ABOUT THIS EPISODE
Your shipping carrier sends a bill. Your invoicing system sends invoices. Nobody has ever compared the two, because the systems were never connected and the reconciliation was a spreadsheet import somebody did by hand. Drummond's CIO pointed an MCP at both sides, extrapolated a year out, and found more than $600,000 in shipping charges the company had absorbed and never passed on to its clients. The same tooling caught carrier overcharges worth filing claims against.
Chris Brock runs IT for a 90-year-old family-owned commercial print and fulfillment company in Atlanta and Jacksonville, just under $100 million in revenue, where the industry-standard ERP has atrocious reporting and a lot of the data going in is hand-typed. The working pattern is specific and repeatable: build an MCP over whatever legacy API or Postgres connection exists, plan on a frontier model, then hand that written blueprint to a cheaper model to execute inside explicit "only work in these lanes" guardrails. In CI/CD, agents security-check and end-to-end test other agents before a developer signs off. Licensing is centralized and allocated mainly to IT and some management, less for cost than for the MSA problem: a CSR dragging a customer-address CSV into an open model is a real contractual exposure. Nothing runs lights-out. Every process still has a human on green light, red light.
The part that answers the budget question is what happens after the win. A hard-dollar number converts the next AI request from a forecast into a case study, and it changes how you can approach a department. Lead with evidence of what a prior automation actually recovered and people stop hearing "we are automating you out of a job." The distinction Brock draws is between busy and strategic, not between human and machine.
Key takeaways:
- Reconcile two systems nobody has ever compared, such as a carrier bill against your own invoices, and extrapolate a year out before you ask for any AI budget. That is where the hard-dollar number comes from.
- Plan on a frontier model, then hand the written blueprint to a cheaper model to execute. Put the "only work in these lanes" constraints in writing first, because an unconstrained agent gets a mile down the road before you catch it.
- Put an agent on your agent. Security-check and end-to-end test the output in CI/CD before a developer ever sees it for sign-off.
- Build the MCP over the legacy system rather than waiting for better reporting. Most old software still exposes an API or direct Postgres, which is enough.
- Lead a funding ask with money you already recovered, not a productivity estimate, and open the same way when you go hunting for automatable work so the department does not get defensive.
Watch the video version on YouTube · Full show notes, transcript + takeaways
