40 ChatGPT Prompts to Rewrite Your LinkedIn
About sections, headlines by role, work experience that reads as proof, and featured-section copy. Built for mid-senior employed professionals who want to be found — not job seekers shouting for attention.
In short: This page contains 40 copy-paste ready prompts, organized into 8 categories with a description and pro tip for each. The first 5 prompts are free instantly, no signup needed. Drafted with AI writing assistance and checked against our editorial policy.
About Section Master Rewrite
1 promptSenior About Section: The 3-Beat Rewrite
1/40✨ What it does
ChatGPT rewrites your LinkedIn About as three beats in a senior employed voice at [role + company], not an open-to-work pitch. You paste your six bullets, edit the opener until it sounds like you, and replace the live section.
Rewrite my LinkedIn About section in the voice of a senior, employed professional — not a job seeker. My current role: [role + company]. My background in 6 bullets: [paste 6 brief bullets — roles, scope, the kind of problems you solve]. Structure the About section in 3 beats: (1) The 1-sentence opener that names WHAT I do and WHO benefits (no "passionate about" or "results-driven" — those are job-seeker tells), (2) A 3-4 sentence middle that names the 2-3 specific kinds of problems I have solved, with the SCALE attached (team size, business stage, dollar impact), (3) A 2-sentence close that signals what I am currently working on or curious about, and how to reach me. Total: 6-8 sentences max. Tone: confident, specific, never desperate. Senior About sections sound like they belong to someone who has options.
Pro tip: Strip out every word a job seeker would use: "passionate", "driven", "results-oriented", "team player", "open to opportunities". Senior About sections describe what you DO, not what you ARE.
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Headline Variants by Role
6 promptsSenior Product Manager: 6 Headline Variants
2/40✨ What it does
ChatGPT writes six Senior PM headlines under 220 characters for [company], each in a different style from outcomes to community. You pick the one that matches how you want to be found, then paste it into your headline.
I am a Senior / Group / Principal Product Manager at [company]. My focus area is [B2B SaaS / consumer / fintech / infra / etc.]. My 1-2 strongest signals are [e.g., shipped X feature that drove $YM ARR, led 0-to-1 launch in regulated industry, ran growth at [recognizable company]]. Generate 6 distinct LinkedIn headline variants, each under 220 characters: (1) An outcomes-first headline that leads with what I have shipped, (2) A specialist headline that owns a specific niche (e.g., "Product Manager building B2B retention loops"), (3) A scope-first headline that signals scale ("PM leading [N] eng teams at [stage] B2B SaaS"), (4) A point-of-view headline that signals what I believe ("Product Manager — bias toward small, opinionated software"), (5) An ex-credential headline if I have a strong prior brand ("PM at [current] — formerly [Stripe/Figma/etc.]"), (6) A community / external-signal headline that hints at writing, speaking, or open source. Rank them by which is best for inbound from VCs / recruiters / founders.
Pro tip: For senior roles, the headline that names your specific niche tends to outperform the generic "Senior PM" — niches attract the right inbound and repel the wrong.
Senior Engineer / Staff+: 6 Headline Variants
3/40✨ What it does
ChatGPT writes six Staff-plus engineer headlines for [company] that span scope, depth, outcome, point of view, credential, and community. You choose one, trim it to fit, and update your headline.
I am a Senior / Staff / Principal Engineer at [company]. Focus area: [distributed systems / ML infra / frontend platform / etc.]. Strongest signals: [e.g., owned the migration of X, wrote the framework Y uses, scaled service to Z QPS, prior at [recognizable company]]. Generate 6 LinkedIn headline variants under 220 characters: (1) Scope-first ("Staff Engineer building [specific system] at [company]"), (2) Specialist depth ("Distributed systems — building the [thing] layer at [company]"), (3) Outcome-first ("Cut [system] latency 4x and rebuilt the [layer] — Staff Eng @ [company]"), (4) Point-of-view ("Staff Engineer. Bias toward boring tech and small interfaces."), (5) Ex-credential ("Staff Eng @ [current] — previously [FAANG / Stripe / etc.]"), (6) Community-signal ("Staff Eng — author of [OSS] | writes about [topic] at [blog]"). Rank by which is best for inbound from staff+ recruiters and tech founders.
Pro tip: The "boring tech, small interfaces" style point-of-view headline is the strongest signal for staff+ — it repels juniors and attracts the right peer signal.
Founder / Operator: 6 Headline Variants
4/40✨ What it does
ChatGPT writes six founder and operator headlines for [company] that signal stage, traction, and a bit of personality. You pick the variant that matches how you want investors and hires to read you, then paste it in.
I am a founder / operator running [company] in [space]. My company is [stage — e.g., bootstrapped, Series A, $XM ARR]. My strongest external signals: [e.g., prior exit, well-known angel investors, recognizable customer logos, podcast appearances]. Generate 6 LinkedIn headline variants under 220 characters: (1) Direct ("Founder, [company] — [what we do in 8 words]"), (2) Outcome-anchored ("Building [company] — $XM ARR / [N] customers"), (3) Customer-anchored ("Building [company] — used by [recognizable customer types]"), (4) Mission-anchored ("Building [company] — making [X] easier for [Y]"), (5) Stage-honest ("Building [company] — early, profitable, hiring"), (6) Community / writing-anchored ("Founder @ [company] | writes about [topic]"). Rank by which is best for inbound from prospective hires, investors, and customers.
