A rule turns a decision you do not want to remake every time into a condition.
The system then applies it the same way, every time.
Rules keep speed from becoming chaos.
AI can prepare more work than a person could produce manually. That makes the quality of the operating rules more important, not less.
Without rules, a system has to guess what “good,” “safe,” “ready,” or “on brand” means.
Useful rules are concrete enough to change behavior. “Be careful” is not a rule.
“Never publish a price, health claim, customer name, or partnership without human approval” is. The free starter has rules like this you can copy.
Safe to automate: approved evergreen posts using claims already verified in the source library.
Needs review: a strong opinion, a customer story, a new product promise, or anything tied to a live event.
Never do: invent a testimonial, publish private information, or copy another creator’s words and images.
The five rules every AI workflow needs
1. Input rules
Define which sources the system may use and which source wins when information conflicts.
For example: current product data beats an old brief; direct customer language can inform messaging but cannot become a fabricated quote.
2. Decision rules
Explain how choices are made.
A prioritization system might weigh revenue signal, urgency, effort, energy, and dependencies instead of simply sorting by due date.
3. Output rules
Describe the shape of a finished result: length, structure, required context, links, sources, status, and next action.
Examples are often stronger than adjectives.
4. Approval rules
Identify where human judgment remains essential.
Taste, legal risk, spending, public publishing, customer communication, and irreversible actions usually deserve a clear checkpoint.
5. Failure rules
Tell the system what to do when information is missing, a tool is unavailable, or confidence is low.
A good failure mode asks, pauses, or escalates. It does not quietly invent.
Write rules in normal language.
- Start with a verb: ask, check, stop, compare, send, wait.
- Name the condition: “when the price is missing,” “before anything publishes,” or “if two sources disagree.”
- Name the action: “ask Dani,” “use the current product record,” or “leave the item in review.”
- Give one positive and one negative example when taste is involved.
- Change the rule after a real failure instead of correcting only one output.
The goal is not to predict every edge case before you begin.
Build a small set of clear rules, run the workflow on real work, and let each failure teach the system how your business actually operates.
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