Best ChatGPT Prompts for LinkedIn Comments: 20 Copy-Paste Examples (2025)
Junaid Khalid
Contents
ChatGPT can write LinkedIn comments for you—but only if you give it the right prompts.
Most people type "write a comment on this post" and get generic, robotic responses that scream "AI-generated." The difference between terrible and excellent ChatGPT comments isn't the AI—it's the prompt.
This guide provides 20 copy-paste ready ChatGPT prompts for LinkedIn comments, organized by use case. Each includes example outputs so you know exactly what to expect.
Why Prompts Matter More Than You Think
Bad prompt:
"Write a comment on this LinkedIn post"
ChatGPT output:
"Great post! Very insightful. Thanks for sharing your perspective on this important topic."
Generic. Robotic. Obvious AI.
Good prompt:
"Write a 40-word LinkedIn comment on this post. Reference one specific detail from the post, add a personal insight or contrarian viewpoint, and ask a thoughtful follow-up question. Use casual professional tone:"
ChatGPT output:
"Your point about async communication saving 10 hours weekly resonates. We've seen similar gains, though we struggled initially with timezone coordination across APAC teams. Did you implement any specific protocols for urgent matters that can't wait?"
Specific. Thoughtful. Sounds human.
The difference: Prompt specificity determines output quality.
How to Use These Prompts
Step-by-step:
- Copy the prompt template
- Read the LinkedIn post you want to comment on
- Copy the post text
- Paste prompt + post text into ChatGPT
- Review AI output and customize if needed
- Post your comment on LinkedIn
Pro tip: Always review and customize. Even great prompts need a human touch for authenticity.
Category 1: General Engagement Prompts
Prompt #1: The Thoughtful Response
Write a 50-word LinkedIn comment on this post. Reference one specific detail or statistic from the post, share a brief related personal experience or observation, and ask a follow-up question that invites the author to elaborate. Use a conversational professional tone:
[paste post text]
Example output:
"The 73% increase in remote work productivity you mentioned aligns with our Q4 data. Interestingly, we noticed the biggest gains came from mid-level managers, not executives as expected. Have you seen similar patterns in leadership vs. individual contributor performance?"
Prompt #2: The Value-Add Comment
You're commenting on a LinkedIn post. Write a 60-word comment that adds new information, research, or a practical tip related to the post's topic. Reference the author's main point, then expand on it with something they didn't mention. Be specific and cite sources if applicable:
[paste post text]
Example output:
"Your framework for customer retention is solid. To add to point #3 about personalization—Salesforce's 2024 State of Marketing report found that 72% of customers expect personalized interactions, but only 38% of companies deliver it consistently. We've had success using dynamic content blocks in email sequences to bridge that gap. What personalization tactics have worked best for your clients?"
Prompt #3: The Contrarian-but-Respectful
Write a 50-word LinkedIn comment that respectfully disagrees with or challenges one aspect of this post. Start by acknowledging what you agree with, then present a different perspective backed by logic or experience. End with an open question. Tone: professional and collaborative, not combative:
[paste post text]
Example output:
"I agree with your points on AI efficiency gains. However, I'd challenge the idea that AI replaces human creativity entirely—in our content team, AI handles research and first drafts, but our strongest performing pieces still come from human insight and storytelling. Are you seeing creative roles evolve rather than disappear?"
Category 2: Industry-Specific Prompts
Prompt #4: For Marketing Posts
Write a 55-word LinkedIn comment on this marketing-related post. Reference a specific tactic or strategy mentioned, share a brief real-world result or case study from your experience (or a hypothetical if you don't have one), and ask about implementation challenges or next steps:
[paste post text]
Example output:
"Your A/B testing methodology for email subject lines is exactly what we implemented last quarter. We saw open rates jump from 22% to 34% just by testing personalization vs. urgency. The challenge was sample size—how many sends do you recommend before declaring a winner statistically significant?"
Prompt #5: For SaaS/Tech Posts
You're a SaaS professional commenting on this LinkedIn post about tech or software. Write a 60-word comment that references the technical aspect discussed, asks about implementation details or edge cases, and shares a relevant technical consideration:
[paste post text]
Example output:
"Your API rate limiting strategy is smart. We implemented similar token bucket algorithms last year. One question: how do you handle burst traffic during product launches when legitimate users might hit limits? We ended up building a dynamic threshold system based on user tier and historical behavior. Curious how others solve this."