Pro tip: Bootstrapped founders should signal it directly. VC-backed founders should signal customer logos. Both audiences read founder headlines for stage signals first.
Senior Designer: 6 Headline Variants
5/40✨ What it does
ChatGPT writes six senior designer headlines for [company], from specialist to outcome to point of view. You pick the one that names your real craft, then drop it onto your profile.
I am a Senior / Staff / Principal Designer at [company]. My specialty is [product design / brand design / motion / design systems / 0-to-1]. Strongest signals: [e.g., shipped X product, led design system for Y, won [award], prior at [recognizable company]]. Generate 6 LinkedIn headline variants under 220 characters: (1) Specialist ("Product Designer at [company] — focused on [specific surface like onboarding, design systems, AI interfaces]"), (2) Scope-first ("Senior Designer leading [N] product surfaces at [company]"), (3) Outcome-first ("Designed [recognizable product/feature] at [company]"), (4) Point-of-view ("Designer — bias toward shipping over polishing"), (5) Ex-credential ("Designer @ [current] — formerly [Apple/Figma/Linear/etc.]"), (6) Community ("Designer | speaker | writes about [topic] at [blog]"). Rank by which is best for inbound from senior design recruiters and founders.
Pro tip: The strongest senior designer headlines name a specific surface ("onboarding", "design systems", "AI interfaces") — generic "Product Designer" reads as mid-level.
Senior Marketing / Growth: 6 Headline Variants
6/40✨ What it does
ChatGPT writes six senior marketing or growth headlines for [company] across channel, stage, outcome, point of view, credential, and community. You choose the angle that matches your next role, then update the headline.
I am a Senior / Director / VP of Marketing or Growth at [company]. My focus: [content / paid / lifecycle / brand / community / PLG growth]. Strongest signals: [e.g., scaled [channel] to $XM ARR, led marketing at [recognizable brand], built the playbook for [motion]]. Generate 6 LinkedIn headline variants under 220 characters: (1) Channel-specialist ("Head of Lifecycle at [company] — built the email engine driving $XM"), (2) Stage-specialist ("Marketing leader — built 0-to-$10M motion at [company]"), (3) Outcome-first ("Built [recognizable campaign / motion] at [company]"), (4) Point-of-view ("Marketing leader — bias toward owned channels over paid"), (5) Ex-credential ("Head of Growth @ [current] — formerly [Hubspot/Stripe/etc.]"), (6) Community ("Marketing leader | writes [newsletter] | speaks at [conferences]"). Rank by inbound quality for senior marketing recruiters.
Pro tip: Stage-specialist headlines ("built 0-to-$10M motion at [company]") attract the most inbound at founder + Series A/B companies, which is where senior marketing leaders are most in demand.
Senior Sales / Revenue: 6 Headline Variants
7/40✨ What it does
ChatGPT writes six senior sales headlines for [company] from outcome-anchored to segment specialist to community. You pick the one that names [SMB / mid-market / enterprise / strategic] without sounding like a quota dump, then paste it in.
I am a Senior / Strategic / Enterprise AE or Director of Sales at [company]. My segment: [SMB / mid-market / enterprise / strategic]. Strongest signals: [e.g., consistently top-quartile, closed $XM in [year], expert in [specific motion like land-and-expand], built the [team / playbook]]. Generate 6 LinkedIn headline variants under 220 characters: (1) Outcome-anchored ("Closed $XM in [year] — Enterprise AE at [company]"), (2) Segment-specialist ("Strategic AE selling to [vertical] at [company]"), (3) Scope-first ("Director of Sales leading [N] AEs at [company]"), (4) Point-of-view ("Sales leader — bias toward MEDDIC + small reps with deep expertise"), (5) Ex-credential ("AE @ [current] — formerly [Salesforce/Stripe/etc.]"), (6) Community ("Sales leader | writes about enterprise selling | mentors AEs"). Rank by which best attracts inbound from senior sales recruiters.
Pro tip: Senior sales recruiters look for outcome numbers FIRST. Headlines that lead with "$XM closed in [year]" outperform every other variant for inbound.
Work Experience Bullet Rewrites
10 promptsTurn Responsibilities Into Proof
8/40✨ What it does
ChatGPT turns each of your [paste your bullets] into proof: what you shipped, the scale, and the measurable outcome. You swap in real numbers, cut anything you cannot defend, and paste the new list onto the role.
Rewrite my LinkedIn work experience bullets to read as PROOF, not duties. My role: [title + company]. My current bullets: [paste your bullets]. For each bullet, transform it using this structure: [What I shipped / drove / changed] + [the scale or scope — team size, dollars, users] + [the measurable outcome — % change, $ change, time saved] + [the second-order effect — what it enabled, what shifted in the org]. Where I don't have a number, suggest a realistic placeholder I can verify, marked with [VERIFY]. End each bullet with proof, not adjective. The goal: a recruiter or peer reading this in 8 seconds should understand the SCALE and IMPACT of what I did.
Pro tip: Always anchor on the second-order effect. "Shipped X" is a duty. "Shipped X, which enabled the team to deprecate the legacy system" is proof.
