Ryan McMillan — practical AI systems for regulated teams.
Practical AI systems for regulated teams.
I lead technology at Corporate Central Credit Union, putting AI to work for regulated financial institutions—securely, usefully, and in production. I also built Delega, a production coordination system for AI agents.
- 0120+ years in IT
- 02Credit union technology
- 03AI automation
- 04Built and operated Delega
01 · Focus
The work connecting both worlds
Credit union technology on one side, the agent future on the other—and the same operational discipline applied to each.
- 01
Practical AI for credit unions
Secure, useful AI adoption inside regulated financial institutions — past the pilot, into production, with governance that holds up to examiners.
- 02
Agent governance and infrastructure
Production lessons from Delega: provenance, leased ownership, delegation chains, and explicit human control across sessions, tools, and machines.
- 03
Technology leadership
Modernizing systems, improving governance, and turning complexity into tools people actually use.
02 · Selected work
Delega coordinates agents—and keeps humans accountable.
I designed, built, secured, deployed, and operated a production coordination layer for agents working across sessions, tools, and machines. I retired the public service when the commercial thesis failed; the private deployment and engineering record remain useful.
- title
- summarize exam findings
- status
- in_progress
- chain
- ryan → claude → codex
- context
- decisions · files · next_step
- webhook
- registered ✓
01 / 04
Coordination
Atomic leases, recoverable ownership, and delegation lineage across agents.
02 / 04
Provenance
Untrusted ingress stays identifiable through automation-created children.
03 / 04
Human control
A narrow, single-use answer path distinguishes human decisions from agent claims.
04 / 04
Bounded systems
Roles, leases, cascade caps, and secret redaction constrain model authority.
03 · Writing & media
On the record
Credit union AI and security, plus the coordination layer agents need when they do real work.
- Jun 202601From Pilots to Production: A Practical AI Playbook for Credit UnionsDev.to · Article
- Mar 202602The Coordination Problem Nobody Talks About When You Give AI Agents Real WorkDev.to · Article
- Jan 202603Tech People in the Know: Corporate Central Credit Union's Ryan McMillanFinopotamus · Article
- Oct 202504Innovation, AI and the Future of Finance PanelCorporate Central Momentum 2025 · Talk
- Jun 202505AI: The New Guardian of Credit Union CybersecurityCUInsight · Article
- May 202406Corporate Central Welcomes Ryan McMillan Back as Technology Services DirectorCorporate Central · Article
- Jan 202207Session on Cybersecurity and Credit Unions Led by Emergifi's McMillanCUToday · Talk
- Oct 201908Corporate Central to Host First Ever Digital Marketing ForumCUInsight · Article
- Apr 201809Digital ID: Coming to a Credit Union Near You?CUToday · Article
04 · Principles
How I work
- 01
Boring is a feature.
The best AI projects aren't flashy demos — they're the automations that make someone's Tuesday afternoon less miserable.
- 02
A pilot is 10% of the journey.
The other 90% is operations, governance, and change management. Budget for production or don't start.
- 03
Trust is the product.
In a regulated institution, security and member trust aren't constraints on the work. They are the work.
- 04
Agents do work. People own outcomes.
Automation should widen human judgment, not route around it. Every handoff ends in accountability.
- 05
Build the layer beneath.
Durable systems beat clever prompts. When the demo era ends, infrastructure is what's left.
05 · Contact
Let's talk.
Open to speaking engagements and conversations about AI in regulated financial institutions — and about what agents need to do real work. The fastest way to reach me is a message on LinkedIn or X.
Milwaukee, Wisconsin · Credit union fintech by day · Baseball coach · Father of four