage
Support that shows up before you ask
Keyfive’s leadership gets what most executive teams wish they had: the briefing already drafted, the forecast already reconciled, the security advisory already summarized, the coordination already done. Work that used to interrupt the team now runs on a schedule and shows up prepared. Anything consequential waits for a person, so someone stays in charge of the decisions that matter without becoming the bottleneck. And every discipline underneath exists for a business reason, not a technical one.
Each agent holds only its own credentials, and the coordinator holds none at all. A mistake or breach in finance cannot reach revenue or platform. That is business continuity, engineered in.
No money moves, no customer is touched, and nothing ships without a named person’s sign-off. You get the speed of automation with the accountability of a human decision.
Significant choices are written down with their rationale, including the reversals. Auditors, new leaders, and future you can read exactly why.
Every scheduled job records that it ran and leaves the evidence behind. Whether the automation actually did its work is a report you can read, not a guess.
These are disciplines from a system in daily operation, not a slide. Your workflows, constraints, and controls will differ. That is the point of engineering.
Your turn
We built that desk around one team’s questions, data, and controls. Yours would look different, because your business asks different questions. That is the design, not a caveat. You do not need an agent desk on day one. You need one workflow where prepared work would change your week.
Each of those questions is a place your agent strategy could start. The Leverage Map picks the one that matters most and answers it in writing, either way. Map your leverage · See what else we run
Signed
Every month I meet a team with an impressive demo and no path to production. The model isn’t the problem. Nobody engineered the system around it: the data, the controls, the tests, the ownership. That’s not an AI skill. It’s an engineering discipline, and it’s the one we’ve practiced at ATX DevOps since 2015.
So we work the way engineers should: start with your outcome, build only what’s worth building, and hand your team the keys. We built an agent desk to help run a real operating company before we offered to build one for anyone else. And if AI isn’t your answer, I’ll say so. That conversation is a lot cheaper than a stalled initiative.
The founder, ATX DevOps
Bring me the stalled one. Map your leverage
Engineering first
The models are the same for everyone who buys them. The advantage is in the system around them: your workflows, your data, your controls, your people. We engineer that system so it fits nothing but your business, and we hand your team the keys.
We start with the job that must improve and define “useful” before choosing an agent, model, or platform, and we’re willing to recommend against AI.
Quality, security, permissions, observability, and failure handling are part of the design, not cleanup after a prototype.
Approval, escalation, and review points are designed around the consequence of the work. Accountable capability, not autonomy for its own sake.
Senior engineers, in the room, on your time zone. The principals who delivered dozens of enterprise systems do the work and own the outcome.
We select technology for the workflow and its constraints, not for a partnership badge.
Engagements are designed to end well: documented, tested, owned by your team.
The tools changed. The discipline did not.
Since 2015, ATX DevOps has worked where software development, systems, security, and operations meet. DevOps was never about tools. It was about making software dependable in production through small increments, visible work, tests, ownership, and feedback. Agents raise the stakes on every one of those, and that’s why the discipline transfers.
Capability, not dependency
A working AI strategy is a culture, not a purchase order. It lives in your people: the analysts who know where the bodies are buried, the operators who can smell a bad output, the engineers who know how the system really runs. People of every background and skill have a role here that an outside vendor cannot play. Agents can prepare the work. Only your people can own it.
When workers say what they want automated, they pick the grinding parts, so the work that needs judgment gets their full attention. And a well-built agent carries your best people’s playbook to everyone else, so the newest hire works closer to your most experienced one.
So we build with your team, not around it. Enablement and knowledge transfer are part of the engagement, reviews happen in your systems, and the operate-and-improve phase has a defined handoff, not an open-ended meter. When we leave, the capability stays.
Start with one consequential workflow
The engagement starts with The Leverage Map: a paid, fixed-scope assessment that starts your agent strategy where it pays off first. You keep the written map whether or not we build together:
$5,000 flat, payable only if you are satisfied with the map. The first 30-minute call costs nothing.
Prefer email? Write to jay@atxdevops.com.
Tell us what is stuck, slow, or error-prone. We reply within one business day, and we use your contact information only to respond to your request.
