◆ Google Looker

Manage Looker at scale with System Activity Analytics

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 taskList all scheduled reports that failed to run last night and send the list to the operations…+
List all scheduled reports that failed to run last night and send the list to the operations team before 9 AM.
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 our next platform review, identify our most resource-intensive dashboards and reports.…+
Before our next platform review, identify our most resource-intensive dashboards and reports. Don't just list them; suggest which ones could be optimized for performance or refactored to reduce server load.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentUsers are complaining that the BI platform is painfully slow, and I'm getting pressure from the…+
Our BI platform is slowing down for everyone, but I can't tell if it's a few problematic dashboards, too many concurrent users, or a system-wide issue.
Users are complaining that the BI platform is painfully slow, and I'm getting pressure from the head of data, Mark, to fix it. I can see general performance metrics, but I can't pinpoint if it's specific dashboards, a peak usage time, or a data pipeline bottleneck. What's the most effective way to diagnose the core performance issue and recommend a solution that will actually make a difference by Friday?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI'm constantly reacting to performance slowdowns and stability issues across our analytics…+
I frequently face unexpected performance bottlenecks and stability issues across our BI platform, leading to reactive firefighting instead of proactive management.
I'm constantly reacting to performance slowdowns and stability issues across our analytics platform, often after users are already frustrated. This leads to endless firefighting. What habit should I change to proactively identify potential bottlenecks and manage our platform's health and scalability before these problems impact our business users?
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.