Prompt #6: For Sales Posts
Write a 50-word LinkedIn comment on this sales-focused post. Reference the sales technique or challenge mentioned, share how you've applied or seen similar approaches work (or fail), and ask about objection handling or a specific scenario:
[paste post text]
Example output:
"The 'give value first' approach you describe is underrated. We started sending custom video audits to prospects before discovery calls—our show rate jumped from 60% to 81%. The time investment is real though. How do you scale personalization when handling 50+ outbound conversations weekly?"
Category 3: Question-Based Prompts
Prompt #7: The Curious Follow-Up
Write a 40-word LinkedIn comment that asks two thoughtful follow-up questions about this post. The questions should dig deeper into the author's methodology, results, or thinking. Don't just ask generic questions—be specific to the content:
[paste post text]
Example output:
"This framework for team structure is fascinating. Two questions: 1) How do you handle cross-functional dependencies when teams are fully autonomous? 2) What metrics do you use to measure whether the structure is actually working vs. traditional hierarchies?"
Prompt #8: The Implementation Question
You've just read this LinkedIn post and want to implement the strategy discussed. Write a 55-word comment that shows you're seriously considering applying this, asks specific questions about the implementation process, and references potential challenges you might face:
[paste post text]
Example output:
"I'm planning to test this content repurposing system for our blog. Before I start, I'm wondering: how do you maintain brand voice consistency when repurposing across 5+ platforms? And did you notice any platform-specific engagement patterns that changed your repurposing approach?"
Category 4: Personal Story Prompts
Prompt #9: The Shared Experience
Write a 60-word LinkedIn comment that shares a brief personal story or experience directly related to this post's topic. Your story should validate or expand on the author's point. Include what you learned and how it changed your approach:
[paste post text]
Example output:
"Your point about transparent pricing hit home. Last year we hid pricing behind 'Contact Sales' and conversion dropped 40%. The moment we published clear pricing (even for enterprise), inbound demo requests tripled and sales cycles shortened by 18 days. Transparency builds trust faster than we expected. Did you measure similar time-to-close improvements?"
Prompt #10: The Lesson Learned
Write a 50-word LinkedIn comment sharing a relevant mistake or lesson learned related to this post's topic. Be vulnerable but professional. Explain what happened, what you learned, and how it relates to the author's advice:
[paste post text]
Example output:
"Wish I'd read this 2 years ago. We scaled our team from 8 to 45 people in 6 months without proper onboarding systems—chaos ensued. The 30-60-90 day framework you outlined is exactly what we built after that painful lesson. How do you adapt onboarding for remote vs. hybrid teams?"
Category 5: Data-Driven Prompts
Prompt #11: The Stats-Backed Response
Write a 55-word LinkedIn comment that supports this post's argument with relevant statistics, research, or data. Cite the source if possible, explain how the data relates to the author's point, and ask if they've seen similar patterns:
[paste post text]
Example output:
"Your emphasis on video content aligns with Wyzowl's 2024 Video Marketing Report—91% of businesses now use video as a marketing tool, up from 86% last year. More interesting: 92% of marketers say video gives them positive ROI. Have you found certain video formats (short-form vs. long-form) perform better for B2B audiences?"
Prompt #12: The Comparison Comment
Write a 60-word LinkedIn comment that compares this post's insights with trends, benchmarks, or data from your industry or recent research. Highlight where the author's experience aligns with broader trends and where it differs:
[paste post text]
Example output:
"Your 2-3% conversion rate on cold outbound matches LinkedIn's B2B benchmarks almost exactly. What's interesting is that you're achieving this with personalized video—most teams hitting 2-3% are using templated sequences at scale. This suggests high-effort personalization and volume-based templates yield similar results. Has that held true as you've scaled?"
