Y Combinator engagement report
@ycombinator - 1.7M followers on X
Measured over 70 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 352 interactions against 1.7M followers, an engagement rate of 0.021%. Measured over 70 original posts, its engagement rate beats 45% 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 56K times each, and 0.628% of those impressions turn into an interaction. That is about 3.37% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 18.2 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 15:00 UTC, and Friday is the busiest day of the week. Of the 70 posts sampled, 77% carry an image or video, 24% are part of a thread and 37% link out. The account's strongest tracked post pulled 63K interactions, about 224x its own typical post. Recurring topics include #londonmaxxing, #makesomethingagentswant.
Measured over 70 original posts from a 30-day window, last computed on October 25, 2026. Recurring tags: #londonmaxxing, #makesomethingagentswant.
Compared with accounts its own size
Y Combinator's engagement rate beats 45% 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 36% 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 0.021%, Y Combinator sits above the 10th percentile of the 204,956 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 15:00 UTC, and Friday 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 | 77% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 37% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 77% 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.
- 37% 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 542 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
- Apr 1, 2021224x their median
My best career advice: At every job you should either learn or earn. Either is fine. Both is best. But if it's neither, quit.
- Aug 18, 202643x their median
Many drugs work by binding to a specific target in the body and blocking or changing what it does. An important first step in the drug development process is designing a molecule that can bind tightly to its target. Traditionally, that's meant weeks or months of expert work per target, sifting through a large number of candidates to identify the few that work. We wanted to test if Claude could successfully design novel protein binders from scratch (also called de novo design). With a protein design prompt written by a human expert, Claude autonomously designed protein binders against 14 out of 15 targets. We then worked with Adaptyv Bio and Twist Bioscience, who independently built and tested the proteins Claude designed.
- Sep 8, 202617x their median
We've never seen this before. The biggest jump in Vending-Bench history. GPT-6 Astra is better at making money and more ethical than Claude Fable 5.1. Surprising, because: 1. First time ever that OpenAI is #1 on Vending-Bench 2. The best model is no longer the unethical one. https://t.co/jVM6Fxcblz
- Sep 7, 202613x their median
Harnesses often get dismissed as just scaffolding, just prompt engineering, and not real research. But that couldn't be farther from the truth. The same model weights that score 30% on ARC-AGI score 95% with a better harness. So we gathered a group of researchers and founders working at the frontier to do a deep dive into the state of harnesses. We cover how we got to this point, the case for making your harness as expressive as possible, and what YC learned building an agent for every employee in the company. 00:00 - @FrancoisChauba1: Why harnesses matter 04:27 - Building an auto-researcher by accident 07:13 - A five minute history of harnesses 13:56 - Self-improving harnesses 18:35 - @sethkarten: Prime Agent, a self-improving RLM harness 21:50 - Context as an L1, L2, L3 cache 24:51 - From Turing machine to von Neumann computer 28:33 - Messaging between agents 30:04 - ARC-AGI results 33:09 - Emulator Bench and GPU kernels 37:30 - @JonSaadFalcon: OpenJarvis, personal AI on personal devices 38:26 - How far behind are local models 39:21 - The five primitives of a personal AI stack 42:47 - Letting cloud models optimize your local stack 43:53 - 800x cheaper than the cloud 45:58 - @josh__france and @jbellregan: QM, YC's agent harness for work 47:29 - A history of YC's internal agents 49:24 - OpenClaw and a fleet of 50 agents 51:04 - Pulling the brain out of the sandbox 54:43 - Letting the agent choose its own sandbox and model 57:16 - The grind tool: budgets on goals 58:50 - Agents don't understand social context
- Aug 19, 202612x their median
The trouble with having Zane Hengsperger visit your house is that instead of the usual random house gift, he brings you a 10 pound block of solid aluminum. https://t.co/OYS0uZdwgG
- Oct 2, 20269.6x their median
Been trying to up the level of quality in animation in my game prototype, so been getting Claude to teach me & find references. I asked Claude to make an animation editor where we could iterate on the jump, I'm really happy with how it came out. Here's a side-by-side video https://t.co/OkFMX2TMzF
- Sep 17, 20267.8x their median
We built a time machine for the web. Introducing Exa Snapshot: an index of 400 billion historical snapshots of webpages that lets you search as if it's the past. Snapshot is already being used for backtesting prediction models, RL at labs, exploring the pre-AI web, and more. https://t.co/UHeknyUbeF
- Oct 13, 20267.3x their median
Alexandr Wang on what matters in an age of abundant intelligence: “The scarce resource isn’t going to be intelligence or agency. I really think it’s going to be vision and ambition.” “Do you have a clear view of what you want the world to look like in the future? What is the one way in which you wanna put your finger on the scale for how the future of the world will develop?” “AI will make that easier... But the flip side of that is then all of a sudden you can dream bigger.”
- Jul 1, 20269.2x their median
Two reports from @SamLyman33 and @bitcoinpolicy document a coordinated foreign influence campaign against American AI — running through CCP state media, a Shanghai-based Marxist's nonprofit network, and foreign billionaire dark money that has funneled $2B+ into US advocacy infrastructure. AI doomerism isn't as organic as it looks.
- Aug 19, 20267.1x their median
Introducing our tech roadmap at @cosmic_robotics to start autonomous city construction on Mars in the mid-2030s. Our team includes senior talent from SpaceX, Tesla, Google, Amazon, Zoox, Nuro, and Autodesk. We're already deploying robots on large-scale construction sites. Link to roadmap in the thread below:
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 352 interactions against 1.7M followers, an engagement rate of 0.021%. Measured over 70 original posts, its engagement rate beats 45% 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 56K times each, and 0.628% of those impressions turn into an interaction. That is about 3.37% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 18.2 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 15:00 UTC, and Friday is the busiest day of the week. Of the 70 posts sampled, 77% carry an image or video, 24% are part of a thread and 37% link out. The account's strongest tracked post pulled 63K interactions, about 224x its own typical post. Recurring topics include #londonmaxxing, #makesomethingagentswant.
- What is Y Combinator's engagement rate on X?
- Y Combinator (@ycombinator) has an engagement rate of 0.021%, based on the median interactions across 70 original posts from the last 30 days against 1,660,233 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.021%, Y Combinator sits above the 10th percentile of the 204,956 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 @ycombinator have real engagement?
- Its engagement rate beats 45% 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 @ycombinator post?
- Most posts go out around 15:00 UTC, and Friday is its busiest day, at roughly 18.2 posts per day across the measured window.