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Prukalpa ✨

@prukalpa · San Francisco · joined 25 Sep 2009

Cofounder @AtlanHQ, Context Layer for AI ✨prev founded @Social_Cops, built India’s National Data Platform, @wef tech pioneer

39 280Followers
4 076Following
8 438Posts total
168.4KViews on collected posts

โพสต์ล่าสุด

This is one of the best articulated guides to understanding SF that I’ve ever read! Few personal notes -> 1/ there is no one who can be too weird in SF — you can be whoever you want to be 2/ there’s plenty of non tech people and the most kind humans I’ve found have been 17.2K views · 46 likes · 1 reposts · 0 replies Open on X →
For the longest time founders didn’t respond to this kind of painful random online feedback and only “defended” it privately. This response is fantastic to see to set the record straight from his perspective — glad to see @tobi do this 3.1K views · 11 likes · 0 reposts · 0 replies Open on X →
Every AI agent looks smart, until it encounters the exception no one wrote down. Because so much of how a business actually works lives in people’s heads, Slack threads, and “you just have to know” rules. What’s one rule at your company that’s obvious to your team, but 1.6K views · 11 likes · 1 reposts · 3 replies Open on X →
Miro got to 600m ARR, raised 500m and have 435m in cash. The company had raised 75m prior to their last round of a Series C that was 400m at an insane valuation. They also seem to have burnt very little of the 400m they raised (in total) — even if they had invested to drive 8.1K views · 26 likes · 1 reposts · 2 replies Open on X →
@nikunj has the amazing ability of articulating complex and nuanced matters in simple language that speaks to you. Please read. 5.2K views · 22 likes · 0 reposts · 1 replies Open on X →
If Miro had raised $50M total, last at a $20B valuation, and sold for $1.79B in equity value, would we tell a different story about the outcome? They're profitable and still have substantial cash ($435M). The capital wasn’t simply lit on fire. I don’t love overcapitalizing 75.9K views · 184 likes · 7 reposts · 9 replies Open on X →
https://t.co/pPmfsH024O 49.7K views · 257 likes · 8 reposts · 13 replies Open on X →
Five months ago we started asking some of the smartest people in AI one question: what is a context layer? We expected answers. We got more questions. Where does a semantic layer end and a context layer begin. How much do ontologies and knowledge graphs actually matter. What ht
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7.6K views · 48 likes · 9 reposts · 11 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

8 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.

ยอดดูมัธยฐาน7 828บัญชีนี้1 033ค่ามัธยฐานของ 10K–100K
การเข้าถึง, %19.93%บัญชีนี้3.60%ค่ามัธยฐานของ 10K–100K
การมีส่วนร่วม, %0.40%บัญชีนี้1.69%ค่ามัธยฐานของ 10K–100K
ตัวชี้วัดบัญชีนี้ค่ามัธยฐานของ 10K–100Kอัตราส่วน
ยอดดูมัธยฐานต่อโพสต์7 8281 0337.58×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)19.93%3.60%5.54×
อัตราการมีส่วนร่วม0.40%1.69%0.24×

บัญชีอื่นในช่วงนี้ →   เปรียบเทียบกับบัญชีอื่น →   ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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

7.6K10 Sep
49.7K
75.9K
5.2K11 Sep
8.1K
1.6K
3.1K
17.2K12 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.90%10 Sep
0.56%
0.26%
0.44%11 Sep
0.36%
0.91%
0.36%
0.27%12 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.69%.

What the audience does

Likes73.9%605 in total
Reposts3.3%27 in total
Replies4.8%39 in total
Bookmarks18.1%148 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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