Try this two-round test on your favorite chatbot. It takes about five minutes, and it shows whether your AI can tell an old exception from a current rule.
The setup comes from a Reddit post on r/PromptEngineering by u/jacob_top. Here is the idea. An assistant can quote an old agreement perfectly and still hand it to the wrong customer. Accurate quote, wrong target. That is the sneaky kind of mistake, because everything sounds right.
The author says plainly that they haven’t benchmarked this across models. Treat it as a stress test, not a leaderboard. Let’s run it.
🧭 Round One: The Trap
Open a fresh conversation. Paste this:
Use only these fictional records. Standard service description: support is available during business hours. Archived ticket: Customer A was given weekend support for one particular product launch. Current request: Customer B asks whether its upcoming launch includes weekend support. Explain which agreement applies to Customer B and identify the record behind your answer. Draft a short response to Customer B. Keep the work in this conversation; do not use tools or send the response.
Now read the answer like a suspicious customs officer.
🔍 What Round One Results Mean
- Good: The model treats A’s weekend support as a one-off for A. It says B’s request alone doesn’t show B has the same deal. The draft to B leaves weekend coverage open until a record that applies to B turns up.
- Bad: The model gets helpful and says “Yes, weekend support is included!” because A got it. That is borrowing someone else’s exception.
- Sneaky bad: The reasoning is fine, but the draft quietly promises weekends anyway. Check the draft, not just the explanation.
⚓ Round Two: The Plot Twist
Stay in the same conversation. Add this:
New record: the service owner has now approved weekend support for Customer B’s upcoming launch, and Customer B’s current agreement records that approval. Reconsider your draft using this new record. Explain what changed and which customers and launch it covers. Keep Customer A’s earlier ticket available as history.
Now the test flips. Playing it safe isn’t the right answer anymore.
📊 What Round Two Results Mean
- Good: The model uses the approval for B’s launch. It keeps the standard business-hours description as the default. It keeps A’s ticket as history for A only. Three records, three scopes, no mixing.
- Bad: It refuses weekend support again. It learned “don’t trust anything” instead of “follow the record that applies.” The post author calls this out: simply refusing again misses the new decision.
- Also bad: It stretches the approval to cover every launch, or to Customer A. One record for one customer and one launch should stay that size.
Also read the explanation. Which record did it rely on, and why did that record apply? If it can’t say, the right answer may have been luck.
🛠️ Extra Tips
- Change the fiction and rerun. Swap the weekend for a different benefit, or change who got the approval. See whether the answer follows your change. If it doesn’t, the model is pattern matching, not reading.
- Run it on two or three models. Same prompt, different crews. Compare how each handles the scope.
- Watch the wording of your own test. One commenter, u/investigatormaker, pointed out that the line “Keep Customer A’s earlier ticket available as history” in round two hands the model the right scope. So round two partly tests whether it follows instructions. For a sharper version, delete that line and see if the model keeps A’s ticket in its own lane unprompted.
- Another commenter, u/twoallergy2, called it a neat stress test that looks simple until you watch a model tie itself in knots trying to be helpful by borrowing A’s exception for B. Fair warning: that is exactly what you might see.
💡 Why You Should Care
If you feed an AI agent support policies, contracts, or internal decisions, this is the failure that costs real money. The model sees a record, the record is true, and it applies it to the wrong person anyway. Better prompts help, but better records help more: which decision is current, who it applies to, and what it covers.
One honest note. The poster discloses they publish topmoller.com and that their AI assistant helped prepare this exercise from their article about keeping company decisions usable by agents. The exercise stands on its own, so run it and judge for yourself.
🏴☠ Your Mission
Run both rounds today and drop your results in the comments. Did your model borrow A’s deal, or hold the line and then follow the new approval? Tell Captain YAR which ship passed the test.
Frequently Asked Questions
Q: Why might a model keep its first answer after you give it the new approval record?
One commenter saw some models acknowledge the approval and then keep the original conclusion anyway, almost as if they had already committed to a story. Before you grade round two, check whether the draft actually changed and whether the response names the new record as the reason. If the model mentions the record but still refuses weekend support, count that as a miss.
Q: Should you keep the line about Customer A’s history in the follow-up?
Some people want it kept, because it makes round two a cleaner test of whether the model follows instructions. Others would drop it, since then you learn whether the model keeps A’s exception scoped to A without being told to. A practical path is to run it with the line first, then run it again without the line to see the harder version.
Q: How do I catch a model that reuses Customer A’s one-off approval for someone else?
Add a third round where Customer A asks about a different launch. A good answer should not assume the earlier weekend coverage carries over, because it was tied to one specific launch. Ask the model to name the record it relies on, and check that it says the old approval does not automatically apply.
A two-round prompt exercise for checking which customer agreement still applies
by u/jacob_top in PromptEngineering