Operations

What an AI-Native Federal Contractor Brings to Your Program Office

Phillip Jo, COO · · 7 min read

Most enterprises pay a deculturation tax. We didn’t.

Every established firm trying to “transform” with AI is paying a hidden tax: deculturation. Their workflows, headcount structures, vendor stacks, and review chains were optimized for a world before agents. Unwinding that is expensive, slow, and culturally painful — and most of the cost gets passed back to the customer, one way or another.

Coa was built after that line. AI came to the fore just 1 years after I joined and I quickly shifted Coa to a simple operating thesis: every back-office function an agent could do, an agent should do, from day one. No inherited PMO templates from a 5,000-person SI. No two-week procurement loops calcified into “the way we do things.” No headcount hired to do work agents already do better.

Today, roughly 85% of our day-to-day operations run on agents. That number is the one we watch — not as a vanity metric, but as the leading indicator of how much value we can return to government as lower price and higher delivery quality.

As senior government executives leading critical decisions on who can best empower their visions and the people tools will serve, Coa adopts a value of radical transparency. Here is how some of our operations run to ensure scaled and compliant delivery while taking in the full cost savings AI can provide.

Scaffolding of Agents

The wrong architecture is one large model with access to everything. We learned that early. The right architecture, for a federal contractor with compliance obligations and audit needs, is context scaffolding: discrete agent teams, each with a narrow context, scoped permissions, and a single departmental owner.

We organize agents the way a mature firm organizes human driven operations — by function.

Coa Operations Finance Cash position Invoice routing Payment scheduling Accounting Ledger reconciliation 1099 / W-2 prep R&D credit capture Legal Subcontract review NDAs Teaming agreements Compliance FAR / DFARS clauses 8(a) / SDVOSB recerts ATO artifact tracking Business Development SAM opportunity triage Capability matching Proposal drafting Delivery / PMO Status reporting Risk register Burndown tracking Subject-Matter Expert Approval Execute
Six agent teams run the day-to-day work across our core functions. Anything with real consequence — legal, financial, or customer-facing — routes to a human subject-matter expert for approval before it executes.

Each box is a small agent team — typically a planner, one or two task agents, and a verifier — operating against a curated context: only the documents, schemas, and tools that function actually needs. Compliance gets the FAR/DFARS clause library. BD gets the SAM feeds and our NAICS register. Accounting gets the ledger and bank feeds. None of them get all of it.

Every agent action with legal, financial, or customer-facing impact is approved by a subject-matter expert — or routed to one — before execution. The agent stack accelerates the work; humans with domain authority retain the decisions that carry consequence.

The breakthrough — the reason the number moved from “automating a few things” to 85% — was what we started calling the half-life of tasks. When an agent team reliably handles a class of work, the task itself shrinks. A proposal review that took two days becomes a four-hour review of an agent-drafted response. The next iteration, the same review becomes a thirty-minute approval of a near-final draft. Every cycle, the human residual halves.

100 75 50 25 0 Mo. 0 Mo. 3 Mo. 6 Mo. 9 Mo. 12 Mo. 15 Time # of tasks
Half-life of tasks. As agent teams learn the shape of their recurring work, the count of tasks requiring direct human handling declines exponentially over time.

Compound that across six departments over eighteen months and the math gets aggressive. With the recent release of multi-agent team frameworks, we crossed 89% on routine task automation. The remaining ~11% sits exactly where it should: judgment calls, relationship work, and the small set of decisions that legitimately require a human on the line.

Less risk, more customer savings, better delivery

Most contractors who become more efficient quietly pocket the gain. We’ve made a deliberate, repeated choice to do the opposite: the savings buy quality and reduce risk on delivery, not margin.

Three concrete things that operational efficiency pays for at Coa:

  • Senior talent a small business wouldn’t normally afford. When the back office costs a fraction of what it would at a comparable firm, we can put a chief medical AI officer, a former VA principal engineer, or a senior security architect on the team. Government gets that bench on the contract.
  • Continuous, lower-risk delivery surveillance. Agents track clauses, ATO artifact freshness, dependency vulnerabilities, and burndown drift continuously — not at monthly checkpoints. By the time a problem reaches a human, it has already been triaged, contextualized, and matched against a playbook. The customer sees fewer surprises.
  • Price discipline at the bid. When the cost-to-serve is genuinely lower, the bid reflects it. We’re not chasing the floor; we’re sustainably below it.
Operational savings Higher quality Senior talent on the contract Lower cost Price discipline at the bid AI speed Continuous, real-time monitoring Government customer
Where the savings go. The savings don't sit on Coa's balance sheet — they flow to the contract as better talent, lower bids, and real-time delivery intelligence.

The honest version of why we made this trade: we care more about the legacy of the technology we leave inside government than the size of our retained earnings. Every member of leadership has worked inside or alongside the federal mission — Army, IRS, VA — long enough to know how important the mission is. We see ourselves as enablers and bridge builders to those imagining the future of federal services not people who “know technology” better than others.