If you cannot say what it used, do not approve it
Provenance is the cheapest control in this guide and the one most often skipped. It costs one question and catches the entire class of errors that look correct.
Handing marketing work to an agent is not a question of how much it can do. It is a question of which actions require a person, and how that person sees enough to say yes in ten minutes. This is the operating guide: what to delegate first, what stays gated, how to review prepared work quickly, and how trust is earned one job at a time.

Four verbs, in a fixed order: you direct, it prepares, you review, it releases. Every difficult question in this area turns out to be a question about where the third verb goes — and almost every failure is somebody quietly removing it.
That order matters more than it looks. Asking a general assistant for a launch produces a good plan and a bad afternoon: you then copy the page into one system, the emails into another, the event into a third and the automation into a fourth. The plan was never the expensive part. The copying was, and so was reconstructing the context at every boundary — which customers bought before, who is showing intent now, what is already live.
An operator is different in one specific way: it prepares the work where the work lives, using the business knowledge and customer context it has been permitted to use, and it stops in front of you with something you can inspect. Not text you have to move. Not an action already taken. A prepared thing, waiting.
The interesting design question is not how much an agent is capable of doing. It is which actions require a human decision, and how that human is shown enough to make it quickly. Get that pair right and you can delegate far more than you would dare to otherwise, because the cost of being wrong is bounded. Get it wrong in either direction — gates everywhere, or gates nowhere — and you end up doing the work yourself either way.
The first three are the same tests that decide whether a task should be automated at all. The fourth is specific to delegation, and it is the one people discover the expensive way.
Notice that the third test is the only one that generates work for you. Writing down the offer, the terms, the voice and the history is the part that makes everything afterwards possible, and it is the part people skip because it does not feel like automation. An agent working from thin context produces confident, structurally perfect, entirely generic work — and you will spend longer fixing that than you would have spent writing the source material once.
The right-hand column is not permanent. Most of it moves left once the source material exists, the job has been done by hand a few times, and you have watched a gated version run. What does not move is anything you would put in a contract.
Treat the gate as a design pattern rather than a safety feature bolted on afterwards. You are deciding, once, which classes of action a person must authorise — and then building everything else to run freely inside that boundary.
And what does not: work that only produces a draft, analysis and summaries, and changes scoped to a single record you can undo in a click. Gating those feels responsible and is actively harmful, because every unnecessary gate spends the attention you need for the ones that matter.
If somebody is clearing dozens of gates without reading them, the risk is exactly what it was before — and it is now documented as reviewed, which is worse. The fix is fewer gates, better read: consolidate. One gate on a whole prepared launch, examined properly, beats nine gates on its parts that everybody clicks through on a Friday afternoon.
If the brief was wrong or the source material was stale, no amount of careful reading will rescue the result — and checking takes about ninety seconds. What did it use? Is that current? Is that the audience I meant? Then read.
After that, the review is not a general act of scrutiny. It is a short routine per kind of artifact, and the routines are short on purpose: a review you can complete in ten minutes is a review that will actually happen every time, which is worth far more than a thorough one that happens twice.
One rule sits above all three. If a review is taking substantially longer than ten minutes, the problem is the size of the job rather than your thoroughness. Ask for it in pieces — the segment first, then the sequence, then the schedule — because a prepared artifact you cannot hold in your head is one you will eventually approve on vibes.
Delegation has a budget as well as a boundary. In Agorix that budget is AI Credits, which measure eligible Operator work — preparing funnels, pages, emails, segments, workflows, course material and audits — and each paid plan includes a monthly allowance.
| Plan | Included AI Credits |
|---|---|
| Launch | 2,500 per month |
| Growth | 10,000 per month |
| Pro | 25,000 per month |
| Business | 40,000 per month |
| Agency / Enterprise | 75,000+ per month |
Those are the current published allowances; the pricing page is the authority on them, along with credit packs for months that need more than the plan carries.
The estimate shown before a larger task is the most useful part of this whole mechanism, and it is worth treating as a conversation with yourself rather than a toll. It arrives at exactly the moment when changing the scope is still free — which is the same reason an approval gate is placed before execution rather than after it.
This is worth knowing before you plan a first month around it. The current Agorix self-serve trial covers the connected platform but does not turn on the AI Operator; the monthly AI Credit allowance arrives with a paid plan, and a walkthrough is currently how you see an agent workflow end to end before choosing one.
