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Follow industry hashtags

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 taskTrack the five industry hashtags I follow this month. Each morning scan the top 30 posts under…+
Track the five industry hashtags I follow this month. Each morning scan the top 30 posts under #saasgrowth #productops #designops #talentacquisition #b2bsales, like and save three useful posts, and compile three takeaways for my morning message: notable trends, one potential contact to follow, and one idea I can comment on to increase visibility.
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 start following new hashtags, make it easy to decide which ones matter: surface the…+
Before I start following new hashtags, make it easy to decide which ones matter: surface the expected follower size, recent post velocity, and one example of a post that attracted thoughtful comments. Flag any hashtag dominated by conference promotion or recruiters so I don’t waste time.
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 started following #growthhacks yesterday because a peer recommended it, but the feed is 80%…+
I followed a new hashtag and saw mostly low-value posts
I started following #growthhacks yesterday because a peer recommended it, but the feed is 80% recycled tips and blatant product ads. I can’t tell if it’s a bad tag or if I tuned the algorithm wrong. Should I unfollow now, add a handful of thought leaders to reshape the feed, or keep watching for a few days? What’s the fastest test to know if this hashtag is worth keeping?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternOver months I keep adding hashtags hoping for fresh content, but my feed fragments and I spend…+
Wasting time on noisy hashtags
Over months I keep adding hashtags hoping for fresh content, but my feed fragments and I spend hours skimming low-value posts. Where am I losing time in my discovery routine, what one habit would reclaim those hours, and how should I prune or consolidate my followed hashtags to surface higher-signal content consistently?
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.