Bullets That Pass the 8-Second Scan
9/40✨ What it does
ChatGPT rewrites your bullets so the first five words carry the strongest signal and every line has a number. You check the scan on your phone, then paste the keepers onto [title + company].
Rewrite my LinkedIn work experience bullets so they pass the 8-second scan test. My role: [title + company]. My bullets: [paste]. Rules: (1) The first 5 words must contain the strongest signal in the bullet — verb + scale + impact, (2) Every bullet must contain at least 1 number (team size, dollars, % shift, headcount, users — anything quantifiable), (3) Cut every adjective ("strategic", "innovative", "results-driven") — they add no signal, (4) No bullet over 25 words. If it does not fit, the bullet is doing 2 things and needs to be split, (5) Order bullets within a role by impact, descending — strongest bullet first. Show me the before / after side by side so I can see what changed.
Pro tip: Cut every adjective in the first 5 words. Adjectives are signals of weakness; specific verbs + nouns are signals of strength.
Bullet Rewrite: From "Led" to Specific Verbs
10/40✨ What it does
ChatGPT replaces lazy verbs like led and managed with specific ones that name what you actually did. You read each line out loud, keep the verbs that are true, and update the role.
My LinkedIn bullets are over-indexed on "led" and "managed" — they hide the actual work I did. Here are my current bullets: [paste]. Rewrite each one to replace "led" or "managed" with a more specific verb that names what I actually did: shipped, scoped, prioritized, killed, negotiated, recruited, deprecated, restructured, expanded, contracted, hired, fired, mentored, escalated, surfaced, defended. Each bullet should signal a specific category of action and the OUTCOME of that action. Show me before / after with the swap highlighted. If the original bullet does not have a clear action verb behind "led", flag it as too vague to keep.
Pro tip: "Led" and "managed" are tells of senior candidates who have not refined their narrative. Specific verbs ("deprecated", "negotiated", "killed") signal calibration and ownership.
Bullet Rewrite: Quantify Soft Outcomes
11/40✨ What it does
ChatGPT attaches a defensible number to soft outcomes like morale, collaboration, or satisfaction. You confirm the proxy is real, drop any line you cannot back up, and paste the rest.
I have LinkedIn bullets where the impact is real but the metric is soft (e.g., "improved team morale", "increased collaboration", "improved customer satisfaction"). Here are my current bullets: [paste]. For each, rewrite to attach a quantifiable proxy: morale → eNPS shift, retention rate, voluntary attrition; collaboration → cycle time, # cross-team launches, # escalations; customer satisfaction → NPS shift, churn rate, CSAT delta, support volume. Where I don't have a real number, suggest a credible proxy and mark it [VERIFY] so I can check before posting. The goal: every "soft" outcome becomes a defensible metric.
Pro tip: eNPS, voluntary attrition, and cycle time are the most defensible proxies for "soft" management wins. Use them instead of vague descriptors.
Bullet Rewrite for a Senior Manager → Director Shift
12/40✨ What it does
ChatGPT rewrites your manager bullets so they read as director-level scope: org context, the plan you set, and the result. You add the real team sizes, then replace the live bullets before you apply.
I am repositioning my LinkedIn for a Senior Manager → Director-level move. My current bullets read as a hands-on manager; I need them to signal strategic scope. Current bullets: [paste]. Rewrite each one to: (1) Add the org-wide context (how many teams, how many ICs, what fraction of the broader org), (2) Surface the planning or strategic call I made (not just the execution), (3) Reframe team outcomes as business outcomes — translate engineering or product metrics into revenue, retention, or strategic position language, (4) Cut any bullet that is genuinely IC-level work and is now beneath the level I am targeting. Mark cuts with [REMOVE - too IC]. Goal: every bullet must signal director-level scope and judgment.
Pro tip: When repositioning upward, the cuts matter as much as the rewrites. Bullets that signal hands-on IC work HURT a director-level positioning — even if they are recent and real.
Bullet Rewrite for Cross-Industry Move
13/40✨ What it does
ChatGPT rewrites your bullets from [current industry] into plain business language that lands in [target industry]. You check that no leftover jargon remains, then paste the new list onto the role.
I am moving from [current industry] to [target industry] on LinkedIn. My bullets currently use industry-specific jargon and metrics. Here are my bullets: [paste]. For each, rewrite to (1) Strip out [current industry] jargon and replace with universal business language (or [target industry] equivalents where they exist), (2) Translate metrics into ones that travel — convert internal KPIs to standard finance/operations metrics (revenue, margin, retention, headcount, capital efficiency), (3) Preserve the SCALE but generalize the CONTEXT — keep "$XM" but make "$XM in [generic outcome]" rather than "$XM in [vertical-specific outcome]", (4) Add 1 bullet per role that signals transferability — what KIND of problem I solved, not what KIND of company I solved it for.
Pro tip: Translate metrics, preserve scale. The same accomplishment lands differently when the dollar amount is preserved but the vertical context is generalized.
Cut a Bullet List in Half
14/40✨ What it does
ChatGPT ranks your bloated bullet list, merges the repeats, and cuts it to the four strongest lines. You keep the ranking honest, then replace the long list with the short one.
