Larry Kim engagement report
@larrykim - 679K followers on X
Measured over 11 original posts from a 30-day window, last computed on October 3, 2026.
Engagement
A typical post picks up 37 interactions against 679K followers, an engagement rate of 0.005%. Measured over 11 original posts, its engagement rate beats 26% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 12K times each, and 0.32% of those impressions turn into an interaction. That is about 1.70% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.5 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 16:00 UTC, and Monday is the busiest day of the week. Of the 11 posts sampled, 27% carry an image or video and 18% link out. The account's strongest tracked post pulled 106K interactions, about 2411x its own typical post.
Measured over 11 original posts from a 30-day window, last computed on October 3, 2026.
Compared with accounts its own size
Larry Kim's engagement rate beats 26% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 22% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.005%, Larry Kim sits above the 10th percentile of the 205,048 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 16:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 27% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 18% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 27% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 18% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 333 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Jun 1, 20262411x their median
To my fellow Angelenos who want change, and are considering voting for Nithya Raman, I can assure you, she is not fit for the job, and she has no path to victory. A vote for Nithya is a vote for Karen Bass. I am ready to earn your vote and make LA feel safe for all. https://t.co/qfnbS9qH4P
- May 31, 2026727x their median
Wow. 1,000 University of California professors signed an open letter to the Board of Regents demanding they bring back standardized testing after it was removed during covid for equity. They reveal that many STEM students are BELOW Middle School level in Math! “The SAT mathematics requirement is not an obstacle to equity; rather, it is a prerequisite for it. Failing to measure preparation gaps does not remove barriers; it moves them into the classroom, where they become harder to overcome.”
- May 21, 2026252x their median
Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why. First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it. Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands. Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition. I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively. THE 100X ORGANIZATION The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago. Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken. The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems. These roles will evolve. But waiting for that to happen naturally means falling behind now. The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working. THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS — THE BUILDERS: 10X ENGINEERS I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality. Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment. AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down. Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed. So who do you want orchestrating and reviewing code? And how do you want your best engineers to spend their time? If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code. The new world is about enabling your 10x engineers to become 100x. The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated. I call this the great reckoning of AI coding, and every company will face this soon if not already. More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well. — THE BUILDERS: 10X PRODUCT MANAGERS Product management and design roles are merging. Designers that have customer focus, become more like product managers. And product managers that have intuition for UX become more like designers. The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results. The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy. Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on. To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production. Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck. That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time. — THE SYSTEM MANAGERS Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp. The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world. You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is. — THE FRONT-LINERS In a world that will become saturated with AI communication, the human touch will matter more than anything to customers. This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings. One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers. REWARDING 100X IMPACT In a world where companies are able to do so much more with less, where does that excess money go? In our case, much of the savings in this new operating model will flow directly back to those that enabled it. We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them. You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace. Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems. THE FUTURE Nearly every company will make changes like these. The ones that do it proactively will define what comes next. The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago. ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.
- Jun 11, 2026253x their median
Opinion: SpaceX IPO makes Elon Musk the first trillionaire. Here’s how to properly hate him https://t.co/qAQVdquwCP
- Sep 25, 202675x their median
I came to the US on an H-1B almost 20 years ago after studying Electrical Engineering at Waterloo. Became US citizen in 2010 under EB-1A. In the last decade I’ve hired over 1,000 Americans and shipped products used by more than a million people. Pretty bummed to learn the program was a scam!
- Apr 6, 202313x their median
We’re on the Nasdaq Tower today in New York’s Times Square! Super proud of our team and grateful for our amazing investors. https://t.co/ROdUAx7sWs
- May 23, 202610x their median
Today we cut headcount by 87%. Business is stronger than ever. Let’s be direct. I own this. Productivity’s evolving. My company leads or dies. Not cost-cutting. Savings rocket to the survivors: $7.5M bands for 10000x AI impact. Deepest gratitude to the exited. Generous packages + LinkedIn kudos from strength. THE 10000X ORG Fewer humans. 10000x output. Old jobs = AI bottlenecks in hoodies. Builders: Elite engineers command agent armies. Everyone else = review spam. PMs merge into AI whisperers. No shipping code — that’s for agents. Agent Managers: Self-automators turned AI zookeepers. They eat. Front-Liners: Human soul for customers. Agents do the rest (flawlessly). Rewards: Savings fund the keepers. Old bands die. 10000x or goodbye. Future: Pricier humans + silicon slaves. We’re the revolution. Best to the “next chapter” crew ❤️
- Aug 24, 20263.2x their median
Every profession is in trouble with AI, but software QA has to be near the top of the list. My entire prompt to Claude: “QA time. Find the biggest bugs in my app.” It found and fixed them. That was it. I didn’t say what to test, where to look, or how to fix anything.
- Sep 27, 20263.2x their median
What skills if any will still matter in 5 years with AI eating up everything? Asking as a parent of 2 young boys. My plan: I am trying to nurture my youngest son towards relationship-based sales, and my older son to be an electrical or mechanical engineer for SpaceX.
- Sep 16, 20261.9x their median
Same old media bullshit ... h/t @DrEliDavid https://t.co/VayKqAmuGG
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 37 interactions against 679K followers, an engagement rate of 0.005%. Measured over 11 original posts, its engagement rate beats 26% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 12K times each, and 0.32% of those impressions turn into an interaction. That is about 1.70% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.5 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 16:00 UTC, and Monday is the busiest day of the week. Of the 11 posts sampled, 27% carry an image or video and 18% link out. The account's strongest tracked post pulled 106K interactions, about 2411x its own typical post.
- What is Larry Kim's engagement rate on X?
- Larry Kim (@larrykim) has an engagement rate of 0.005%, based on the median interactions across 11 original posts from the last 30 days against 679,290 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.005%, Larry Kim sits above the 10th percentile of the 205,048 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @larrykim have real engagement?
- Its engagement rate beats 26% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @larrykim post?
- Most posts go out around 16:00 UTC, and Monday is its busiest day, at roughly 0.5 posts per day across the measured window.