Agent to Agent Workflows

Three levels of autonomy

Nobody goes from human-handled to fully automated in one step, and a vendor who suggests you should is telling you something about themselves. This is the same issue handled three ways — suggested, drafted for approval, and resolved end to end — so you can decide where each kind of work sits, and move it when the evidence supports it.

  • The same issue at three levels of autonomy
  • Set per issue type, not once across the platform
  • A person approves anything customer-facing by default
  • Move a category up when your own queue justifies it

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Autonomy is a dial, and most deployments treat it as a switch

The two common failures are opposites. Turn automation on everywhere and the first confidently wrong answer to an important customer costs more trust than the project saves. Keep everything human and you have bought an expensive suggestion engine.

The real question was never whether to automate. It is which work is safe to automate — and safe is a property of the issue type, the customer it belongs to and what happens if the answer is wrong, which cannot be settled in a workshop.

Three cards covering the ways autonomy gets decided badly: automating everywhere, keeping every interaction human, and settling the boundary in a workshop before anyone has evidence.
The first two are opposite failures and the third produces a policy the queue disagrees with, quietly, for two quarters.

The three levels, and the exit from each

The levels are the easy part. The handover out of each one is what deserves the scrutiny.

  1. Step 1

    Suggested

    The system proposes and the agent decides. Every suggestion accepted or rejected is evidence about whether that category is ready to move up.

  2. Step 2

    Drafted and approved

    The response is written, with its reasoning and sources attached, and a person releases it.

  3. Step 3

    Handled end to end

    For issue types where the evidence supports it, the interaction resolves without a person — and stays reviewable afterwards like any other.

  4. Step 4

    The exit at every level

    Each level has a defined point where it stops and hands to a person with the work attached. This determines how a bad case ends.

Four stages covering the three autonomy levels — suggested, drafted and approved, handled end to end — and the defined exit each one has to a person with the work already done.
The levels are the easy part. The fourth panel is the one worth examining before anything is switched on.

What makes a phased approach defensible

You are not deciding how much you trust AI. You are deciding which specific work it handles.

Set per issue type, not per platform

A password reset and a safety-critical fault do not belong at the same level, and no global setting is right for both. Autonomy per category is what makes the decision reviewable.

The default is that a person approves

Anything reaching a customer is approved by a human unless you deliberately decided otherwise for that category. That is the correct default for a system that will sometimes be wrong.

Categories move on evidence

Every accepted suggestion and edited draft says something about whether a category is ready. A level change should follow what happened in your queue, not a projection.

A five-row table assigning a different autonomy level to each issue type, with the reason for it and what the consequence would be if the answer were wrong.
No single global setting can be right for both the top row and the bottom one, which is the whole reason this is a per-category decision.

Why the usual approaches fall short

Two of these are too fast, one is too slow, and one is unanswerable.

Full automation from day one

The first confidently wrong answer to an important customer costs more than the automation saved.

Suggestions only, indefinitely

Safe and static. It keeps a person in every loop including the thousands that never needed one.

A single global autonomy setting

Forces one answer across password resets and safety-critical faults.

Deciding the boundary in a workshop

Produces a policy based on what people imagine is in the queue. The queue disagrees.

Two columns comparing full automation on day one, suggestions only forever, a single global autonomy setting and deciding the boundary in a workshop with per-category levels moved on evidence.
A single global setting is the quiet failure: whichever level you pick is wrong for a large share of your volume.

What things are called

Worth pinning down, because "autonomous" is used to mean all three of these.

Agent assist
Suggestions offered to a human, who accepts, edits or discards them.
Draft and approve
The response is fully prepared and a person releases it.
Autonomous resolution
The interaction is handled end to end without a person in the loop.
Autonomy level
Which of those applies — set per issue type rather than once across the platform.
Handover point
The defined condition at which an automated path stops and passes to a person.
Confidence threshold
How sure the system has to be before it acts rather than asks.

Frequently Asked Questions

At suggestion level across the board, then move individual categories up as your own evidence supports it. Starting anywhere else means guessing, and the cost of guessing wrong is asymmetric — a bad automated response is far more expensive than an unused suggestion.

Agent to Agent Workflows

Decide it on your own categories

Bring your issue-type breakdown and we will work through which categories are genuine candidates to move up a level, and which ones should stay with a person.

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