Category 6: Actionable Takeaway Prompts
Prompt #13: The Implementation Plan
Write a 50-word LinkedIn comment that extracts one key takeaway from this post and explains exactly how you plan to implement it. Be specific about your first step and timeline. Ask the author for tips on avoiding common mistakes:
[paste post text]
Example output:
"Taking your advice on LinkedIn post consistency—starting Monday, I'm committing to 3 posts weekly for 90 days to test engagement patterns. Planning to batch-write on Sundays and use native scheduler. What's the #1 mistake you see people make when building consistent posting habits?"
Prompt #14: The Tactical Breakdown
You're commenting on a LinkedIn post with actionable advice. Write a 55-word comment that breaks down which specific tactic from the post you found most valuable and why. Explain how it applies to your specific situation:
[paste post text]
Example output:
"Of the 7 tactics you shared, #4 (segmenting email list by engagement level) is pure gold. We've been sending identical emails to everyone—no wonder open rates plateaued at 18%. Going to create 3 segments this week: engaged, moderate, cold. Did you see immediate lift or did it take a few sends?"
Category 7: Networking & Relationship Prompts
Prompt #15: The Collaboration Opener
Write a 45-word LinkedIn comment that genuinely expresses interest in the author's work or perspective and opens the door for potential collaboration, conversation, or knowledge sharing. Be specific about why you're interested and what you'd like to discuss:
[paste post text]
Example output:
"Your approach to community-led growth is exactly what we're exploring for our SaaS product. Would love to hear more about how you measured community impact on pipeline and retention. Open to grabbing virtual coffee if you're up for swapping notes?"
Prompt #16: The Expert Acknowledgment
Write a 40-word LinkedIn comment that acknowledges the author's expertise in this area, references a specific insight from their post that demonstrates deep knowledge, and asks for their opinion on a related advanced topic:
[paste post text]
Example output:
"Your breakdown of CAC payback periods across different customer segments shows real depth. Most founders only track blended CAC. Question for you: at what ARR scale did you start seeing meaningful differences in enterprise vs. SMB payback periods?"
Category 8: Future-Focused Prompts
Prompt #17: The Trend Prediction
Write a 55-word LinkedIn comment that takes this post's topic and discusses where you see it heading in the next 12-24 months. Reference the author's current insights and project forward. Ask if they agree with your prediction:
[paste post text]
Example output:
"Your analysis of AI in content creation is spot-on for 2025. I predict by 2026 we'll see 'AI authenticity' become a major differentiator—brands that openly disclose AI usage and focus on human editing will outperform those trying to hide it. Do you see transparency becoming competitive advantage?"
Prompt #18: The Evolution Comment
Write a 50-word LinkedIn comment that discusses how the topic in this post has evolved over time. Reference how things used to be, acknowledge the author's current insights, and ask where they see further evolution happening:
[paste post text]
Example output:
"Remember when 'growth hacking' just meant viral loops and referral programs? Your post shows how sophisticated it's become—multi-touch attribution, cohort analysis, product-led growth. What's the next evolution? I'm betting on AI-powered predictive churn models becoming table stakes by 2026."
Category 9: Appreciation & Support Prompts
Prompt #19: The Genuine Praise
Write a 45-word LinkedIn comment that offers specific, genuine praise for this post. Don't be generic—point out exactly what made it valuable (clarity, data, contrarian view, etc.) and explain who should read it:
[paste post text]
Example output:
"This is the most comprehensive breakdown of LinkedIn organic reach I've seen in 2025. The chart showing post performance by time-of-day was especially valuable—most guides ignore timezone impact. Every B2B marketer should bookmark this."
Prompt #20: The Amplification Comment
Write a 40-word LinkedIn comment that amplifies this post's message by adding your endorsement and explaining why your network should pay attention. Tag a specific group of people who would benefit:
[paste post text]
Example output:
"Every founder raising Series A should read this. Your framework for investor updates—monthly vs. quarterly, metrics to include, storytelling structure—is exactly what VCs want to see. Sharing with my portfolio companies."
Tips for Better ChatGPT Comments
1. Always customize: Even the best prompts need human editing for authenticity.
2. Vary your prompts: Don't use the same prompt for every comment—LinkedIn's algorithm (and humans) notice patterns.
3. Add context: If you have industry-specific context, add it to the prompt: "You work in B2B SaaS marketing..." or "You're a fractional CMO..."
