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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
See the prompt↓All LinkedIn tasks

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskWe need three senior backend engineers for the cloud team. Run a boolean search targeting…+
We need three senior backend engineers for the cloud team. Run a boolean search targeting backend, Go, Python, distributed systems, and AWS, limited to candidates in the Bay Area with open-to-work status. Review the top 50 results, shortlist ten who have at least five years in backend systems and two of those keywords in their profile, and send the shortlist to Marco in engineering for quick feedback by Wednesday.
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 I send this candidate list to Marco, surface the strongest signals up front: show years…+
Before I send this candidate list to Marco, surface the strongest signals up front: show years of backend experience next to each name, list the two most relevant technologies from their profile, and flag any open-source or production scale features. Highlight anything that suggests immediate fit for our cloud stack.
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 ran a search for senior backend engineers and the results are noisy — product engineers,…+
My search returned many false positives for ‘backend’.
I ran a search for senior backend engineers and the results are noisy — product engineers, devops, and full-stack folks with a single backend mention. Marco expects a clean shortlist by Wednesday. I’m unsure whether to tighten keywords and risk missing diverse candidates or keep it broad and spend hours triaging. What search adjustments will most efficiently surface true backend system engineers?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternOver several hiring cycles I spend too much time filtering search returns because my queries…+
Searches keep returning noisy profiles and I waste time triaging.
Over several hiring cycles I spend too much time filtering search returns because my queries pull in unrelated roles. I think my keyword approach is the problem but I don’t know which patterns to change. What search strategy and naming conventions should I adopt to reduce false positives and cut triage time in half?
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 LinkedIn'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.