◆ Google Looker

Design Looker explores for users

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 taskBuild an explore for the sales team that allows them to see sales by product, region, and sales…+
Build an explore for the sales team that allows them to see sales by product, region, and sales representative.
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 acceptThe product managers need to analyze user engagement with our new feature. Design an explore…+
The product managers need to analyze user engagement with our new feature. Design an explore that makes it easy for them to slice and dice the data by user segment, time spent, and actions taken, without needing to ask me for every query.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentA new product manager just complained that the 'customer churn' explore is too complex and they…+
A new product manager just complained that the 'customer churn' explore is too complex and they can't get the numbers they need.
A new product manager just complained that the 'customer churn' explore is too complex and they can't get the numbers they need, and I'm afraid they'll revert to asking for manual reports. I can't tell them I might have over-engineered it. What's the most common reason users find explores difficult, and what's the best next step to simplify it while retaining necessary detail?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI frequently get requests from users asking for new fields or aggregations in existing…+
I frequently get requests from users asking for new fields or aggregations in existing explores.
I frequently get requests from users asking for new fields or aggregations in existing explores, which means I'm constantly modifying them. It feels like I'm always chasing their evolving needs. What habit should I change to anticipate user questions and build more flexible, future-proof explores from the beginning, so I spend less time on reactive changes?
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 Google Looker'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.