My LinkedIn role has 7-8 bullets and reads as bloated. Here are the current bullets: [paste]. Help me cut to 4 bullets that signal the most: (1) Rank all current bullets by signal strength (scale + outcome + uniqueness), (2) Identify which 2 bullets are essentially the same accomplishment from different angles, and merge them into 1, (3) Cut any bullet that is hygiene work (regular duties, expected at this level) — those are not differentiating, (4) Keep at most 4 bullets total, in descending order of impact. Show me the cuts with a 1-line reason for each removal. Goal: a recruiter reading 4 strong bullets remembers more than reading 8 mediocre ones.
Pro tip: Recruiters remember 4 strong bullets and forget 8 weak ones. The cut is more valuable than the addition.
Add Second-Order Impact to Every Bullet
15/40✨ What it does
ChatGPT adds a second-order effect to each bullet: what got faster, cheaper, hired, or de-risked because of the work. You keep only the downstream effects you can point to, then paste the new lines.
My LinkedIn bullets describe what I did but not what it enabled downstream. Bullets: [paste]. For each, add the second-order effect — what shipped because of this work, what got faster, what got deprecated, what got acquired, what got hired into, what got de-risked. Format: [Primary action + outcome] — which enabled [second-order effect with its own scale]. Where I don't know the second-order effect, suggest 2-3 plausible candidates I can verify. Goal: every bullet signals that I think about leverage, not just execution.
Pro tip: Second-order effects (what your work enabled) often have BIGGER numbers than your direct outcome. Surfacing them is the senior signal.
Rewrite a Bullet About a Failed Project
16/40✨ What it does
ChatGPT rewrites a failed or pivoted project so the bullet shows the work that still has value, plus the judgment you applied. You fill in [paste] with the real ending, then decide whether the line stays on the profile.
I have a project on my LinkedIn that ended in failure or pivot but the work I did was meaningful. Project: [briefly describe — what we tried, what we learned, why it ended]. My current bullet: [paste]. Help me rewrite it so the bullet signals (1) The work I shipped that has standalone value (the infra, the research, the customer learning), (2) The decision I made or argued for that turned out to be right even though the project failed, (3) What the company adopted afterward as a result of what I built — show the lasting impact. Frame as a learning artifact, not a wound. Keep under 25 words. Senior profiles benefit from honest failure framing; junior ones avoid it.
Pro tip: Acknowledging a failed project on LinkedIn (well) is a senior trust signal. Most candidates hide them; senior candidates surface the lessons.
Bullet Rewrite Across 3 Tones
17/40✨ What it does
ChatGPT rewrites one bullet in three tones: numbers-forward, story-forward, and peer-forward. You pick the tone for the audience you want next, then paste that single version.
I want to test which tone works best for my LinkedIn audience. Here is 1 bullet I want to optimize: [paste your bullet, including current context]. Rewrite it in 3 distinct tones: (1) Numbers-forward — lead with the metric, no adjectives, sounds like a quarterly review, (2) Story-forward — lead with the problem context, sound like a peer telling a war story, (3) Point-of-view forward — lead with the principle or belief that drove the work, sound like an essay sentence. For each, give the bullet plus a 1-sentence note on what audience the tone is best for (recruiters / peers / founders / customers). Goal: pick the tone that matches my next career move.
Pro tip: Different audiences read LinkedIn differently. Founders respond to point-of-view tone; recruiters respond to numbers-forward; peers respond to story-forward. Match tone to your next move.
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Project Experience Reformatters
6 promptsReformat a Project as a Proof Artifact
18/40✨ What it does
ChatGPT reformats a project as a proof write-up: what it is, who it was for, the decision, the outcome, and a link. You add the real URL, trim the fluff, and pin it under Projects or Featured.
I have a notable project I want to highlight on LinkedIn — currently it lives in the "Projects" or "Featured" section. Project: [briefly describe — what, when, with whom]. Current write-up: [paste]. Reformat it as a proof artifact with this structure: (1) 1-sentence opener naming WHAT it is and WHO it was for (no "passionate about" tells), (2) 2-3 sentences of context — the problem, the stakes, the constraint, (3) The 1-2 specific decisions I made that are differentiating, (4) The OUTCOME with a number — even if approximate, even if I have to mark [VERIFY], (5) The link or artifact (if available) — repo, case study, demo, talk. Under 100 words. The goal: a peer scanning the section in 15 seconds understands what makes this project worth reading more about.
Pro tip: The "decision I made that is differentiating" sentence is the senior signal. Without it, projects read as generic case studies; with it, they read as your unique judgment.
Project Section: Open-Source Contribution
19/40✨ What it does
ChatGPT writes a 100-word open-source entry that names what you contributed and why it mattered, without humblebragging. You add the repo link, then paste it onto Projects.
I have an open-source contribution I want to surface on LinkedIn. The project: [name + brief description]. My contribution: [briefly describe — what I built / fixed / proposed]. Help me write a 100-word entry that signals seniority: (1) The 1-sentence what + why — what I contributed and what problem it solved, (2) 2-3 sentences of technical context — why this approach over the obvious alternatives, what trade-off I made, (3) The signal — # of contributors, # of users / downloads / stars, % the project has grown, anything that signals scale, (4) The link — repo, PR, or related blog post. Tone: confident, specific, no humblebrag. Senior contributors describe what they built; juniors describe what was hard about it.
