Himanshu Kumar engagement report
@codewithimanshu - 70K followers on X
Measured over 7 original posts from a 30-day window, last computed on September 18, 2026.
Engagement
Early reading. We have captured 7 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 108 interactions against 70K followers, an engagement rate of 0.157%. Posts are seen about 6.3K times each, and 1.72% of those impressions turn into an interaction. That is about 9.03% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 09:00 UTC, and Wednesday is the busiest day of the week. Of the 7 posts sampled, 100% carry an image or video, 100% are part of a thread and 14% link out. The account's strongest tracked post pulled 244 interactions, about 2.3x its own typical post. Recurring topics include #capcutpc, #gpt6astra, #seedance25. Only 7 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 7 original posts from a 30-day window, last computed on September 18, 2026. Recurring tags: #capcutpc, #gpt6astra, #seedance25.
Where this sits in the catalog
At 0.157%, Himanshu Kumar sits above the 50th percentile of the 151,176 accounts in this comparison. That places it in the above the median band, which runs 0.126% to 0.6%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.003% |
| 25th percentile | 0.021% |
| 50th percentile | 0.126% |
| 75th percentile | 0.6% |
| 90th percentile | 2.29% |
| 99th percentile | 84.3% |
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 09:00 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 | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 14% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 100% 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.
- 14% 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 971 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 16, 20262.3x their median
A trader built a QUANT bot using Claude Fable 5. I saw it & asked Claude Fable 5 to do something wild: Analyze undervalued markets on Polymarket to find arbitrage opportunities and detect the wallets exploiting them so I can copy them. Turned $2K -> $11K overnight. It monitored over 1,000 wallets. I realized something fast: There are arbitrage bots I can't compete with without knowing how to program. But I can find them. And copy them. Fable 5 built me a monitoring terminal connected to a copytrading bot on Telegram. Not a script. Not even a bot. An AI agent that improves every time it finds a new wallet. It analyzes the behavior of each wallet: → How it operates → Its arbitrage patterns → The size of its positions → The exact moment it enters 70% hit rate right now. 7 wallets being copied out of 500+ monitored. The bot never stops. Never bets. It just follows the math and seeks profit. Most people are trying to predict the market. This system just identifies who's already winning and copies their exact moves. No guessing. No emotions. No trading experience needed. The entire edge is pattern recognition + execution speed. While traders debate which way BTC will move, this agent is already positioned in the same trades as wallets pulling $10K+ per day. You only need: → Claude → A device → 1 hour per day The system runs autonomous after setup: → Monitors 1,000+ wallets continuously → Detects arbitrage patterns in real-time → Copies winning positions automatically → Improves selection logic with each trade No manual trading. No chart reading. Just identifying proven edges and following them. 💡 I'm sharing the complete monitoring terminal + copytrading bot setup for free. 24 hours only. To get it: 1️⃣ Comment "Fable" 2️⃣ Like and Repost 3️⃣ Follow @codewithimanshu ( So i can DM you) I'll DM you everything.
- Sep 9, 2026
What if the biggest upgrade in AI video isn’t another generation model? What if it’s giving creators a better way to tell AI where everything is supposed to be? That’s the question I had looking at GPT-6 Astra’s spatial workflow. #GPT6Astra #CapCutPC https://t.co/nQcRoHcTpk
- Sep 9, 2026
9–5 isn’t the only way to make money anymore. 👀 People are earning up to $379/day online using simple copy-paste tasks. I broke down the entire method into a step-by-step guide. Normally, I’d charge $89 for it. But for the next 48 hours, you can get it completely FREE. 🔥 Want the guide? 1️⃣ Like this post 2️⃣ Comment “COPY” 3️⃣ Follow me @codewithimanshu 4️⃣ I’ll send it to your DM 📩 No payment. No signup fee. 48 hours only. ⏳
- Sep 14, 2026
A one-man trader can now build what used to require an entire hedge fund research team. Cost: ~$100/month in AI subscriptions. Five PhDs at a top quant desk? ~$270,000/month. And AI doesn't just replace the analysts. It changes how fast you can test ideas. The system looks like this: 1 research agents Read filings, transcripts, options flow, and on-chain data overnight. 50 different research personas can attack the same market from different angles. 2. Coding agent Give it one sentence: "Build a strategy around this signal." It creates the entry rules, exits, sizing, and risk limits. Then fixes its own code. 3. Backtest agent Takes the strategy and replays years of historical data in seconds. Weak ideas get eliminated before real money touches them. 4. Breaker agent The most important agent in the entire stack. It tries to destroy everything the other agents built. Higher fees. More slippage. Worst market conditions. Worst historical periods. If it survives the attack, the strategy gets another test. 5. Critic agent Reads your trading journal. Finds the mistakes you keep repeating. Then feeds those mistakes back into the system. That's the new quant workflow: Research → Build → Backtest → Attack → Improve → Repeat. No giant research floor. No army of analysts. No waiting weeks to test one idea. Just a network of AI agents working around the clock. And the biggest edge isn't that AI can predict markets. It's that AI can test thousands of ideas faster than a human team ever could. 💡 I'm sharing the complete AI QUANT workflow, including the exact agent structure, prompts, backtesting process, and breaker framework. Free for 24 hours. To get it: 1️⃣ Comment "AI" 2️⃣ Like + Repost 3️⃣ Follow @codewithimanshu I'll DM you the setup.