4. Specify length: Include word count targets (40-60 words ideal for LinkedIn).
5. Request tone: Add "conversational," "professional," "casual," or "thought-provoking" to get the right voice.
6. Use examples: If you have a style you like, paste an example comment into the prompt as reference.
Prompt Template Framework
Build your own custom prompts using this formula:
Write a [WORD COUNT]-word LinkedIn comment on this post.
[INSTRUCTION 1: Reference specific detail]
[INSTRUCTION 2: Add your perspective/experience]
[INSTRUCTION 3: Ask question or call-to-action]
Tone: [conversational/professional/thoughtful]
[paste post text]
Example:
Write a 50-word LinkedIn comment on this post.
Reference one specific tactic from the author's framework, share a brief result you've seen (or a hypothetical scenario), and ask about potential challenges in implementation.
Tone: conversational but professional
[paste post text]
Free vs. Automated Solutions
ChatGPT (Free/Paid):
- Unlimited comment generation
- Requires manual copy-paste workflow
- No voice learning
- Good for occasional use
LigoAI (Free trial, then paid):
- 30 comments free to test AI quality
- AI learns your commenting voice
- One-click generation directly in LinkedIn
- Multi-platform (LinkedIn, Twitter, Reddit, Facebook)
- Better for daily/high-volume use
When to use which:
- Low volume (5-10 comments/week): ChatGPT is great
- High volume (15+ comments/week): LigoAI saves significant time
- Testing AI comments: Start with ChatGPT, try LigoAI free trial
Common ChatGPT Comment Mistakes
Mistake #1: Too Generic ❌ "Great post! Very insightful." ✅ "Your point about async standup meetings saving 5 hours weekly matches our experience—we saw similar gains after switching from daily Zoom calls to Loom updates."
Mistake #2: Too Long ❌ 150-word essay comments ✅ 40-60 words max (LinkedIn best practice)
Mistake #3: No Personalization ❌ Using AI output without editing ✅ Always customize with your voice/experience
Mistake #4: No Engagement Hook ❌ Statements with no follow-up ✅ End with a question or call-to-action
Mistake #5: Obvious AI ❌ "As an AI language model..." or overly formal language ✅ Conversational, specific, human-sounding
Advanced Prompt Techniques
Technique #1: Multi-Step Prompts
Instead of one prompt, use two:
Step 1:
"Read this LinkedIn post and identify the 3 main points: [paste post]"
Step 2:
"Now write a 50-word comment that references point #2, shares a brief experience, and asks a follow-up question."
Result: More targeted comments because ChatGPT analyzed first.
Technique #2: Voice Training
Add examples of your past comments to train ChatGPT:
"Here are 3 LinkedIn comments I've written that reflect my voice and style: [paste 3 of your actual comments]
Now write a comment in the same style for this post: [paste new post]"
Result: Comments that actually sound like you.
Technique #3: Constraint-Based Prompts
Add specific constraints:
"Write a LinkedIn comment (50 words max) that:
- Uses zero buzzwords or jargon
- Includes one specific number or stat
- Asks exactly one question
- Sounds like a conversation, not a blog post
[paste post]"
Result: Cleaner, more authentic output.
Measuring Comment Quality
How to tell if your AI comment is good enough:
✅ Passes the "scroll test": Would you read this if someone else posted it?
✅ Adds value: Does it contribute new information, perspective, or questions?
✅ Sounds human: No AI buzzwords ("delve into," "in conclusion," "utilize")
✅ Is specific: References details from the post, not generic praise
✅ Invites response: Author or others would want to reply
✅ Shows you read: Couldn't be copied/pasted to any other post
Final Thoughts
ChatGPT can write excellent LinkedIn comments—if you give it excellent prompts.
The 20 prompts in this guide will save you hours while helping you build genuine relationships on LinkedIn. But remember: AI is a tool to enhance your voice, not replace it.
Always review, customize, and add your human touch.
Next steps:
- Bookmark this page
- Try 3-5 different prompts this week
- Note which generate the best responses
- Build your own prompt library from what works
If you comment frequently (15+ times/week), consider trying LigoAI's free trial for a more integrated workflow with voice learning.
Frequently Asked Questions (FAQ)
What is the best ChatGPT prompt for LinkedIn comments?