Prepared work is worth reviewing when it was built from your real customer story rather than from a prompt window. The AI Operator is a paid-plan capability — the current self-serve trial does not enable it — so the trial is where you see the connected record itself, and a walkthrough is where you watch an agent work on it. See how the AI Operator works.
That sentence is the whole safety model. An agent that has prepared forty good follow-up sequences has earned nothing at all about pricing pages, and treating competence as transferable is how organisations end up surprised.
Write the demotion rule at the same moment you grant the approval, in the same sentence: one materially wrong output returns this job to gated review. Deciding that in advance is the entire trick, because the day after something goes out wrong is the worst possible day to have a conversation about policy — everybody is defending a position instead of applying a rule.
What each rung looks like in practice depends on the roles, permissions and controls configured in your workspace, and on what the platform currently supports. Confirm the activity history and the reversibility you actually have before granting anything on the third rung — that rung assumes you can see what happened and undo it.
Wrong output is information about your inputs far more often than it is information about the agent. Reading it that way is the difference between improving the system and rewriting the same brief forever.
In every case the response is the same shape: shrink the job, not the ambition. Put that job back behind a gate, fix the input the failure pointed at — the disagreeing documents, the thin source material, the brand guidance that is a list of adjectives — and run it again on a smaller scope. What does not work is asking more insistently.
Provenance is the cheapest control in this guide and the one most often skipped. It costs one question and catches the entire class of errors that look correct.
None of this is caution for its own sake. A review you trust and can finish in ten minutes is what makes it reasonable to hand over the next job, and the one after that.
Start with one job. Run it as drafts until the corrections are cosmetic, move it behind a gate, and leave it there while you learn what it does on an unusual week. Add the second job only when the first has stopped being interesting — which is the same restraint that governs your first marketing automations, for the same reason.
A named point in an automated job where prepared work stops and waits for a person, with the actual change visible before anything is released. It is not a notification, and “let me know when it is done” is not a gate. Four properties make one real: the reviewer sees the change rather than a summary, a named person owns clearing it, the default when nobody responds is that nothing happens, and there is a record of who approved what.
Customer-facing and consequential work should sit behind a human review step — that is the whole design pattern, not a temporary caution while the technology improves. Gate anything you cannot recall, anything that spends money or changes access or price, anything with a large blast radius, and anything touching records you could not reconstruct. Drafts, analysis and single-record changes you can undo do not need a gate, and gating them dilutes the attention available for the gates that matter.
No. The current Agorix self-serve trial does not enable the AI Operator. Paid plans include a monthly AI Credit allowance for eligible Operator work, and a personalised walkthrough is currently the way to see an agent workflow before you choose a plan — the pricing page carries the current allowances and the exact trial terms. The trial itself covers the connected platform: a payment method is required, nothing is due on the day, and cancelling before the first charge costs nothing.
Check the inputs before the output — a wrong brief or stale source material cannot be rescued by reading the result more carefully, and the inputs take ninety seconds. Then run a routine per artifact: for a funnel, the offer terms, where money changes hands, what happens to non-converters, and what sends without a further gate; for an email batch, the first and the last in full plus every factual claim about the business; for a segment, the count before the definition and five spot-checked records. If the review runs past ten minutes, the job was too large.
AI Credits measure eligible AI Operator work — preparing funnels, pages, emails, segments, workflows, course material and audits. Each paid plan includes a monthly allowance, from 2,500 on Launch up to 75,000 or more on Agency and Enterprise. Included credits reset each month; purchased credit packs are prepaid and currently roll over for twelve months, which is why a predictable heavy month is usually an argument for a pack rather than a permanent tier change. Before a larger task begins, an estimated range should be shown so the scope can be reviewed first.
Grant standing approval to a specific job, never to an agent in general. Five conditions: the job is narrow rather than a category, it has run gated often enough that you can predict the output before reading it, it is reversible and you have reversed one to prove it, it is capped on volume and blast radius, and it has a named owner with a review date already in the calendar. Write the demotion rule at the same time — one materially wrong output puts the job back behind a gate — because nobody wants to argue about policy on the day something goes wrong.
Events, courses, campaigns, checkouts and workflows on one customer record — with human approval points for consequential work. The AI Operator itself is a paid-plan capability and is not enabled in the current self-serve trial; book a walkthrough to see an agent workflow run end to end.
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