A program office runs on paper that someone signed. A briefing goes up the chain with a name on it. A deliverable goes to the customer with a name on it. A response to a contracting officer goes out with a name on it. The name means a person read the work and stands behind it.
Super Intelligence (SI) changes who writes the first draft. It does not change whose name goes on the final one. That gap is the subject of this piece, and it is the reason we built SAIN around a record. The broader reasoning is in Why SAIN is building the trust infrastructure for AI. Here is the version for a program office, with a checklist at the end you can use this month.
The first pass is where the time goes
Most of the hours in a program office go into the first pass:
- Reading the manual to find the one paragraph that applies
- Summarizing six status reports into one
- Pulling the last three after-action reviews to see whether a problem has come up before
- Drafting the correspondence that someone senior will rewrite anyway
An agent can take that work. It reads faster than any of us, it does not get tired at the end of the week, and it can draft a decent starting point in the time it takes to open the folder.
The hard part comes after. Six weeks later, someone asks where a sentence in the briefing came from. Was it in the source document, or did the agent write it? Who checked it? Was the version that went up the chain the version that person approved?
If the only answer is a chat history and somebody's memory, the program has a problem. The person whose name is on the work cannot show what they reviewed.
Three questions every record should answer
When I talk with program teams, what they need from a record comes down to three questions.
Who asked? Every piece of agent work starts with a request from a person. The record should show who made it, when, and what they asked for.
What did the agent produce? The draft as the agent wrote it, before anyone edited it. Most tools throw this away, and it is the part an assessor most wants to see, because it shows where human judgment came in.
Who approved it, and what did they approve? The decision, the person who made it, and the exact version they signed off on. If the document changed after approval, the record should show that too.
Anchor'd keeps a tamper-evident audit trail of every action, approval, and draft. For a program office that means a record of what was asked, what the SI produced, and who approved it.
Tamper-evident is the important word. Anyone can keep a log, and a log can be quietly edited. In a tamper-evident record, each entry is fingerprinted when it is written, so an entry changed after the fact no longer matches its fingerprint. The graphic below shows the idea with a simple chain of fingerprints.
Agents that stop and ask
A record tells you what happened. It does not stop anything from happening.
That is the second half of the problem. An agent that drafts a summary is low risk. An agent that sends the summary, files it, or deletes something carries more, and the question becomes what happens when it tries something outside its job.
Guardian watches your agents and lets a named person stop them. A human always decides. The agent's unusual action pauses, a person with authority is notified, and nothing moves until that person decides. The decision goes on the record with everything else.
I think of it the way a good supervisor treats a new staff member. You do not watch every keystroke. You set the boundaries, you get notified when someone steps outside them, and you make the call. Guardian is how that works when the new staff member is an agent.
What the assessor sees
Program offices answer to reviewers: inspectors, auditors, security officers, the customer. Each of them will eventually ask how SI is used in the program and how it is controlled.
A policy document answers part of that. A record answers the rest. With Anchor'd and Guardian in place, a program can show a reviewer:
- Every request made to an agent, and who made it
- The draft the agent produced, kept separate from the edited version
- Every approval, with the approver and the version approved
- Every time an agent was stopped, and what the person decided
That turns the question "how do you control your SI?" into a walk through the evidence. Ask the sample record below what a reviewer would ask.
A checklist for your first agent workflow
Start small. Pick one recurring task that eats staff hours, such as a weekly status rollup, a manual search, or a correspondence draft. Then work through this list before the agent touches it.
- Name the owner. One person is responsible for the workflow and everything the agent produces in it.
- Name the authorized person. Decide who can approve an agent's held action and who can stop the agent. Write the names down.
- Set the bounds. List what the agent may read, who it may send to, and what it may never do without approval. Deleting, sending outside the program, and anything you cannot undo belong on that list.
- Require approval on every output for the first month. The approval should name the exact version approved.
- Keep the agent's draft. Store it beside the edited version, so a reviewer can see what changed.
- Review the record weekly. Look at the holds, the edits, and the time the first pass took.
- Show it to your reviewer early. Ask your security officer or assessor what else they would want to see, before the workflow grows.
These are the same rules we give our own agents: ask before an action you cannot undo, stop when an authorized person says stop, and keep a record you do not change.
By the end of the first month you will know two things: how many hours the first pass was costing, and whether your reviewers are comfortable with what the record shows.
Where the work involves controlled information, the agent and its models need to run inside your boundary. That is a separate question, covered in what it takes to run Super Intelligence on a disconnected network. Files that come in with the work deserve a look too, covered in screening what enters the boundary.
Where SAIN fits
SAIN is the Super Accountable Intelligence Network. We build trust infrastructure for industries and government, and the record is at the center of it. Sonara, our training app, is in production for a federal defense program.
There is more on how this applies to defense work on our defense page, and on Anchor'd and Guardian individually. If you are working out how agents fit into your program and what your reviewers will need to see, we are glad to start with your constraints.