Pro tip: Senior OSS write-ups describe the DECISION you made (and what alternative you rejected). Junior write-ups describe the EFFORT you put in.
Project Section: Side Project With Business Outcome
20/40✨ What it does
ChatGPT writes a 100-word side-project entry with what it does, why you built it, and the real traction. You drop in [name + 1 sentence] and the numbers, then pin it.
I have a side project (built outside my day job) with real traction. Project: [name + 1 sentence]. Traction: [what — users, MRR, downloads, customers, recognition]. Help me write a 100-word LinkedIn entry: (1) 1-sentence what — what it does and who it serves, (2) Why I built it — the specific itch or gap I noticed, (3) The traction with numbers — exact numbers, not adjectives, (4) The current state — actively maintained? Sunset? Sold? Looking for co-builder? (5) The link to the product or write-up. Goal: signal that I ship outside the day job, that I think in customer outcomes, and that I have public taste. Side projects are a senior differentiator IF they show outcome — not effort.
Pro tip: Side projects without numbers are noise on a senior LinkedIn. The signal is the traction, not the existence. If the traction is small, lead with the LEARNING instead.
Project Section: Speaking / Talks / Workshops
21/40✨ What it does
ChatGPT consolidates your talks into one Featured entry with a throughline and a few specific appearances. You paste [list with title, venue, year, topic], then add links to the recordings.
I have spoken at [conferences / podcasts / internal events] in the last 2 years. Talks: [list with title, venue, year, topic]. Help me write a LinkedIn Project / Featured section entry that consolidates them. Structure: (1) 1-sentence opener describing the throughline — what topic I am known for speaking on, (2) 2-3 specific talks with their venues and 1-sentence on what each was about, (3) Total reach if I can estimate it (attendance, views, downloads), (4) The link to the most recent talk or a curated playlist. Tone: confident, not promotional. Goal: signal that I have a thesis and that audiences respond to it. Speaking matters on senior LinkedIn for inbound and brand.
Pro tip: Always name the throughline. "Talks on [X]" reads as a person with a point of view; a random list reads as resume padding.
Project Section: Writing / Newsletter / Blog
22/40✨ What it does
ChatGPT writes a Featured entry for your newsletter or blog: what you write, who reads it, and the pieces that traveled. You add the subscribe link, then pin the entry.
I write a newsletter, blog, or column. Publication: [name + brief description]. Audience: [size + composition — e.g., 3K subscribers, mostly senior PMs at B2B SaaS]. Cadence: [weekly / biweekly / monthly]. Help me write a Featured-section entry: (1) 1-sentence what — what I write about and who reads it, (2) The 2-3 most recent pieces with 1-sentence on each, (3) The signal — subscriber count, growth, notable readers if I am comfortable naming them, (4) The link to subscribe. Tone: declarative, not pleading. Goal: signal that I have a body of public work and a defined audience. Writing is one of the highest-leverage senior LinkedIn signals.
Pro tip: Subscriber counts under 1K are still worth surfacing IF the audience is right (e.g., 800 senior PMs is signal-rich). Quality of audience > raw count for senior LinkedIn.
Project Section: A Hire You Made That Worked
23/40✨ What it does
ChatGPT writes a 60-word Featured note about a hire you made, framed as judgment rather than a brag. You confirm they would be glad to be named, then post it or keep it private.
I want to surface a notable hire I made — not as a brag, but as a signal of judgment. The hire: [role + who they were when I hired them + what they have done since]. Help me write a 60-word Project / Featured section entry that signals this: (1) 1 sentence on the role I hired for and the constraint (early-stage? Rare skillset? Tough market?), (2) 1 sentence on the candidate — who they were when I hired them, especially if I bet on signal others missed, (3) 1 sentence on what they have shipped since. Tone: about THEIR work, not mine. Goal: signal hiring judgment without making it about me. Senior hiring stories on LinkedIn pay forward to your reputation as a builder of teams.
Pro tip: Make the entry about THEM, not you. Senior hiring stories signal your judgment via the success of others, not via your own self-promotion.
Recommendation Request Prompts
4 promptsRecommendation Request to a Former Manager
24/40✨ What it does
ChatGPT drafts a 150-word recommendation request to a former manager that recalls a specific memory and scaffolds what to write. You send it to [name + the role they had when they managed me], then follow up once if it sits.
I want to ask a former manager to write me a LinkedIn recommendation. Former manager: [name + the role they had when they managed me]. We worked together for [length]. The 1-2 things they would credibly speak to about my work: [list]. Write me a 150-word request message: (1) Genuine, warm opener with 1 specific memory from our time together (not generic flattery), (2) The ask — explicitly for a LinkedIn recommendation, with the WHY (career move? Visibility? Brand building?), (3) The scaffolding — offer 2-3 themes they could speak to and 1 specific story or outcome they could anchor on (this makes their job 10x easier), (4) The make-it-easy — offer to write a draft if helpful, give a soft timeline, signal no pressure if they cannot, (5) Genuine close. Goal: a recommendation that signals THEIR experience of working with me, not a generic blurb.
Pro tip: Always offer to write a draft. Most managers are overwhelmed; offering a draft turns a 30-minute task into a 5-minute review. Reply rate triples.
