Sequoia Capital engagement report
@sequoia - 819K followers on X
Measured over 3 original posts from a 30-day window, last computed on September 27, 2026.
Engagement
Early reading. We have captured 3 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.
A typical post picks up 377 interactions against 819K followers, an engagement rate of 0.046%. Posts are seen about 227K times each, and 0.166% of those impressions turn into an interaction. That is about 27.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 17:00 UTC, and Wednesday is the busiest day of the week. Of the 3 posts sampled, 67% carry an image or video and 33% link out. The account's strongest tracked post pulled 1.6K interactions, about 4.3x its own typical post. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
Measured over 3 original posts from a 30-day window, last computed on September 27, 2026. Recurring tag: #observability.
Where this sits in the catalog
At 0.046%, Sequoia Capital sits above the 25th percentile of the 205,676 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.679% |
| 90th percentile | 2.56% |
| 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 17:00 UTC, and Wednesday 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 | 67% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 33% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 67% 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.
- 33% 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 765 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
- Sep 10, 20264.3x their median
https://t.co/1h0NXW3wm3
- Jun 12, 20262.6x their median
Ad Astra @elonmusk and @SpaceX 🫡🚀 https://t.co/HJReXx3sS2
- Aug 18, 2026
Today we're announcing our $100M Series C at a $1B valuation, led by @ICONIQCapital. It's our third round in 14 months and brings our total funding to over $200m The round came together in less than 48 hours. We weren't planning to raise. Then new ARR doubled last quarter and we crossed 600+ customers including public companies and enterprises with $2B in revenue. Rillet AI agent usage is growing 70% each month and CFOs are replacing Oracle Fusion, SAP and Workday to run their companies on Rillet. We also announced our alliance with EY and officially partnered with more than half of the top 20 CPA firms. @RilletHQ is creating an entirely new category of finance infrastructure. With Rillet, the ERP becomes the harness for the modern finance organization, where people and agents share the same financial data, apply the same accounting policies and controls, and work from a single, continuously updated view of the business. Agents perform increasingly complex financial work, while finance teams retain visibility, approval authority and a complete audit trail. Thank you to our customers for believing in the mission and building the future of finance with us. We could not do this without you. Thank you to the Rillet team. As I say often, building Rillet is our own version of sending rockets to Mars. It is incredibly difficult. You make it look easy. Finally, thank you to our investors. To ICONIQ for leading the round and to our existing and new investors for building with us. @sequoia , @a16z, Sequoia Global Equities, @BainCapVC, @oakhcft, @BatteryVentures, @FirstMarkCap, @scalevp, and @creandum. Back to work :)
- Aug 11, 2026
OWN YOUR INTELLIGENCE Last year, building on open-weight models was primarily a cost rationalization exercise. Slightly worse performance for a much cheaper price. Now, it is increasingly an existential and strategic topic for our portfolio. Intelligence is the product. Companies want to shape it and own it and let it compound within their own walls. Not your weights, not your product. Now, with frontier open-weight models and fantastic tooling/infrastructure, owning your intelligence at the frontier is finally becoming possible. The result: every application company we work with is embarking on the journey of doing their own research on post-training, evals, harnesses, etc. The hottest neolabs may just be @Harvey, @FactoryAI, @Ramp, etc. The list goes on. We held a summit @sequoia to convene our portfolio on this topic, together with @gabepereyra (@Harvey) on building Harvey Labs, @lqiao (@FireworksAI_HQ) on post-training, @hwchase17 (@LangChain) on harnesses + evals, @BrendanFoody (@mercor) on RL environments and synthetic data, @QuantumArjun (@trajectorylabs) on online continual learning. Opening talk below; rest to come this week! 00:00 What is sovereign AI (and what it isn't) 01:24 Centralized vs. decentralized intelligence 02:54 Four reasons companies own their models: cost, speed, performance, destiny 04:22 "Not your weights, not your product" 05:32 The application companies are the newest neo labs 07:05 Step 1: Deciding what to own vs. rent 09:51 Step 2: Build the team (and don't shoehorn your platform team) 11:17 Step 3: Legibility – why your research has to be visible 12:33 Step 4: The technical roadmap 13:56 The stack: production vs. development 15:16 Opening Pandora's box – base models, harnesses, context
- Aug 12, 2026
Preview has raised $12M in funding to date, led by @sequoia with participation from @thegp and @farooqib. AI video is now part of how real productions get made. What professional work requires hasn't changed: scripts, shot lists, versions, reviews, deliveries, and a clear record of how every frame was made. Preview is the professional platform where AI video production runs. Producers, directors, and artists planning, generating, reviewing, and delivering together, from first idea to editor handover. Studios already run real work on Preview: commercial productions for Fortune 100 brands, and some of the first hybrid films with Oscar-winning talent, arriving on streaming platforms later this year. 3,000 studios are on the waitlist. We're letting the next ones in now.
