Someone asked you to write them a LinkedIn recommendation, and you have been staring at a blank box for ten minutes. Or you are the one who needs recommendations and every draft you get back reads like it was copied from the same template as everyone else's. Either way, you want a real example you can adapt in five minutes, not another lecture on why recommendations matter.
This guide gives you 14 copy-paste examples grouped by relationship, a simple five-part structure, and the fixes that separate a recommendation people actually read from one they scroll past. Every example is written to be personalized, not pasted word for word, because a recommendation that sounds like a template helps no one.
Key takeaways
- Use the 5-part structure: context, one specific project, measurable impact, a standout trait, and a confident close. It works for every relationship type.
- Be specific, not flattering. "Increased trial signups 22% in one quarter" beats "hardworking and dedicated" every time. Vague praise reads as filler.
- Length is 2 to 4 short paragraphs, roughly 75 to 150 words. Long enough to be credible, short enough that people finish it.
- Match the recommendation to the person's next goal. A recommendation aimed at a job seeker should highlight different things than one aimed at a consultant courting clients.
- You cannot recommend yourself. LinkedIn only lets you write recommendations for 1st-degree connections, and the recipient chooses whether to display it.
- Write in your own voice. The point of a recommendation is that a real person vouched for someone. A generic paragraph defeats the entire purpose.
The 5-part structure behind every good recommendation
Every strong LinkedIn recommendation, regardless of who it is for, hits the same five beats. Learn these once and you never face a blank box again.
- Context. How you know the person and for how long. One sentence. "I managed Priya for two years on the growth team at Acme."
- One specific project. Not a list of adjectives. Pick a single real thing they did that you witnessed. Specificity is what makes it believable.
- Measurable impact. A number, an outcome, or a concrete result. If you cannot attach a metric, describe the before-and-after in plain terms.
- A standout trait. The one quality that makes this person different from everyone else with the same job title. This is the line the reader remembers.
- A confident close. A clear, unhesitating endorsement. "I would hire her again in a heartbeat" carries more weight than "I recommend her."
The infographic below lays out the five parts in order so you can keep them in view while you write.
The most common failure is skipping straight to step four, the adjectives, and never touching steps two and three. That is how you end up with "a talented, dedicated professional who is a pleasure to work with," which describes roughly everyone and convinces no one.
LinkedIn recommendation examples by relationship
Here are 14 examples, grouped by how you know the person. Replace the bracketed details with real specifics. Keep the structure, change the substance.
For a manager or mentor
Example 1, direct manager:
I reported to Daniel for three years as he built our support org from four people to thirty. What stood out was not just the scale but how deliberate he was about it. He rewrote our onboarding so new hires were taking live tickets in a week instead of a month, which cut our time-to-productivity in half. Daniel is the rare leader who is both demanding and genuinely on your side. I learned more about managing people from him than from any course. Any team would be lucky to have him leading it.
Example 2, mentor:
I have known Sofia as a mentor since I was a junior designer figuring out how to present work to executives. She taught me to lead with the decision, not the process, advice I still use every week. During one high-stakes rebrand, she coached me through three rounds of leadership feedback without ever taking the pen from my hand. Sofia lifts the people around her instead of outshining them. I recommend her without reservation.
For a peer or colleague
Example 3, close collaborator:
Marcus and I worked side by side on the analytics team at Northwind for two years. He approaches messy data problems with a calm, structured logic that I have not seen matched. During our Q3 pricing overhaul, he built the model that let us test five scenarios in a day instead of a week, and his read on the numbers is the reason we shipped the right one. Marcus is the colleague you want in the room when the stakes are high. I would jump at the chance to work with him again.
Example 4, cross-functional peer:
I partnered with Lena across engineering and marketing on more launches than I can count. She is the translator every company needs, the person who can sit between a skeptical engineer and an impatient stakeholder and get both to yes. On our platform launch she kept nine workstreams aligned and shipped on time, which almost never happens. Lena makes hard collaboration look easy. Highly recommended.
Example 5, junior colleague you saw grow:
When Amir joined our team he was two years out of school and clearly nervous. Eighteen months later he was leading our most complex integration and mentoring the next new hire. He owns problems end to end instead of handing them off, and he asks the question everyone else is too proud to ask. Amir's growth curve is the steepest I have watched up close. He is going to do serious things.
