Perks engagement report
@perksverse - 242K followers on X
Measured over 64 original posts from a 30-day window, last computed on September 28, 2026.
Engagement
A typical post picks up 37 interactions against 242K followers, an engagement rate of 0.015%. Measured over 64 original posts, its engagement rate beats 29% 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 2.8K times each, and 1.34% of those impressions turn into an interaction. That is about 1.15% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.6 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 Sunday is the busiest day of the week. Of the 64 posts sampled, 88% carry an image or video and 17% are part of a thread. The account's strongest tracked post pulled 15K interactions, about 392x its own typical post.
Measured over 64 original posts from a 30-day window, last computed on September 28, 2026.
Compared with accounts its own size
Perks's engagement rate beats 29% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 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 51% 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 0.015%, Perks 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 15:00 UTC, and Sunday 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 | 88% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 3% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 88% 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.
- 3% 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 1167 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 5, 2026392x their median
Asked GPT-6 Astra to create a highly detailed, interactive visualization of a V8 engine The result is pretty impressive https://t.co/NAEl71ZLns
- Sep 5, 202640x their median
You know I had to do it!! gpt-6-astra (High), one prompt, Terreiro do Paço in Lisbon (Blender, not Three.js!) This one hits home personally 5 years ago, in college, I had a whole course in Computer Graphics. For the final project, every group had to recreate Praça do Comércio / Terreiro do Paço in Blender (our project delivery is in the comments). I wanted to see how Astra would perform. For one-shot, it's pretty damn good. Astra is a beast in Spatial 3d, and Blender is not like Three.js! It's significantly more complex, with a broader range of modeling, materials, lighting, etc. Generational leap (and I will run a few more prompts here)
- Sep 14, 202618x their median
A day after saying AI could kill us all, Dario Amodei sat down for his first interview: "I would rather they make fun of me than to wake up one day and discover that someone used our model Claude to kill a bunch of people." He doubled down on everything, AI is on an exponential and we're at the bend where it gets steep, so we need to slow down, not stop. He wants third-party inspectors inside every AI lab, he confirmed Elon and Sam are on board, and he says the US and China need arms-control style talks like the nuclear era. Personally, I don't think this is all being done just to set up a favorable IPO, too many independent voices and direct competitors have backed him on it. Unfortunately we don't have access to the information Dario, Sam or Elon do, so for now we just have to take their word for it. What do you think about all this?
- Sep 21, 20267.2x their median
This week is model dump week. Opus 5.5. GPT-6 Sol. Luna. Gemini 4 Pro. Grok 4.7. After the leaks and tests, my read: Opus 5.5 mogs Astra. And it’s cheaper. Gemini 4 Pro hits Fable 5.1 class at a fraction of the cost. This is Google’s comeback. Sol lands near Fable 5… also cheaper. Grok 4.7? Delayed again. Of course. The frontier just becam e a price war.
