2011
Hired the VP. Built the CoE. Bought the charter.
A slide with a box in the center and arrows pointing outward. The box was always the same shade of corporate blue. Coaches. A budget. Ambition.
Slide 01
The VP was hired in 2011. You brought in coaches. You built a Center of Excellence. Fifteen years later, that VP is holding a crystal clock, and your organization still cannot release software without a change advisory board meeting and a three-week regression cycle. Now you are standing up an AI Center of Excellence with the same box, the same arrows, and the same eight people.
Slide 02
A slide with a box in the center and arrows pointing outward. The box was always the same shade of corporate blue. Coaches. A budget. Ambition.
It produced meetings, status reports, and maturity assessments. The teams that actually became Agile did it themselves, usually in spite of the CoE.
An Agile coach on every team who mostly attends standups and asks "what are your blockers?" Not faster delivery. Not better software. A new layer of meetings.
If the transformation was going to work this way, would it not have worked by now?
Slide 03
Four proof of concepts, none in production. The steering committee is impressed by the demos. The rest of the organization is still waiting for access.
An AI Champions program where one person from each team attends a monthly meeting and reports back. The Champions attend the meetings. They do not build agents.
A Slack channel with 200 members and four posts per month, three of which are links to articles about what other companies are doing. $6 million spent over two years.
Meanwhile, across the street, a mid-size manufacturer gave everyone AI access on day one, wrote a one-page acceptable use policy, and told their people to automate their own work. Within six months: over 30 agents in production.
Slide 04
That was true in 2022. Custom models, training pipelines, serious infrastructure. Foundation models changed the economics entirely. Building an agent in April 2026 requires the ability to describe what you want done, evaluate the output, and refine. Your supply chain analyst has that skill. Your compliance officer has that skill.
Imagine it is 1995 and your CIO creates the Email Center of Excellence. Eight people. They review every outgoing email for compliance. You want to send a message to a client? Submit a request. Estimated turnaround: five business days. A one-page AI framework gives every team what they need. A 40-page governance document produced by a team that has never built an agent gives you paralysis.
This was the argument for keeping the Agile CoE alive in year five, and year eight, and year twelve. The coordination never produced coordination. It produced meetings and maturity assessments. You did not centralize DevOps forever. You embedded it into every team. The question is whether you do it now or waste eighteen months arriving at the same conclusion.
Slide 05
Slide 06
No engineering background. Building proof-of-concept agents for better patient outcomes on his own time. Describing clinical workflows to an AI the way he would explain them to a new nurse. Medication reconciliation edge cases, shift handoff patterns. Nobody from the hospital's AI team gave him permission.
Four teams. Two high performers, two not. His two strong teams plus agents can now absorb the workload of all four. He finally has to have the conversations he has been avoiding about performance. His company's AI team does not know. They are still finalizing their Q2 tool evaluation report.
Built an agent that monitors equipment maintenance logs and generates exception reports when sensor readings deviate from historical baselines. Not a developer. Spent three days refining it. Runs in production now. Her team gets the report every morning instead of spending half a day pulling it manually. The AI team does not know she built it.
Slide 07
Eight people fully loaded: $1.8M-$2.2M per year. Across twelve orgs assessed this year, centralized teams deployed an average of roughly one agent in their first twelve months. Some deployed zero. Even crediting half the cost to governance, you are paying a million dollars per production agent.
$500 per person per year in licenses. Four hours per week for experimentation. One-page governance framework. For 200 people: $100K in tooling. If 20% of experiments produce an agent saving two hours per week, the math breaks even inside six months.
Built by the people who need them, for the work those people already understand. They stay in production because the person who built it is the person who maintains it. No handoff. No backlog. No dependency on a team across the hall.
Even on the most conservative math, a million dollars per production agent versus $100K and some recaptured time for fifteen is not a close call.
The Agile CoE had the same economics problem. You paid for eight coaches for fifteen years. How much Agile did you get?
Slide 08
Not a pilot. Not a phased rollout. Access. In regulated industries, "access" means access within the guardrails your compliance team already knows how to build. HIPAA-scoped environments, FedRAMP boundaries, data classification tiers. The rules should be infrastructure, not a committee.
What data can agents access? Enforce it at the infrastructure level. What outputs require human review? Build that gate into the workflow. What happens when an agent is wrong? Define the circuit breaker and automate it. Automated tests, security scans, rollback mechanisms. Anyone can deploy with confidence.
If you do not protect the time, it will not happen. Everyone's calendar is already full of the work they are doing the old way.
Turn them into the people who build and maintain the governance pipeline, not the people who review everyone else's work. Measure them on how many agents other teams deployed safely, not on how many documents they produced.
Slide 09
Not a roadmap. Not a vision slide. Not an AI Center of Excellence with eight people and arrows on a slide. If the end state includes a permanent centralized AI team, you have not described transformation. You have described a new bureaucracy.
An organization where building agents is as ordinary as writing an email or opening a spreadsheet. Supply chain builds reconciliation agents. Compliance builds audit agents. Nobody files a request to get permission. AI is not a special initiative. It is how work gets done.
The technology you are trying to scale through a centralized team is the same technology that makes centralized teams unnecessary.
Putting it in a team and expecting it to radiate outward is like putting literacy in a department and expecting the rest of the organization to learn to read by proximity.
Slide 10
Not where you are. Where you are going. What does the engineering organization look like when every team has agent capability? What happens to the coordination layers that exist only because humans were slow? What roles change, what roles disappear, what new roles emerge? If you have not drawn that picture, every mile you drive is a guess.
The VPs and directors who control the calendars, the budgets, the governance models. If they do not understand what agent-driven development looks like in production — not in a demo, not in a slide — they will keep approving structures that block it. Your leaders stopped building years ago, and now they are making architectural decisions about a technology they have never used.
Not "enable" it. Not "champion" it. Teach it. The way you teach any core competency the organization cannot function without. You did not outsource learning to write code. You did not create a Git Center of Excellence with eight people and arrows on a slide. You taught people the skill and you expected them to use it.
Slide 11
Slide 12
You do not have a critical thinking team. You do not have an email team. You stopped having an Agile CoE — or did you? Is someone getting a twenty-year clock in 2031?
The technology you are trying to scale through a centralized team is the same technology that makes centralized teams unnecessary. How did that work out last time?