The best prompt includes three elements: (1) specific word count (40-60 words), (2) clear instructions (reference specific detail, add insight, ask question), and (3) tone specification (conversational professional). Example: "Write a 50-word LinkedIn comment on this post. Reference one specific detail, share a brief related experience, and ask a follow-up question. Use conversational professional tone: [paste post]." This structure consistently produces authentic, engaging comments.
How do I make ChatGPT comments sound more human?
Specify constraints in your prompt: no buzzwords, conversational tone, specific word count, and include a question. Add context like "You're a [your role]" to the prompt. Most importantly, always customize ChatGPT's output before posting—add your personal touch, change 2-3 words, adjust tone. Use the voice training technique by feeding ChatGPT examples of your past comments to analyze your style.
Can LinkedIn detect ChatGPT-generated comments?
LinkedIn can't directly detect if you used ChatGPT to write a comment. However, they can detect patterns like identical comments across multiple posts, obvious AI language (buzzwords like "delve into" or "leverage"), or suspiciously fast commenting speeds. If you customize each ChatGPT output and post manually at human speed, detection risk is zero. The tool itself is safe—careless use is risky.
What's the ideal length for ChatGPT LinkedIn comments?
40-60 words is optimal for LinkedIn comments. This length is substantial enough to add value and show you read the post, yet short enough that people actually read it. Comments under 30 words often feel shallow; comments over 80 words rarely get read fully. Always specify word count in your ChatGPT prompt: "Write a 50-word comment..." ensures appropriate length.
Should I use ChatGPT free or paid for LinkedIn comments?
ChatGPT free (GPT-3.5) is sufficient for most LinkedIn commenting needs. ChatGPT Plus ($20/month, GPT-4) produces slightly better quality with more nuanced understanding and natural language, but the difference is incremental for short-form comments. Use free for testing; upgrade to Plus if you're also using ChatGPT for long-form content, complex analysis, or high-volume commenting where quality matters most.
How many LinkedIn comments can I generate with ChatGPT?
ChatGPT free offers unlimited comment generation with no usage caps. ChatGPT Plus ($20/month) also offers unlimited usage but with higher rate limits during peak times and access to GPT-4. There are no daily or monthly limits on how many comments you can generate—the constraint is your time for the manual copy-paste workflow, not the AI's capacity.
Can I automate posting ChatGPT comments to LinkedIn?
No, and you shouldn't try. LinkedIn's Terms of Service prohibit fully automated posting without human oversight. The safe approach: use ChatGPT to generate comment suggestions, review and customize each one, then manually post to LinkedIn. Tools that auto-post ChatGPT outputs carry high ban risk. The value is in AI assistance, not complete automation.
What mistakes should I avoid when using ChatGPT for comments?
Avoid these common mistakes: (1) posting AI output without customization, (2) using the same prompt for every comment (creates pattern), (3) not specifying word count (outputs too long), (4) generic prompts producing generic comments, (5) posting too fast (10+ comments in 5 minutes looks automated), and (6) using obvious AI language like "delve into" or "in conclusion." Always review and edit before posting.
How do I train ChatGPT to write in my voice?
Use the voice training technique: (1) collect 10-20 of your best past comments, (2) paste them into ChatGPT with prompt "Analyze these LinkedIn comments and describe the writing style, tone, and patterns: [paste comments]", (3) save ChatGPT's analysis, (4) for future prompts, include "Write in this style: [paste style analysis]" or reference the conversation. This teaches ChatGPT your unique voice patterns for more authentic outputs.
Is using ChatGPT for LinkedIn comments considered cheating?
No, using AI writing assistance is not cheating—it's a tool like spell-check or grammar correction. Most professionals use some form of assistance (editors, templates, tools) for content creation. The key is adding your authentic perspective and expertise. AI helps you articulate thoughts faster; you provide the insights and judgment. LinkedIn doesn't prohibit AI writing assistance; they prohibit fully automated behavior without human oversight.
Related Resources
About the Author
Junaid Khalid
I have helped 50,000+ professionals with building a personal brand on LinkedIn through my content and products, and directly consulted dozens of businesses in building a Founder Brand and Employee Advocacy Program to grow their business via LinkedIn