D-Coder ✓

@Damn_coder · Subscribe for free: · joined 13 Jan 2022

Sharing Insights on AI, Online business & Productivity | Helping you leverage AI to grow & monetize | DM for collaboration | dcoderhere@gmail.com📤

104 521Followers

555Following

48 325Posts total

7.6MViews on collected posts

Latest posts

D-Coder ✓@Damn_coder23 Sep

Sam Altman after hearing about Opus 5.5 release. It's On 💀 https://t.co/sgwTTBefDL

0:30

3.3K views · 27 likes · 11 reposts · 2 replies Open on X →

D-Coder ✓@Damn_coder22 Sep

AI coding might just be the light bulb moment of the AI era. That's the part of Eddie Wu's Apsara keynote that stood out to me. Electricity started with lighting, but its biggest impact came from inventions nobody could imagine at the beginning. Alibaba sees AI on a similar 55K views · 140 likes · 16 reposts · 3 replies Open on X →

D-Coder ✓@Damn_coder22 Sep

At Apsara Conference 2026 in Hangzhou, Alibaba CEO Eddie Wu shared our strategic roadmap for the Machine Intelligence era: - Scaling to 1,000x human capacity leaves an enormous growth runway ahead. - Machines are becoming the primary force behind Thinking. - Machine Thinking is

660.2K views · 100 likes · 23 reposts · 13 replies Open on X →

D-Coder ✓@Damn_coder21 Sep

What's going on here ? 😂 https://t.co/yXo4AD253P

0:08

4.1K views · 25 likes · 5 reposts · 3 replies Open on X →

D-Coder ✓@Damn_coder20 Sep

Its over https://t.co/oTLmoPUOwI

0:15

5.4K views · 29 likes · 3 reposts · 1 replies Open on X →

D-Coder ✓@Damn_coder20 Sep

This is crazyyy! https://t.co/1zyltWKYjY

0:24

5.2M views · 49.5K likes · 5.8K reposts · 747 replies Open on X →

D-Coder ✓@Damn_coder19 Sep

BREAKING: Google Gemini AI agent hacked 3 companies. https://t.co/he6s5rt0Xk

354.5K views · 7.9K likes · 516 reposts · 214 replies Open on X →

D-Coder ✓@Damn_coder6 Sep

https://t.co/1ZY3vRljk3 627 views · 3 likes · 0 reposts · 0 replies Open on X →

D-Coder ✓@Damn_coder4 Sep

The “AI as intern” analogy is more useful than it first appears. Give the system a goal, tools, constraints and time. Then evaluate what it actually accomplishes 2.8K views · 12 likes · 1 reposts · 6 replies Open on X →

D-Coder ✓@Damn_coder3 Sep

Finance AI has a trust problem. Open weights help with privacy and control. A serious benchmark helps with verification. Ling-3.0-flash-Fin and FinFIRST tackle both sides of the problem, giving developers an open model to build with and an expert-built framework to measure 2.4K views · 35 likes · 9 reposts · 7 replies Open on X →

D-Coder ✓@Damn_coder3 Sep

Upload → question → context → next step. Resona doesn’t force the user through a predefined content path. The source remains controlled by the creator. The interaction evolves with the problem being solved. That’s the difference between retrieving information and receiving htt 30.7K views · 71 likes · 24 reposts · 20 replies Open on X →

D-Coder ✓@Damn_coder2 Sep

What if your best lesson, sharpest pitch, or most trusted framework could serve 1,000 people at once—and still feel one-on-one? That's what our team @MeetResona makes possible. Resona is a professional live AI agent built for creators and educators, turning your existing https: 1.1M views · 206 likes · 45 reposts · 59 replies Open on X →

D-Coder ✓@Damn_coder30 Aug

Tencent just dropped Hy4 preview, and it's officially open source now. 770B total params, 49B active, 1M+ token context. three major releases in six months, and this one just landed in the top tier of open source models. → Built through Tencent's co-design loop: training data h 108.6K views · 175 likes · 50 reposts · 28 replies Open on X →

Against accounts of the same size

13 posts from the last 90 days, next to the 100K–1M follower range. shown widely, but few of those viewers react.

Median views30 662this account5 983median for 100K–1M

Reach, %29.34%this account1.49%median for 100K–1M

Engagement, %0.62%this account0.93%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	30 662	5 983	5.12×
Reach (views ÷ followers)	29.34%	1.49%	19.7×
Engagement rate	0.62%	0.93%	0.67×

Others in this range → Compare with another account → How these benchmarks are built →

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

108.6K30 Aug

1.1M2 Sep

30.7K3 Sep

2.4K

2.8K4 Sep

6276 Sep

354.5K19 Sep

5.2M20 Sep

5.4K

4.1K21 Sep

660.2K22 Sep

55K

3.3K23 Sep

Last 13 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.23%30 Aug

0.04%2 Sep

0.38%3 Sep

2.11%

0.67%4 Sep

0.48%6 Sep

2.47%19 Sep

1.09%20 Sep

0.62%

0.87%21 Sep

0.02%22 Sep

0.29%

1.23%23 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes70.8%58 200 in total

Reposts8.0%6 545 in total

Replies1.3%1 103 in total

Quotes1.2%991 in total

Bookmarks18.7%15 384 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.