Seema Amble ✓

@seema_amble · San Francisco, CA · joined 26 Jun 2011

partner @a16z // investing in b2b AI companies // strong opinions on 🍕

20 803Followers

2 923Following

3 251Posts total

358.8KViews on collected posts

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Seema Amble ✓@seema_amble8 Sep

what still hasn't changed: the best way to get a venture job is to start doing the job (e.g. have ideas for companies, theses, people; engage in a conversation even if over email), don't send a cold email just asking to chat! surprising how few people do this despite the number 2.7K views · 38 likes · 0 reposts · 4 replies Open on X →

Seema Amble ✓@seema_amble8 Sep

Good take! 9.7K views · 24 likes · 0 reposts · 1 replies Open on X →

Seema Amble ✓@seema_amble4 Sep

incumbents may have owned the record but the focused AI company can own the end to end job (and eventually the record too) https://t.co/TvnfeyTMVr

7.8K views · 64 likes · 2 reposts · 6 replies Open on X →

Seema Amble ✓@seema_amble3 Sep

@seema_amble a neutral data foundation is what a strong vertical harness needs underneath it 624 views · 6 likes · 0 reposts · 0 replies Open on X →

Seema Amble ✓@seema_amble3 Sep

The cash collection story from yesterday is a very good example of a customer first trying to build on top of a legacy system and then realizing it was missing key contextual data and the agent performed poorly - we keep hearing stories like this! 2.5K views · 18 likes · 1 reposts · 2 replies Open on X →

Seema Amble ✓@seema_amble3 Sep

substack article here: https://t.co/f8lkuCe0yS 2.1K views · 6 likes · 2 reposts · 1 replies Open on X →

Seema Amble ✓@seema_amble3 Sep

In the midst of the Claudeforce announcement and the debate around systems of record, focused AI native startups can win by leaning into their data asset, depth, learning loops, and ability to work across systems and parties https://t.co/cHPqJIiKjH 333.4K views · 335 likes · 31 reposts · 39 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

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

ยอดดูมัธยฐาน2 663บัญชีนี้993ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %12.80%บัญชีนี้3.63%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %0.83%บัญชีนี้1.92%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	2 663	993	2.68×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	12.80%	3.63%	3.53×
อัตราการมีส่วนร่วม	0.83%	1.92%	0.43×

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

333.4K3 Sep

2.1K

2.5K

624

7.8K4 Sep

9.7K8 Sep

2.7K

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.13%3 Sep

0.44%

0.83%

0.96%

0.94%4 Sep

0.26%8 Sep

1.58%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.92%.

What the audience does

Likes36.6%491 in total

Reposts2.7%36 in total

Replies4.0%53 in total

Quotes2.4%32 in total

Bookmarks54.4%729 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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เทียบกับบัญชีขนาดเดียวกัน

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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