◆ Elasticsearch

Query with match by multiple fields

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 taskQuery the 'product_catalog' index. Find all products where the 'category' is 'Electronics' and…+
Query the 'product_catalog' index. Find all products where the 'category' is 'Electronics' and the 'brand' is 'Acme Corp'. I need the top 10 results.
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 marketing team needs to identify high-value customers. Query the 'customer_interactions'…+
The marketing team needs to identify high-value customers. Query the 'customer_interactions' index to find users who have 'purchased_plan' set to 'Premium' AND have interacted with 'support_ticket' in the last 30 days. Make sure the query is performant for large datasets and returns relevant results for the campaign.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentI'm trying to find specific log entries in 'application_logs' where 'error_message' contains…+
My multi-field search is returning too many irrelevant results, and I can't pinpoint why.
I'm trying to find specific log entries in 'application_logs' where 'error_message' contains 'timeout' and 'service_name' is 'payment_gateway', but I'm getting a ton of noise. The incident response team needs these logs urgently to diagnose a critical issue. I'm afraid I'm missing a key parameter or using the wrong operator. What's the best way to refine this multi-field query to get only the highly relevant results without missing critical information?
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 for complex searches across multiple fields, and I often spend a lot…+
I spend too much time tweaking multi-field queries to get precise results for ad-hoc requests.
I frequently get requests for complex searches across multiple fields, and I often spend a lot of time iteratively refining the query to get the precision the user needs. This slows down our response to business questions. What habit should I change in how I approach query construction for multi-field searches to more quickly arrive at accurate and relevant results?
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 Elasticsearch'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.