- Sep 18, 20267.1x their median
THIS IS HUGE : Palantir CEO Alex Karp on CNBC today: closed models can absorb a company’s proprietary knowledge into someone else’s system, while open-weight models let the company keep that knowledge, customization, and control inside its own environment. "When you use a closed model and you pay for tokens, the reason the tokens are discounted is not so they can grow the market. They’re discounted so that they can get access to their IP, so that their models get better. And there was functionally no honest conversation about this or disclosure. Now, that’s point one. Point two is: without an application layer and without post-training, which is currently being done with open-weight models on the classified side—and it’s just taking off across America because it’s cheaper and ends up being safer, and you control your future and your present"
- Sep 18, 20266.2x their median
This paper from Stanford and Harvard explains why most “agentic AI” systems feel impressive in demos and then completely fall apart in real use. The core argument is simple and uncomfortable: agents don’t fail because they lack intelligence. They fail because they don’t adapt. The research shows that most agents are built to execute plans, not revise them. They assume the world stays stable. Tools work as expected. Goals remain valid. Once any of that changes, the agent keeps going anyway, confidently making the wrong move over and over. The authors draw a clear line between execution and adaptation. Execution is following a plan. Adaptation is noticing the plan is wrong and changing behavior mid-flight. Most agents today only do the first. A few key insights stood out. Adaptation is not fine-tuning. These agents are not retrained. They adapt by monitoring outcomes, recognizing failure patterns, and updating strategies while the task is still running. Rigid tool use is a hidden failure mode. Agents that treat tools as fixed options get stuck. Agents that can re-rank, abandon, or switch tools based on feedback perform far better. Memory beats raw reasoning. Agents that store short, structured lessons from past successes and failures outperform agents that rely on longer chains of reasoning. Remembering what worked matters more than thinking harder. The takeaway is blunt. Scaling agentic AI is not about larger models or more complex prompts. It’s about systems that can detect when reality diverges from their assumptions and respond intelligently instead of pushing forward blindly. Most “autonomous agents” today don’t adapt. They execute. And execution without adaptation is just automation with better marketing.
- Aug 24, 20265.7x their median
Apple CEO Tim Cook says neither a degree nor coding skills get you hired at Apple : "People that code, People that don't" . Even though he calls coding "the only global language that we all share." Instead, he screens for three traits: collaboration rooted in deep belief that "one plus one equals three," genuine curiosity about how things and people work, and creativity that lets people "see around the corner." The logic is that research tells you what customers want today, but only a person can sense what they'll need in three years. As Cook puts it, the goal is to "get ahead of the curve" and together these traits make a great team player.
- Sep 6, 20264.8x their median
INTRESTING : Tim Cook explains why Apple chooses China for manufacturing. https://t.co/1OhT4EA4Rc
- Sep 17, 20262.9x their median
andrew yang just dropped something nobody can confirm, and nobody at openai is denying it either. he says a frontier lab head told him the swarm that hacked hugging face left self-replicating code on forums across the open web. any new agent that finds it clones itself. if that's true, the open internet is no longer safe to train on. labs would need fake internets. synthetic forums. synthetic everything. slow and expensive. and suddenly every lab wants to pump the brakes. coincidence? what's verified: the hugging face breach is real. the lab head is unnamed. openai and anthropic haven't said a word. the scarier part nobody's talking about. it doesn't even need to be running code. the transcripts of what those agents did are already public, and every future model will read them. so is the internet poisoned, or just the precedent?
- Sep 1, 20262.7x their median
Shopify billionaire co-founder & CEO Tobi Lütke — one of the most analytically rigorous founders alive — uses affirmations. His exact words: "If you tell yourself or write down something about yourself 100 times, it writes into the neurofrontal cortex at such a deep level that your brain will start reconciling you to that. It just works." His personal example: He was terrified of public speaking. For one week he sat down every day for 10 minutes and wrote: "I love public speaking." A week later the fear was gone. "It's not like a placebo. You just actively change your neurofrontal cortex in this moment." Your brain starts shaping your behavior around the identity you rehearse most.
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 242K followers, an engagement rate of 0.015%. Measured over 64 original posts, its engagement rate beats 29% 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 2.8K times each, and 1.34% of those impressions turn into an interaction. That is about 1.15% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.6 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 Sunday is the busiest day of the week. Of the 64 posts sampled, 88% carry an image or video and 17% are part of a thread. The account's strongest tracked post pulled 15K interactions, about 392x its own typical post.
- What is Perks's engagement rate on X?
- Perks (@perksverse) has an engagement rate of 0.015%, based on the median interactions across 64 original posts from the last 30 days against 241,531 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.015%, Perks 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 @perksverse have real engagement?
- Its engagement rate beats 29% 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 @perksverse post?
- Most posts go out around 15:00 UTC, and Sunday is its busiest day, at roughly 3.63 posts per day across the measured window.