◆ Google Looker

Perform daily Looker tasks

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 taskRefresh the 'Daily Sales' dashboard for the East Coast region and send a snapshot to Mark by 9…+
Refresh the 'Daily Sales' dashboard for the East Coast region and send a snapshot to Mark by 9 AM, highlighting any sales over $10,000.
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 acceptBefore the daily sales report goes out, ensure it's actionable for the sales managers.…+
Before the daily sales report goes out, ensure it's actionable for the sales managers. Highlight any regions or product lines that are significantly underperforming yesterday's targets and suggest a concise summary for the executive email.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe 'Customer Support Tickets' dashboard is showing zero new tickets for the last 12 hours,…+
The 'Customer Support Tickets' dashboard is showing zero new tickets for the last 12 hours, which is impossible.
The 'Customer Support Tickets' dashboard is showing zero new tickets for the last 12 hours, which is impossible. Our support team is active 24/7. The data source is 'Zendesk_API_Connector', and I checked the API status, which seems fine. The Head of Support needs accurate numbers for their morning stand-up, and I'm worried about a silent data pipeline failure or an unexpected filter. What's the most common reason for a critical real-time dashboard to suddenly flatline, and what's my immediate next step to get it reporting correctly?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI often find myself manually checking critical daily dashboards because I don't fully trust the…+
I often find myself manually checking critical daily dashboards because I don't fully trust the automated refresh or data integrity.
I often find myself manually checking critical daily dashboards because I don't fully trust the automated refresh or data integrity. This takes up valuable time and creates anxiety. What habit should I change to build more confidence in the daily data processes and reduce the need for constant manual verification?
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.