Recommendation Request to a Peer or Cross-Functional Partner
25/40✨ What it does
ChatGPT drafts a 150-word peer recommendation request anchored on one dimension like judgment or collaboration. You send it after you name [specific work or project], then offer to write one back.
I want to ask a peer / cross-functional partner to write me a LinkedIn recommendation. Partner: [name + their role + how we worked together]. We collaborated on [specific work or project]. The angle they could best speak to: [collaboration, judgment, technical depth, customer empathy, communication]. Write me a 150-word request: (1) Open by acknowledging our collaboration with 1 specific moment, (2) The ask, with the WHY (career move, brand, visibility), (3) Scaffold — name the SPECIFIC angle I am asking them to speak to (peer recommendations are most credible when they speak to a specific dimension, not generally), (4) Offer a draft, give a soft timeline, signal no pressure, (5) Genuine close. Peer recommendations are 2x more impactful than manager ones on LinkedIn — make the ask great.
Pro tip: Peer recommendations beat manager recommendations on LinkedIn — peers are seen as harder graders. The trick is asking them to speak to ONE dimension specifically.
Recommendation Request to a Customer or External Partner
26/40✨ What it does
ChatGPT drafts a 150-word request for a customer or client recommendation that names the outcome you drove together. You personalize the opener, then send it while the work is still fresh.
I want to ask a customer / external partner / client to write me a LinkedIn recommendation. Partner: [name + their role + their company + how we worked together]. The outcome we drove together: [briefly describe]. Write me a 150-word request: (1) Open with genuine appreciation for the working relationship (1 specific moment), (2) The ask — explicitly for a LinkedIn recommendation, with the WHY (career move, brand), (3) Scaffold — name 1-2 specific things THEY experienced (the responsiveness, the strategic input, the way I handled the tough conversation), (4) Acknowledge that they are busy and offer a draft they can edit OR a 3-sentence outline they can build from, (5) Genuine close. Customer recommendations are gold on LinkedIn — they are the most credible signal because they have no incentive to flatter.
Pro tip: Customer recommendations beat both manager and peer recommendations for senior LinkedIn — they signal that someone with no career incentive vouched for your work.
Recommendation Request With a Specific Angle
27/40✨ What it does
ChatGPT drafts a 150-word request that asks [name + role] to speak to one specific strength you need for your next move. You name that strength in your own words, then send the note.
I want to ask [name + role] for a LinkedIn recommendation that signals one specific thing: [name the thing — e.g., strategic thinking, hiring judgment, technical depth, leadership in crisis, customer empathy]. Why I want this specific angle: [the next career step requires signaling this dimension]. Write me a 150-word request: (1) Genuine opener with a specific memory that anchors on the angle, (2) The ask, with the WHY (specific career goal, not generic), (3) Scaffold the angle explicitly — "if you had to describe ONE thing about my work that you saw firsthand, would you be willing to anchor on [the angle]?", (4) Offer a draft outline that hits the angle, (5) Genuine close, with offer to reciprocate. Targeted recommendations beat generic ones 5:1 on LinkedIn.
Pro tip: Senior career moves require signaling specific dimensions. Asking for a recommendation that signals the SPECIFIC thing your next role demands is far more valuable than a generic glowing blurb.
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Featured Section Copy
5 promptsWhat to Pin to Featured: 5-Item Audit
28/40✨ What it does
ChatGPT audits your Featured section and tells you what to pin, what to drop, and what is missing for your current trajectory. You unpin the stale items, then add the one new piece it ranked highest.
I have a LinkedIn Featured section I have not updated in [time]. Help me audit it: (1) The 5 things on senior LinkedIn that are HIGHEST signal — a recent case study or write-up, a talk or podcast appearance, an article I wrote that performed well, a product I built or shipped, a public review or customer-facing piece, (2) Walk through what I currently have featured and rank each by signal strength, (3) Identify what is missing — what would I add to round out the section, (4) Decide what to pin in what order — the top 3 are seen most, so the order matters, (5) Identify what to UNPIN — old content that no longer signals my current direction. Goal: a Featured section that signals my current trajectory in 4 items.
Pro tip: Most senior LinkedIn profiles have outdated Featured sections. The signal is more about WHAT YOU LEAVE THERE than what you add — old, off-direction content actively hurts you.
Featured Section Copy: Case Study Pin
29/40✨ What it does
ChatGPT writes a short Featured caption and a 120-word intro comment for a case study pin. You paste both onto the pin, then check the caption still makes a peer want to click.
I want to pin a case study or write-up to my LinkedIn Featured section. The work: [briefly describe — what I shipped, when, the outcome]. Help me write the Featured caption (under 30 words) and the introductory comment (under 120 words): (1) The caption — the headline that makes a recruiter or peer click. Lead with the most surprising number or the most unexpected angle, (2) The intro comment — context in 3 sentences, the specific decision I made that is interesting, and the link/CTA. Tone: confident, specific, no hype. The goal: a peer reading the caption gets the substance in 5 seconds and clicks because they want the details.
Pro tip: Lead with the most surprising number. Senior peers click on captions that signal something they did not expect — not captions that sell.
Featured Section Copy: Talk or Podcast Pin
30/40✨ What it does
ChatGPT writes a caption that states the thesis of your talk, plus an intro comment that says who it is for. You attach [title + venue + topic], then pin the recording.
