- Revenue Creator
- Posts
- Guardrails, Not Scripts
Guardrails, Not Scripts
Turn your intuition into rules so your team and future AI can act without you.
Simple Decision Rules That Free You From Every Question
Last week, you made your work visible by listing the main flows in your business and picking one to look at more closely. This week, you will take that single flow and turn it into a simple, clear playbook that someone else can follow. That someone might be a team member today and an AI helper tomorrow.
You are not writing a textbook. You are writing clear instructions that let the business move without you standing in the middle of every step.
The problem in plain language
When there are no shared decision rules, every choice feels special.
Your team might think:
→This situation is different.
→I do not want to make the wrong call so that I will wait.
→The founder usually decides this so that I will forward it.
From your side, it looks like a steady stream of small decisions.
You look at the situation, think it through, and reply. None of these moments are huge, but together they fill your day. If you ever want parts of your business to run with less of you, human autonomy and AI support both depend on the same thing. Clear, simple rules for everyday decisions.You do not need a rule for everything. You just need enough rules so that:
→Your team can act with confidence in typical cases.
→You only see the exceptions and edge cases.
→Any future AI helper can safely handle a first pass within clear boundaries.
A tactical framework: guardrails, not scripts
Think of decision rules as guardrails on a road. They do not tell you exactly how to steer at every moment. They simply mark what is safe, what is not, and when to slow down or stop.
Good rules have a few qualities:
1) They are simple. People can remember them without looking them up every time. | 2)They are specific enough to act on. They refer to clear numbers or conditions, not vague ideas. |
3)They define when to act, when to say no, and when to escalate. They make it clear when the person should decide, and when to pull someone else in. | 4)They work for both humans and helpers. A team member and an AI assistant would reach roughly the same answer if they applied the rule. |
You can start by adding rules to the flow you documented last week. Look at that playbook and ask:
→Where do people hesitate?
→Where do they ask me to decide?
→Where have I made the same decision several times in the same way?
Those spots are where a simple rule will have the most significant impact.
A simple example: decision rules in a client services flow
Imagine a small design studio that works with ongoing retainer clients. They already documented one flow: “Weekly client delivery.”
The basic steps are:
→Review current tasks for each client.
→Decide what fits into this week.
→Do the work and review it.
→Send the update or deliverable.
→Handle any client feedback.
The team is capable, but they often ask the founder questions like:
→The client asked for something outside the original agreement, should we include it?→They want this done by tomorrow, can we promise that?
→They asked for a discount this month, what should I say?
The founder has been handling each question one by one. We can add a few simple decision rules to this flow.
Scope changes →If the request can be done in under one hour and fits the general spirit of the work, include it and note it in the project log. →If it would take more than one hour, add it to a “proposed next month” list and tell the client it will be considered for the next cycle. →If the request would block the current agreed work, escalate to the founder. | Rush requests →If the client asks for a next-day change, check the schedule. →If the change fits into two hours and does not delay other clients, say yes and mark it as a rush. →If it would delay other clients, offer two options: a later date or a paid rush if you support that. →Escalate only if the client insists or if there is a serious relationship risk. | Discounts →If a long-term client (over 12 months) has a one-time issue, you may offer a small discount or credit within a set amount without asking. →For larger discounts or repeated requests, escalate to the founder. |
Now imagine a normal week:
→A client asks for a small extra change. The designer checks the rough time, sees it fits under an hour, and just does it.
→Another client wants a big extra feature. The designer adds it to the next month list and gives a clear reply.
→A third client asks for a last minute change that would delay others. The designer offers two options without guessing.
The founder sees fewer messages. The team feels more confident.
Later, if the studio adds an AI helper for triage or drafting messages, it can use the same rules to suggest replies that the team reviews. This is the pattern you want.
Where AI fits, in simple terms
At this stage, AI does not replace your judgment. It mirrors it. Once you have written rules like the ones above, an AI assistant can help by:
→Reading incoming messages and tagging the rule applies.
→Drafting a reply that follows your rule, for a human to check.
→Highlighting cases that do not match any rule so a person can decide.
The quality of that support depends almost entirely on the clarity of your flows and rules. Traditional autonomy is when your team follows these rules well. AI-supported autonomy is when a helper applies the same rules to reduce the number of decisions humans have to make.
The foundation is the same.