For a direct report
Example 6, high performer:
I managed Chloe as a senior engineer on our infrastructure team, and she is the kind of engineer who makes every system she touches more reliable. She rebuilt our deployment pipeline and cut production downtime by roughly 30%, which our whole org felt. Beyond the technical work, she quietly raised the bar for code review across the team. I would rehire Chloe without a second thought.
Example 7, someone who exceeded their role:
Tomás started as a customer support rep and left as the person who effectively ran our knowledge base. He noticed our top 20 questions were eating half the team's time, built out self-serve docs for each, and deflected a measurable chunk of ticket volume, all without being asked. He sees the problem behind the problem. Whatever team gets him next is getting a force multiplier.
For a client or vendor
Example 8, consultant you hired:
We brought in Rachel to untangle a demand-gen program that had stalled. Within a quarter she had rebuilt our attribution so we could finally see which channels were working, and reallocated spend toward the two that were. Leads went up and cost per lead came down. Rachel tells you what you need to hear, not what you want to hear, which is exactly why we kept working with her. I recommend her to any founder who is tired of vanity metrics.
Example 9, agency or service provider:
Our agency worked with Kenji's team for over a year, and the difference from our previous vendor was night and day. He set clear expectations, hit every deadline, and treated our budget like it was his own. When a campaign underperformed he flagged it early and came with a fix, not an excuse. Kenji is the partner you keep. I would recommend his work to anyone.
For a job seeker or student
Example 10, recent graduate:
I supervised Aisha during her internship, and she operated at the level of someone with years more experience. She took a vague brief to audit our email onboarding, turned it into a concrete set of fixes, and shipped the top three before her internship ended. She is curious, coachable, and genuinely fun to work with. Any employer who passes on her is making a mistake.
Example 11, career changer:
Ben came to product management from a decade in teaching, and it turns out that was his superpower. He can explain a complicated roadmap to a room full of engineers and a room full of executives and have both walk out clear. On his first project he ran a discovery process that killed a feature we would have wasted a quarter building. Ben brings a rare mix of empathy and rigor. He has my full recommendation.
Example 12, short and strong (when you are short on time):
Nina and I worked together for two years, and she is one of maybe three people I would drop everything to work with again. She turned our content program from an afterthought into our top source of inbound leads. She is relentless about quality and generous with credit. Hire her before someone else does.
Example 13, intern:
Priya interned with our product team for a summer and outperformed people twice her tenure. Handed a vague brief to clean up our user-research notes, she built a tagged, searchable library the whole team still uses. She asks sharp questions, takes feedback without ego, and ships. If you can hire her before she graduates, do it.
Example 14, written for a recruiter to read (job seeker):
I worked with Jordan for three years and would put my name behind him for any senior operations role. He took our fulfillment process from a daily fire drill to a system that ran itself, cutting late shipments by roughly 40%. He is calm under pressure, relentless about the details, and the person the team looks to when something breaks. Any hiring manager would be lucky to get him.
What to write when you barely know the person
Sometimes you are asked to recommend someone you worked with only briefly, and the honest problem is you do not have a rich, specific story to tell. Do not fake one. A recommendation that invents detail reads false, and false is worse than short.
Instead, narrow the frame. Recommend the one thing you can genuinely speak to.
I only worked with Omar on a single project, but it was enough to see how he operates. He took the messiest part of our migration, the part nobody wanted, and made it his. He is the person who runs toward the hard thing. On that basis alone, I would happily work with him again.
Honesty about the limits of your view actually makes the praise more credible, not less. A reader trusts a specific claim about one project more than a sweeping claim you clearly cannot back up.
The mistakes that make a recommendation forgettable
Most weak recommendations fail in the same predictable ways. Avoid these five and you are already ahead of 90% of what gets posted.
- All adjectives, no evidence. "Hardworking, reliable, and a great team player" could be anyone. Trade every adjective for a fact.
- Too long. A 300-word recommendation does not get read. Two to four tight paragraphs is the sweet spot.
- Generic open. "It is my pleasure to recommend" is the same first line on a million recommendations. Open on the specific relationship or a specific moment instead.
