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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 taskGet a PDF of all the recommendations for John Smith, our new VP of Sales, by end of day…+
Get a PDF of all the recommendations for John Smith, our new VP of Sales, by end of day today.
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 acceptI need to share the recommendations for Sarah Jones with the hiring committee. Make sure the…+
I need to share the recommendations for Sarah Jones with the hiring committee. Make sure the PDF highlights the ones that specifically mention 'leadership' or 'mentorship' so they can quickly see her relevant strengths.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentMichael Lee, our top candidate for the Senior Engineer role, only has two recommendations, both…+
Our top candidate, Michael Lee, has only two recommendations, both from five years ago.
Michael Lee, our top candidate for the Senior Engineer role, only has two recommendations, both from roles he held over five years ago. This feels like a red flag, but he aced the interviews. I'm afraid the hiring manager will see this as a lack of current support, but I don't want to lose him. What's the likely diagnosis for the dated recommendations, and what's the best next move to address this concern without making him feel scrutinized?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI keep finding that promising candidates have very few or very old recommendations, which makes…+
Candidates often have sparse or outdated recommendations, making it hard to assess them.
I keep finding that promising candidates have very few or very old recommendations, which makes it hard for me to confidently present them to hiring managers. This often leads to delays as we try to get more current references. What habit should I change in my candidate screening process to proactively address recommendation gaps and build a more complete picture of their recent performance?
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.