- Sep 9, 2026
@Clay just raised a $115M Series D at a $7.1B valuation. Now, more than 17,000 teams build on Clay, including Anthropic, SpaceXAI, Google, OpenAI, Stripe, Visa, UPS — and 80% of the Forbes AI50. @nytimes just broke the news, but the story goes far beyond the raise. AI is unleashing the biggest wave of company creation in history. Clay’s goal is to be the engine they use to grow. Clay is a self-learning revenue engine that figures out the best GTM play for your company, then runs it. We started as the company with the best data about other companies. Then we became the infrastructure to run campaigns across email, ads, and landing pages. Now we’re building agents that learn from every campaign, predict the next best action, and get better each time they run. Software engineers use coding agents to write code. GTM engineers now use growth agents to autonomously grow their companies. In 2023, we introduced GTME as a new role for people creating revenue systems with data, automation, and AI. Two years later, thousands of GTMEs are growing the world's best companies. They are gathering in nearly 100 Clay Clubs around the world, from Bangalore to Boston and Lahore to Lisbon. That’s why we’re proud to launch a $1M scholarship fund, helping more people enter the profession. @Wellington_Mgmt led our Series D, with participation from @sequoia, @stepstonegroup, @a16z Perennial, @MeritechCapital, DST Global, @CapitalG, @BoxGroup, @boldstartvc, @BloombergBeta, and @EvolutionEquity. A gracious thank you goes out to our customers, community, partners, team, and every GTM engineer shaping this with us. We are going to unveil the future of Agentic GTM at SCULPT on October 8. Stay tuned to see how to use AI to grow every company. 🖤🩵❤️💛
- Aug 13, 2026
Intelligence and Experience are orthogonal vectors Terence Tao is perhaps the world’s smartest person, but drop him into an accounting firm or onto a construction site and on day one he’s not going to be very productive @trajectorylabs calls this The Experience Gap, and they have a way to close it @QuantumArjun explained how at our Sovereign AI event: 00:00 Introduction 00:12 Building the platform for continual learning 01:33 The experience gap: models have IQ but no tenure 02:52 Traceability → model spec → better models and harnesses 05:27 Four wishes for the agent ecosystem 06:34 Wish 1: Trace the whole tree — and capture the corrections 08:03 Wish 2: Evals from real traffic, graded in the real harness 09:26 Wish 3: Let the agents cook, and make tool responses informative 10:34 Wish 4: Get comfortable on open weights, experiment with routers 11:51 Why owning your intelligence shouldn't be consulted away 13:15 Demo: import a benchmark, train a model, deploy it 14:28 Q&A: What's the trainable object — weights, harness, or context? 16:08 Q&A: Continual learning without training on customer data 17:13 Q&A: Episodic memory and the hierarchy of feedback 19:37 Q&A: Where continual learning matters most
- Aug 27, 2026
Yay, in TIME100 AI w/ @Azaliamirh ! With AlphaChip, we started the field of AI for Chip Design. Last year, we founded Ricursive to take on all of chip design, from model to GDS (the final input to the fab). How we got here: (1/n) https://t.co/YJ7OQQbRcX
- Sep 23, 2026
Find the bottleneck. Swarm the bottleneck. Shatter the bottleneck. If every CEO that I coach focused like @alighodsi, I wouldn't have a job. His strategy: - Identify the main bottleneck - Focus the whole company on it (to an extreme) - If you overdo it, thats great. You did it right. @databricks put all their attention on one thing at a time, and in this story it was figuring out how to get the commercial engine humming. Complete obsession. Now at a $7B run rate. Link to full episode in the comments
- Aug 24, 2026
"Is it Bitter Lesson-pilled?" — the most used, and most misused, phrase in AI right now. @RichardSSutton sums it up on the latest Training Data with @kjaved_ , @sonyatweetybird, @Alfred_Lin "Don't be distracted by human knowledge, as AI traditionally has been many times. Instead, focus on learning methods that will scale with computation, like search and like learning."
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 377 interactions against 819K followers, an engagement rate of 0.046%. Posts are seen about 227K times each, and 0.166% of those impressions turn into an interaction. That is about 27.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 17:00 UTC, and Wednesday is the busiest day of the week. Of the 3 posts sampled, 67% carry an image or video and 33% link out. The account's strongest tracked post pulled 1.6K interactions, about 4.3x its own typical post. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
- What is Sequoia Capital's engagement rate on X?
- Sequoia Capital (@sequoia) has an engagement rate of 0.046%, based on the median interactions across 3 original posts from the last 30 days against 818,712 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.046%, Sequoia Capital sits above the 25th percentile of the 205,676 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 @sequoia have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @sequoia post?
- Most posts go out around 17:00 UTC, and Wednesday is its busiest day, at roughly 1.5 posts per day across the measured window.