- No standout trait. If your recommendation could be swapped onto three other people without anyone noticing, it says nothing. Name the one thing that is uniquely theirs.
- A weak close. "I recommend them" is a shrug. "I would hire them again tomorrow" is a stance. Take the stance.
A recommendation that could be swapped onto three other people without anyone noticing is not a recommendation. It is filler with a name on it.
How to actually write yours in five minutes without sounding generic
Here is the honest tension. The best recommendations sound like a specific human wrote them, because a specific human did. But when you sit down to write one, especially several at once, the words come out stiff and corporate, and you reach for the same tired phrases everyone uses. The result reads like AI even when a person typed it.
This is exactly the problem LiGo was built to solve, just pointed at recommendations. LiGo's voice layer, LiGo Brain , learns how you actually write from your own past LinkedIn posts and comments, so anything it drafts sounds like you rather than like generic corporate filler. Feed it the specifics (who the person is, the one project, the result) and it drafts a recommendation in your voice that you then edit and send. You keep the authenticity, you skip the blank-box paralysis. Because the model is trained per profile, an agency writing recommendations on behalf of different clients gets each one in that client's voice, not one flattened house style. That is the whole point of a recommendation: it has to sound like the person vouching, not like software.
It matters that this is a co-pilot, not a bot. LiGo is not a scraping automation that logs into your account and acts on its own; it drafts, you review, and it posts to LinkedIn through LinkedIn's official OAuth API. Nothing goes out that you have not read. For something as personal as vouching for someone by name, that human check is the point, not a limitation.
If you are on the other side of this, waiting for recommendations to come in, the bottleneck is usually the asking, not the writing. Our full guide on how to ask for a LinkedIn recommendation walks through the exact message that gets a yes and a reply within a day.
And once the recommendations land on your profile, make sure the rest of it earns them. A strong About section and a clear personal brand turn social proof into an actual first impression.
Questions fréquemment posées
What should I write in a LinkedIn recommendation?
Follow the five-part structure: state how you know the person and for how long, describe one specific project you saw them handle, add a measurable result or concrete outcome, name the single trait that makes them stand out, and close with a confident endorsement. Keep it to two to four short paragraphs and trade generic adjectives for real evidence.
How long should a LinkedIn recommendation be?
Roughly 75 to 150 words, or two to four short paragraphs. That is long enough to include a specific story and a result, and short enough that people actually finish reading it. Anything past about 200 words tends to lose the reader, and one strong paragraph beats three padded ones.
Can I write a LinkedIn recommendation for myself?
No. LinkedIn only lets you write a recommendation for a 1st-degree connection, and you cannot recommend yourself. The person you recommend also chooses whether to display it on their profile. If you want more recommendations on your own profile, the move is to request them from people you have worked with, not to write your own.
What makes a LinkedIn recommendation stand out?
Specificity. A recommendation stands out when it names a real project, attaches a number or outcome, and calls out one trait that is uniquely that person's. Vague praise blends into every other recommendation; a concrete claim ("cut onboarding time in half," "grew content into our top lead source") is what a reader remembers and believes.
Should a recommendation focus on skills or personality?
Both, but anchor it in evidence. Lead with what the person did and the result it produced (skills and impact), then add the one personal quality that made it possible. "She rebuilt our pipeline and cut downtime 30%, and she did it while quietly raising the bar for the whole team" works because the personality claim is earned by the concrete one.
How many recommendations should I have on my profile?
There is no magic number, but a handful of specific, credible recommendations from a mix of managers, peers, and clients does far more than a dozen generic ones. Aim for quality and variety of perspective. Two great recommendations that each tell a real story will outweigh ten that all say "great to work with."
What is a good sample recommendation for a colleague?
A strong recommendation for a colleague opens with how you worked together, names one specific project you both remember, and adds the result it produced. For example: "Marcus and I worked side by side on the analytics team at Northwind for two years. During our Q3 pricing overhaul, he built the model that let us test five scenarios in a day instead of a week, and his read on the numbers is the reason we shipped the right one. I would jump at the chance to work with him again." Swap in your own project and outcome, and keep it to two to four sentences.