I want to pin a talk / podcast appearance to my LinkedIn Featured section. The talk: [title + venue + topic]. Help me write the caption (under 30 words) and intro comment (under 120 words): (1) Caption — the thesis of the talk in 1 line, not the title. The thesis is what makes someone click, (2) Intro comment — who the audience was, the specific question or angle I addressed, the 1 surprising thing I argued for, the link. Tone: declarative, not promotional. Goal: a peer scanning Featured understands what I have a point of view on, not just that I have spoken in public.
Pro tip: The thesis matters more than the venue. Captions that lead with "I argued that [contrarian or specific point]" outperform "Spoke at [conference]" 5:1.
Featured Section Copy: Writing Sample Pin
31/40✨ What it does
ChatGPT writes a caption and intro comment for a writing sample that lead with the most interesting sentence, not the title. You pin the piece, then edit the comment so it sounds like you.
I want to pin a writing sample (essay, newsletter post, blog) to my Featured section. The piece: [title + publication + brief topic]. Why it matters: [what it argues / what audience it found]. Help me write the caption (under 30 words) and intro comment (under 120 words): (1) Caption — the single most interesting sentence from the essay, lifted directly, (2) Intro comment — what made me write it, who reacted strongly, what I have changed in my thinking since, the link. Tone: like a peer recommending the piece to another peer. Goal: senior peers click because the caption signals taste and a real point of view, not because they want to be supportive.
Pro tip: Lift the single best sentence directly from your piece for the caption. Your own writing usually has the strongest hook — better than anything you would write from scratch.
Featured Section Copy: Side Project Pin
32/40✨ What it does
ChatGPT writes a builder-to-builder caption and intro for a side project, with the surprising constraint and the real traction. You add the link, then pin it.
I want to pin a side project to my LinkedIn Featured section. The project: [name + 1-sentence what + traction]. Help me write the caption (under 30 words) and intro comment (under 120 words): (1) Caption — the most surprising thing about the project (the speed, the constraint, the audience, the technical choice), (2) Intro comment — why I built it, what I learned that is portable, the current traction with real numbers, the link. Tone: builder talking to other builders. Goal: senior peers click because they want to study the project, not because they want to support me.
Pro tip: Lead with the surprising constraint or speed ("built in 3 weeks", "shipped solo", "used X non-obvious tech"). Senior builders read for constraint, not for outcome.
Connection Message Templates
4 promptsCold Outreach: Asking for a Conversation, Not a Job
33/40✨ What it does
ChatGPT writes a cold LinkedIn connection note under 300 characters to [name + role + company] that asks for a conversation, not a job. You send it, then follow with one specific question if they accept.
I want to send a cold LinkedIn connection request to [name + role + company]. Reason I want to connect: [specific — saw their talk, read their writing, admire their work in [area], thinking about a career move in their space]. Write me a connection request under 300 characters (LinkedIn limit): (1) 1 sentence that signals I have done real research — reference something specific they have shipped, said, or written, (2) 1 sentence that names what I do or am known for — so they understand why I am reaching out from a position of peer, not student, (3) 1 sentence that names the SPECIFIC reason I want to connect — not "I would love to chat" but "I am thinking about [specific topic] and would value 15 minutes of your thinking." (4) Close with a soft signal of no-pressure. Goal: reply rate of 30%+, not 5%.
Pro tip: Senior cold outreach reply rates depend on whether the message signals YOU did the research. Generic "I love your work" messages get archived; specific references get replies.
Mutual Connection Introduction Request
34/40✨ What it does
ChatGPT writes a 150-word intro request to [name of mutual connection], including a blurb they can forward to [name + role + company]. You send the request, then let them copy-paste the blurb as-is.
I want to ask [name of mutual connection] to introduce me to [name + role + company]. Reason for the intro: [specific — exploring a role, asking for advice, looking for a customer, sourcing a hire]. Write me a 150-word request to the mutual connection: (1) Genuine opener with a specific reference to our last conversation or interaction, (2) The ask — explicitly framed as a double-opt-in intro (their preferred method), (3) The 3-sentence forwardable blurb the mutual can paste — what I do, why I want to talk to this specific person, what is in it for them (briefly), (4) An out — "no worries if it is not the right ask right now", (5) Genuine close. Goal: the mutual can forward without thinking, and the recipient can decide in 30 seconds.
Pro tip: Always give the mutual a forwardable blurb they can paste with one click. The reason most intros don't happen is the friction of writing the email — remove it.
Re-engagement Message to a Dormant Connection
35/40✨ What it does
ChatGPT writes a short re-engagement note to a dormant connection that names the gap and a specific reason to talk. You send it to [name + how we know each other + how long since we last talked], then leave the next step easy.
I want to reach out to a former colleague / dormant connection on LinkedIn. Connection: [name + how we know each other + how long since we last talked]. Reason for re-engaging: [specific — career move, want their thinking on a problem, exploring a partnership, just genuine catch-up]. Write me a 200-character message: (1) Acknowledge the gap warmly, no fake "thinking of you out of the blue" — be honest about why now, (2) 1 specific reference to our last interaction or working relationship, (3) The specific ask or reason — not vague "let me know how you are" but "I am thinking about X and would value your read", (4) Soft signal of no pressure, (5) Genuine close. Goal: reply rate above 50% for dormant senior connections.
