◆ Apache Cassandra

Define common business vocabulary

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskAdd 'customer_id', 'product_sku', and 'order_total' to the shared data dictionary, defining…+
Add 'customer_id', 'product_sku', and 'order_total' to the shared data dictionary, defining them as text, text, and decimal, respectively. Make sure 'customer_id' is marked as the primary identifier for customer records.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptReview the existing business vocabulary for 'customer_segment' and 'campaign_name'. Suggest…+
Review the existing business vocabulary for 'customer_segment' and 'campaign_name'. Suggest improvements to their definitions to ensure they are unambiguous and cover all known use cases for the marketing team's new analytics project.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentOur marketing analyst is confused because 'campaign_id' isn't unique across all campaigns, only…+
The new marketing analyst just asked why 'campaign_id' isn't unique across all campaigns.
Our marketing analyst is confused because 'campaign_id' isn't unique across all campaigns, only within a specific year. I'm afraid if we don't clarify this now, they'll misinterpret historical data. We can't just change the existing data model. What's the best way to explain this nuance and prevent future misinterpretations without causing a rework of their current reports?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternWe keep losing time in meetings because the sales team's definition of 'active user' doesn't…+
We keep having discussions where different teams use the same term but mean different things.
We keep losing time in meetings because the sales team's definition of 'active user' doesn't match engineering's. This leads to conflicting reports and wasted effort. What habit should I change to proactively align these definitions before they become blockers?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Apache Cassandra's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.