In this article
The question
In my own agent-assisted build, I keep approval at shipping, production data and direction. For sales, I want the same clarity about who can say yes to each action.
Before a message goes, my bar is that the reviewer can see the recipient, the claim and the research behind it, then change or stop the action. Letting an agent prepare work should come with a clear account of what still needs a person's decision.
This is where research earns its place in the workflow. A reviewer who receives only a confident draft still has to reconstruct why this buyer was chosen, what the source said and which parts are assumptions. I want that work visible before the approval.
Put the decision in front of the right person
In an r/techsales discussion[1], u/tangosukka69 described agents that researched accounts and prepared prospecting emails in Gmail drafts. The seller said they would “review, make slight tweaks, and send.”
That puts a person before the send. The post's productivity claims are unverified, and the workflow alone cannot establish that the review catches unsupported claims.
I would ask what that person sees beside the email. Can they open the source behind the buyer claim? Can they tell whether a hiring event is an observation or a diagnosis? Do they know if a colleague already owns the relationship?
In a separate r/CRM comment[2], u/DistinctDuck8543 suggested teams “flag anything with a number or timeline for manual review” before syncing notes. That is a proposed rule. It does not establish that other wording is safe or that the check prevents every error.
My read is that human review needs a defined question and the evidence to answer it. For a date or number, that may be the exact supporting sentence. For account overlap, it may be the relationship owner's context. The same approve button cannot supply either missing piece.
The approval boundaries I would draw
I start with what the action commits the team to. Research can prepare an assessment while keeping its uncertainty visible. A message can make a claim to a buyer. A commercial promise can commit the company to work or terms.
My engineering approval boundaries are context for this position, not a description of every sales setting in Mach. Sales teams need to name their own reviewer and decide which actions may proceed under an agreed policy.
| Action or uncertainty | Who I would involve | What needs a decision |
|---|---|---|
| A buyer claim has an unclear source | Someone who can open and interpret it | Whether the claim can be used as written. |
| Another seller owns an active conversation | The relationship owner | Whether this contact helps the conversation. |
| A call is the next step | The seller responsible for it | What to discuss and what happened. |
| A message makes a price or delivery commitment | The person responsible for that promise | Whether the terms and scope are authorized. |
| A recurring draft matches an agreed policy | The configured reviewer, where required | Whether this particular case qualifies. |
These are the boundaries I would use to design the process. They are not a claim that Mach automatically routes every exception to the ideal person.
The NIST AI Risk Management Framework[3] calls for clear responsibilities and defined human oversight. It does not prescribe a sales approval screen. For me, the practical application is to name who can stop the action and give that person the evidence needed to decide.
What Mach currently makes configurable
Mach's playbook source offers review for every draft, no routine review, the first case for a company, or review until a configured approval history is met. A writer's unresolved question can also send the move to review.
The approval-history rule uses recent approvals without edits. I regard that as a process signal. It does not prove the next claim is true, that the buyer's circumstances are unchanged or that the recipient should still be contacted.
Before reducing review, I would want to know what kinds of claims the policy covers and what still requires attention. A supported recurring message and a new customer-result claim may need different treatment. The team should be able to explain that choice without saying the agent has become trustworthy in every situation.
The engine also gives human work a place in the sequence. Calls and some other actions become tasks for a person to perform and record. The useful check is whether the right person actually receives the task with enough context.
Keep unresolved research and instructions visible
An earlier Mach build account describes a 14-step briefing where one instruction could not be placed in the drawing. The previous rule rejected the whole drawing. The published account describes retaining the usable drawing and showing the unresolved instruction instead.
The smaller regression example in that account is separate from the original briefing and reports no campaign outcome. I take a narrower lesson from it: the person reviewing the work should be able to find what remains unresolved.
I want the same treatment for research. An unknown budget should remain unknown. A possible need should appear as a question to investigate. A missing source should leave the claim unsupported. Otherwise, the reviewer may approve a tidy-looking answer without seeing the decision still waiting underneath it.
Reduce review by improving the work that reaches it
A queue full of identical approval requests can encourage skimming. An unowned queue can leave a useful message waiting until its information is old.
I would use the reasons for edits and holds to improve the work before it reaches that queue. Repeated missing evidence calls for better research. Repeated confusion about the offer calls for clearer instructions. Repeated account overlap calls for better ownership context.
That is a review practice I recommend, not a claim that Mach automatically learns the correct policy. After a rule changes, keep sampling the work. Earlier approvals cannot establish the quality of future claims.
For an action-by-action map, see which AI sales actions should need approval. My aim is that the person saying yes can explain the action they authorized and the evidence they used.
How this post was made, 5 November 2026: AI assisted research and drafting from author-provided approval boundaries and principles. Public quotations were checked, and review modes and human-task paths were inspected in the source snapshot for Mach's deployed build. The 14-step history is attributed to its published account. No live workflow or original incident was replayed.
What evidence does your reviewer need before they can approve the next action?
Common questions
Does human review guarantee accuracy?
A reviewer can miss a problem or lack its source. Review is more useful when the evidence and the decision are visible, and the person has authority to stop the action.
Can a team approve a recurring message pattern?
A team can define that policy. Check the workspace's actual settings and the facts of each case before assuming a later action qualifies.
What does approval history tell us?
It records how earlier drafts were handled. The inspected trust rule uses approvals without edits. It does not measure the truth of every claim or a change in buyer circumstances.
Should preparing a draft require the same approval as sending it?
The consequences differ. Define the permission for each action separately so allowing preparation does not silently authorize contact with a buyer.
Who should review a possible account overlap?
Start with the relationship owner, if known. A generic reviewer may be able to check the words while still lacking the context to decide whether contact is appropriate.
What if one playbook instruction cannot be carried out?
Keep the original instruction visible and ask what should happen to it. A usable drawing should not make the unresolved instruction disappear or imply it became a supported action.
How does approval relate to an uncertain send?
Approval decides whether an action should proceed. A lost response after the attempt creates a separate problem: establishing whether the message sent.
