Dr. Debashis Dutta

@debashis_dutta · الرياض, المملكة العربية السعود · joined 26 Nov 2009

Board & Executive Advisor | AI, GenAI & Risk Analytics Governance | Multi-Cloud AI | Data Governance (DAMA-CDMP) | Regulatory Assurance: IFRS 9 & Model Risk I

13 538Followers

14 596Following

64 312Posts total

16.3KViews on collected posts

Against accounts of the same size

4 posts from the last 90 days, next to the 10K–100K follower range. reaches fewer people than peers, but engages them much harder.

Median views116this account2 392median for 10K–100K

Reach, %0.85%this account7.18%median for 10K–100K

Engagement, %5.24%this account1.50%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	116	2 392	0.05×
Reach (views ÷ followers)	0.85%	7.18%	0.12×
Engagement rate	5.24%	1.50%	3.49×

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

15.8K16 Mar

14411 Jul

13413 Jul

9514 Jul

9715 Jul

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

0.04%16 Mar

4.86%11 Jul

5.22%13 Jul

5.26%14 Jul

7.22%15 Jul

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.50%.

What the audience does

Likes41.7%15 in total

Reposts25.0%9 in total

Replies19.4%7 in total

Quotes5.6%2 in total

Bookmarks8.3%3 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.

Latest posts

NEW PAPER: Can AI agents diagnose failure by learning what success looks like? As enterprise AI agents execute longer and more complex workflows, one problem becomes critical: When an agent fails, where did its trajectory begin to go wrong? https://t.co/3ybsDoX7zq https://t.co/Z 97 views · 3 likes · 2 reposts · 2 replies 15 Jul 2026 The next major #financial #AI #incident may not begin with a failed model. It may begin with an #AI #agent executing an authorized-looking action—before anyone has time to stop it. Link in the comment 👇👇 https://t.co/qjZqtWgRzj 95 views · 2 likes · 1 reposts · 1 replies 14 Jul 2026 AI risk has moved from the technology agenda to the board agenda. A major study from the MIT AI Risk Initiative and MIT FutureTech, involving 272 international experts across 37 countries, delivers a message that leaders cannot ignore. 👇link in comment 👇 https://t.co/F9p4VA6N3o 134 views · 3 likes · 1 reposts · 2 replies 13 Jul 2026 #Tokenization is moving from experimentation to financial infrastructure. A new #IMF Note, “The ##Rise of Tokenization: Deciphering New Trends in Payments and Asset Tokenization,” makes one thing clear: Tokenization is not just about putting ##assets on #blockchain. 👇👇 https:// 144 views · 2 likes · 4 reposts · 1 replies 11 Jul 2026 In the age of AI, innovation gets attention — but governance builds trust. I’m pleased to share that I have earned the @PECB ISO/IEC 42001 Senior Lead Implementer certification. Over the years, I have pursued advanced AI and machine learning certifications across leading https 15.8K views · 5 likes · 1 reposts · 1 replies 16 Mar 2026