◆ LinkedIn

Research company pages

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 taskI need a quick dossier on Nimbus Tech before the call. Pull recent company posts, executive…+
I need a quick dossier on Nimbus Tech before the call. Pull recent company posts, executive changes, open roles in sales and product, and any news about funding or layoffs in the last 60 days so I can ask informed questions.
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 dig through Nimbus Tech’s page, highlight the two posts most likely to matter to a…+
Before I dig through Nimbus Tech’s page, highlight the two posts most likely to matter to a hiring conversation: one about strategy or product and one about hiring or org change. Flag anything that contradicts their stated strategy or raises a recruiter’s red flag.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentNimbus Tech’s company page is full of optimistic product posts but their open roles show many…+
Their page claims growth but hiring is frozen.
Nimbus Tech’s company page is full of optimistic product posts but their open roles show many withdrawals. I’m not sure if this is a freeze or a timing issue. What’s the likeliest read and how should I frame questions on the call to avoid embarrassment?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI routinely scan company pages for hiring signals but I end up chasing noise and miss true…+
I waste time checking company pages for useful signals.
I routinely scan company pages for hiring signals but I end up chasing noise and miss true opportunities. Which routine causes the waste and what specific habit change will make my research faster and more accurate?
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.