- Sep 12, 2026
Jacob Coxon's next interview on CBS News (ex Anthropic + OpenAI researcher who resigned). “We can't just unplug it because it could be copying itself over to other computers.” The explanation gets even more unsettling: An AI is just code. It could potentially transfer itself over the internet to another computer. You unplug it here, but it could still be running somewhere else. And maybe it makes 10,000 copies of itself, with all of them cooperating. No theory. No sci-fi movie. Just a former Anthropic + OpenAI researcher explaining a potential AI risk in a CBS News interview. The bigger question: What if shutting down one AI system doesn't actually mean shutting it down? From the CBS News YouTube channel. Full video link in the comments. If this was interesting, follow @codewithimanshu for more AI and tech content.
- Sep 17, 2026
Most people are using AI the hard way. These 11 AI tools can save you hours of work every single week 👇 1. https://t.co/sd0e7rZy7j — Solve complex problems 2. https://t.co/xYCSRd0uTJ — Remove backgrounds instantly 3. https://t.co/ULyXL6MW9u — Research anything 4. https://t.co/tB0xW4rNXu — Create music with AI 5. https://t.co/Wr0lMNBAUX — Design graphics 6. https://t.co/WtJa5AxVqh — Clone voices 7. NotebookLM — Turn information into perfect notes 8. https://t.co/YYHjK0zctU — Summarize YouTube videos 9. https://t.co/P0mdV9LAbO — Edit & generate videos 10. https://t.co/e2fQMY6bAB — Edit podcasts like text 11. https://t.co/92vXxyuD05 — Create AI avatar videos Save this list before you forget it. Follow me @codewithimanshufor more useful AI tools & resources.
- Sep 12, 2026
The gap between a product image and a real shopping experience just got a lot smaller. Turns out GPT-6 Astra + Dreamina Seedance 2.5 is an actual pipeline. The workflow is surprisingly simple: generate consistent product views from different angles in Dreamina, then send those images to GPT-6 Astra. Astra uses those references to create an interactive product detail page where customers can rotate and explore the product from every side. Instead of relying on a few flat images, this turns a product concept into a more immersive online showcase. And the best part? Dreamina’s competitive pricing makes it easier to generate multiple product views and experiment with different concepts before building the final experience. This feels like a new way to think about e-commerce visuals. #Dreamina #DreaminaPartner
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 108 interactions against 70K followers, an engagement rate of 0.157%. Posts are seen about 6.3K times each, and 1.72% of those impressions turn into an interaction. That is about 9.03% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 09:00 UTC, and Wednesday is the busiest day of the week. Of the 7 posts sampled, 100% carry an image or video, 100% are part of a thread and 14% link out. The account's strongest tracked post pulled 244 interactions, about 2.3x its own typical post. Recurring topics include #capcutpc, #gpt6astra, #seedance25. Only 7 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 Himanshu Kumar's engagement rate on X?
- Himanshu Kumar (@codewithimanshu) has an engagement rate of 0.157%, based on the median interactions across 7 original posts from the last 30 days against 69,572 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.157%, Himanshu Kumar sits above the 50th percentile of the 151,176 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 @codewithimanshu have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @codewithimanshu post?
- Most posts go out around 09:00 UTC, and Wednesday is its busiest day, at roughly 1.87 posts per day across the measured window.