Pro tip: Dormant connections respond to honesty about the gap. "Hope you have been well" is a tell of someone who has not thought about why they are reaching out — make it specific.
Outreach After Their Job Change
36/40✨ What it does
ChatGPT writes a 200-character congrats note after a job change that opens a door without asking for anything. You send it the week they start, then wait for them to reply.
A connection I respect just changed jobs (per LinkedIn notification). New role: [role + new company]. My relationship to them: [former colleague / peer in industry / known each other socially / cold connection but I have followed their work]. Write me a 200-character congrats + open-door message: (1) Genuine, specific congrats — name what is exciting about the move (the company, the role, the timing), (2) 1 sentence that signals I have been paying attention to their trajectory, (3) An open door — "I would value catching up once you are settled — happy to share what I have been seeing in [adjacent space] if useful", (4) No ask. Goal: reactivate the relationship before they get inundated with sales pitches in their new role.
Pro tip: Job changes are the highest-leverage relationship reactivation moment. Reaching out within 48-72 hours of the announcement is a senior signal of attentiveness.
Commentary Prompt Templates
4 promptsThoughtful Reply Under a Senior Leader's Post
37/40✨ What it does
ChatGPT writes a 100 to 150 word comment on [name + role]'s post about [topic] that adds a real point instead of a compliment. You paste it, then trim any sentence that sounds like you are performing.
I want to write a thoughtful reply to a LinkedIn post by [name + role] about [topic]. My genuine reaction: [briefly note your honest take — agreement, disagreement, addition, counterexample]. Write me a 100-150 word comment that signals senior peer engagement, not fanboying: (1) Open with the specific point in their post I am responding to (quote it briefly), (2) My substantive take — agree, disagree, or add — with specific reasoning and 1 concrete example from my own experience, (3) The 1 question I would push back on or extend with, (4) A close that leaves room for them to respond. Tone: peer talking to peer. No "great post" openers, no compliments — earn engagement through substance. Goal: top-quartile reply in the thread.
Pro tip: "Great post" comments are filtered out by senior LinkedIn users — they read as low-signal. Specific substantive replies (even respectful disagreement) get noticed by the original author.
Add Value to a Trend / News Discussion
38/40✨ What it does
ChatGPT writes a 100 to 200 word comment that adds your under-discussed angle on [topic] instead of repeating the hot takes. You post it on the thread, then stay to reply if someone pushes back.
I want to comment on a hot trend / news item in my space — [topic]. The dominant takes in the discussion right now: [the 2-3 most repeated angles]. My differentiated angle: [what is the under-discussed angle that I am uniquely positioned to add]. Write me a 100-200 word comment for a LinkedIn post or thread on this topic: (1) Acknowledge the dominant takes briefly (so I am not seen as missing the point), (2) Name what is being missed in the discussion — the second-order effect, the constraint nobody is naming, the historical analog, (3) The 1 specific data point or example from my work that anchors my angle, (4) Close with the question I would push the discussion toward. Goal: a comment that gets quoted or screenshot by others. Senior commentary builds inbound.
Pro tip: The senior commentary move is naming what the dominant takes are MISSING — not adding another generic agreement. Differentiated commentary is what builds inbound.
Polite Disagreement With a Peer Post
39/40✨ What it does
ChatGPT writes a 150-word polite disagreement that first names what you agree with, then states your real pushback. You paste [paraphrase] of their post, then send the comment only if you would say it to their face.
A peer / connection I respect posted something on LinkedIn I disagree with. Their post: [paraphrase]. My disagreement: [your honest take and reasoning]. Write me a 150-word comment that disagrees respectfully and substantively: (1) Open by acknowledging the post and what I AGREE with (do not skip this — it earns the right to disagree), (2) Name the specific point I push back on, (3) My reasoning, with 1 concrete example or data point, (4) Acknowledge what would make me change my mind, (5) Close with respect for the author. Tone: peer-to-peer, not adversarial. Goal: disagreement that strengthens the relationship instead of damaging it.
Pro tip: Always lead with what you agree with. Skipping that step is what makes LinkedIn disagreement feel adversarial — even if the substance is the same.
Quote-Tweet-Style Repost With Commentary
40/40✨ What it does
ChatGPT writes 100 to 200 words of repost commentary that adds your own point of view instead of a bare share. You attach the original, then post the commentary as the thing people read first.
I want to share a LinkedIn post by [name] with my own commentary (quote-repost style). The original post: [paraphrase or quote]. Why it matters to me / why I want to repost: [reason — agreement, surprise, validation, want to amplify a contrarian take]. Write me a 100-200 word repost commentary: (1) The 1-sentence hook that names why I am amplifying this, (2) 2-3 sentences of substantive engagement — what about the original I agree with, push back on, or extend, (3) The 1 angle I am adding that is not in the original — my unique contribution, (4) The link or repost mechanic. Tone: confident addition, not blind amplification. Goal: a repost that adds my own POV and earns me readers from the original author's audience.
Pro tip: Blind reposts add nothing to your own signal. Adding 100 words of your own POV turns the repost into a piece of YOUR content — and earns audience from the original.
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