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Save candidate profiles

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 taskSave potential hires for the sales development rep role into the candidate pool labeled Q3…+
Save potential hires for the sales development rep role into the candidate pool labeled Q3 SDRs. For each profile, add a one-line note with why they might fit — outbound experience, quota attainment, or industry familiarity — and tag Nadia in Talent to review. Do this for the next 25 profiles that match our saved search and confirm the pool has at least 40 profiles by Monday.
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 bulk-save profiles to the Q3 SDR pool, make it easy for reviewers to decide: show the…+
Before I bulk-save profiles to the Q3 SDR pool, make it easy for reviewers to decide: show the three strongest signals at the top of each saved profile (outbound experience, quota history, industry), add a confidence score from 1–5, and surface the contact availability so Talent can prioritize outreach.
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’ve been saving profiles into the Q3 SDR candidate pool but when Nadia reviews them half are…+
My saved pool has many low-quality profiles.
I’ve been saving profiles into the Q3 SDR candidate pool but when Nadia reviews them half are unusable — misaligned experience or outdated contact info. I’m worried the pool will be irrelevant by Monday. I can’t tell which saved-search filters I should tighten without losing volume. What immediate filter changes or note conventions will make the pool ready for outreach?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternAcross multiple quarters my saved candidate pools grow quickly but much of the volume is low…+
Candidate pools fill with mismatches and stale contacts.
Across multiple quarters my saved candidate pools grow quickly but much of the volume is low quality or stale, wasting Talent’s time. I suspect my saving criteria and note practices are inconsistent. What habit or small checklist should I adopt when saving profiles so pools are consistently actionable and reduce downstream screening time?
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.