Manos Koukoumidis ✓

@Koukoumidis

CEO @ https://t.co/FHoWf8TCnl

1 834Followers

98Following

260Posts total

2.2MViews on collected posts

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Manos Koukoumidis ✓@Koukoumidis11 Aug

@Koukoumidis 100% Agreed. A model that learns from your own production traffic is the first form of AI that behaves like an asset. It appreciates with use, while everything rented sits on the books as an expense. The software analogy is the strongest part of this: everyone writes 163 views · 5 likes · 1 reposts · 0 replies Open on X →

Manos Koukoumidis ✓@Koukoumidis11 Aug

My prediction: 🔮 In a year, renting all of your intelligence from a frontier lab, or hiring someone else to build your proprietary AI for you, will look as strange as outsourcing all of your proprietary software. The frontier labs will build extraordinary general intelligence. 4.6K views · 57 likes · 2 reposts · 3 replies Open on X →

Manos Koukoumidis ✓@Koukoumidis11 Aug

The AI strategic shift is not "build everything yourself." General frontier models will remain incredibly valuable. The rule for enterprise AI is: Consume what is generic. Build and own what differentiates you. Coding? Maybe rent it. General knowledge? Rent it. But 1.2M views · 168 likes · 3 reposts · 5 replies Open on X →

Manos Koukoumidis ✓@Koukoumidis11 Aug

AI ownership alone isn’t enough. The bigger opportunity is compounding intelligence. Every production interaction creates something valuable: Failures. Edge cases. Corrections. Expert feedback. New proprietary data. Today, most of that experience disappears while the 10.4K views · 65 likes · 2 reposts · 3 replies Open on X →

Manos Koukoumidis ✓@Koukoumidis11 Aug

Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they https 1M views · 470 likes · 168 reposts · 115 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

5 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง under 10K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.

ยอดดูมัธยฐาน10 352บัญชีนี้4 175ค่ามัธยฐานของ under 10K

การเข้าถึง, %564.45%บัญชีนี้250.82%ค่ามัธยฐานของ under 10K

การมีส่วนร่วม, %0.68%บัญชีนี้1.41%ค่ามัธยฐานของ under 10K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ under 10K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	10 352	4 175	2.48×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	5.6× audience	2.5× audience	2.25×
อัตราการมีส่วนร่วม	0.68%	1.41%	0.48×

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

1M11 Aug

10.4K

1.2M

4.6K

163

Last 5 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.10%11 Aug

0.68%

0.02%

1.35%

3.68%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.41%.

What the audience does

Likes51.9%765 in total

Reposts11.9%176 in total

Replies8.6%126 in total

Quotes14.6%215 in total

Bookmarks13.0%191 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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