Prasanna S ✓
@myprasanna · Chennai · joined 24 May 2009
Co-Founder @Rippling @Vorfluxai
46 949Followers
9 912Following
3 404Posts total
2.6MViews on collected posts
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NO. Market says: Hyperliquid revenues / on-chain trading market can grow substantially and hyperliquid has a small chance of making it the leader in the end state. It's odds weighted discounted cash flows.
3.2K views · 15 likes
· 0 reposts · 5 replies
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check out @vorfluxai -- connect your $200/mo codex account and it's practically free. Many have switched from Devin to Vorflux saving 20x or more.
7.3K views · 32 likes
· 2 reposts · 3 replies
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Devin is S-tier but insanely cost prohibitive.
Wish I could use it more.
22.7K views · 57 likes
· 0 reposts · 10 replies
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Live now with @rvivek -- join us and lmk your thoughts/Qs!
https://t.co/RnxFaNOvkq
3.5K views · 22 likes
· 1 reposts · 2 replies
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Building a Self-Driving Company, Episode 7 (Vivek Ravisankar, HackerRank) https://t.co/naCQrb7jsR
5.8K views · 61 likes
· 2 reposts · 6 replies
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@myprasanna @vorfluxai @Rippling Blown away by my experience. You guys have created something special.
Can’t wait for everyone to experience this. Excited to be along for the ride!
12K views · 53 likes
· 4 reposts · 2 replies
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Heres our full manifesto:
https://t.co/j78ZAzVx2x
32.2K views · 76 likes
· 3 reposts · 10 replies
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Tokenmaxx, not peoplemaxx. Sign up here:
https://t.co/8ezK9OnMAg
19.9K views · 66 likes
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9/ We run it with you
None of this ships as a box with a good-luck note taped to it. We profile where your engineering breaks, wire the harness to your stack, and run the first sessions with you. The models churn every few months; keeping current is our job, not yours.
Already
19.9K views · 44 likes
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8/ From code to shipped, while you sleep.
Three more between working code and a merge that goes live:
Testing. If the branch comes back to your laptop to check, what was the cloud for? The whole app comes up, a browser gets driven through the real flows, and you clear testing h
20.9K views · 49 likes
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7/ From prompt to code.
Three bottlenecks between your prompt and working code:
The machine. A real app is a dozen services at once; a blind cloud runs a script, not that. Vorflux stands up a raw machine like a new engineer's laptop and brings every process up live. Code that h
21.3K views · 61 likes
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6/ Backlogs die first
It was a pile of work waiting behind one person. Six bottlenecks sit between a prompt and a merged PR, and once they fall, the backlog becomes a choice: stop saying no, build them all, find out which ones matter.
Still hiring engineers before you've maxed
22.5K views · 61 likes
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5/ Profile the human time
Writing code became a commodity. Bottlenecks moved. Every model release, we profile where human time still goes and throw tokens at it until it's gone. Human time is the bottleneck. Tokens are not. https://t.co/KZJGoEEG62
24.3K views · 86 likes
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4/ The harness
That judgment needs somewhere to live. It lives in the harness: the one place your engineering principles run on every session, lossless and compounding.
We train no models, so it stays neutral. The labs ship their opinion. Nobody ships yours. https://t.co/lZldjI
27.7K views · 90 likes
· 2 reposts · 1 replies
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3/ The Great Flattening
Code stopped being the hard part this year. Follow that all the way out and the whole company changes shape: planning, design, review, execution all collapse toward the system that runs the work.
One person inside, or zero. Your job stops being the task
32.2K views · 88 likes
· 2 reposts · 1 replies
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2/ The models woke up.
The models got genuinely superhuman at code this year. GPT-5.6 Sol just topped the coding benchmarks; a different lab led the month before; no single model sweeps.
And they outgrew your laptop. The cloud you were offered is blind: it writes code on some h
45.3K views · 108 likes
· 5 reposts · 1 replies
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Launching @vorfluxai : The autopilot for software engineering. I was prev co-founder / CTO of @Rippling ($10B) and #1 coder in India. Vorflux is my high octane Ferrari.
Every AI coding tool still makes you fly the plane. That's the copilot model: you stay in the seat, approving
2.2M views · 3.2K likes
· 244 reposts · 630 replies
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5:25
Im Vergleich zu Konten gleicher Größe
18 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.
Medianaufrufe21 908dieses Konto924Median für 10K–100K
Reichweite, %46.66%dieses Konto3.62%Median für 10K–100K
Interaktion, %0.32%dieses Konto1.52%Median für 10K–100K
| Kennzahl | Dieses Konto | Median für 10K–100K | Verhältnis |
|---|---|---|---|
| Medianaufrufe pro Beitrag | 21 908 | 924 | 23.7× |
| Reichweite (Aufrufe ÷ Follower) | 46.66% | 3.62% | 12.9× |
| Interaktionsrate | 0.32% | 1.52% | 0.21× |
Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
27.7K14 Jul
24.3K
22.5K
21.3K
20.9K
19.9K
19.9K
32.2K
12K
5.8K9 Sep
3.5K
22.7K15 Sep
7.3K16 Sep
3.2K17 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.34%14 Jul
0.36%
0.29%
0.30%
0.25%
0.23%
0.36%
0.28%
0.49%
1.18%9 Sep
0.75%
0.30%15 Sep
0.50%16 Sep
0.63%17 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes48.7%4 589 in total
Reposts3.4%317 in total
Replies7.3%688 in total
Quotes2.1%201 in total
Bookmarks38.5%3 635 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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