Sudarshan

Home is where the heart lies. The heart lies in South Bangalore. Tweets personal.

[Amit Dubey @AmitHellboyz143]

He is isn't wrong
For context the catch btw 👇

[Aaron Levie @levie]

Just coming off of meetings with a couple dozen enterprise IT leaders discussing AI agents. Here are a few of the common themes that stand out:

* Lots of conversation that you have to solve an operating model challenge to get the full benefits of AI. Most companies have orgs that have always operated in siloes; but agents are most effectively when they are tied to a process, which often cuts across these siloes. So the big question is how do you start to deploy centrally managed agents that can work across organizational boundaries. Who manages these agents? How do they get deployed and adopted?

* Data fragmentation remains a major issue for most organizations. As long as data remains highly fragmented and not in standard formats, or data is not available to the right people and agents, enterprises are dealing with issues around being able to get answers from agents that are accurate or that conform to their business practices. This cuts across both systems with structured data (product metrics or revenue figures) and unstructured data (product roadmap or customer contracts).

* Clear sense that companies need to figure out what their core data moats are going to be in the future. If everyone has access to roughly the same superintelligence from the various models, then the context that you feed the models becomes proprietary value in the future. Capturing this data and getting it into a format that agents can use becomes very important.

* Everyone is trying to figure out the right metrics to manage to for AI adoption. General consensus that tokens are not the right metric per se, and people leaning more toward business outcomes (in an ideal world). For business outcomes (like more revenue or more shipped product), though, you have to get close to each individual workflow to figure out if it was successfully transformed with AI so it’s harder to manage top down.

* Growing view that enterprises are going to live in a multi-model world. Lots of interest (though early in actual adoption) in layers that can route workloads to different models (frontside or open weights) for cost or performance reasons. Also enterprises are trying to figure out what things do you give to the models directly vs. what do you separate as horizontal systems and context so you can swap any system in and out.

* Talent for driving AI adoption and implementation still remains a major issue and topic. Many view it as something you necessarily have to train for internally due to a shortage of talent being trained on this in the outside. As an aside, this feels like it remains a huge opportunity for those that get very good at deploying and management agents in an enterprise since most companies are looking for these skills.

* The best use-cases for AI tend to be those that fundamentally change the work being done instead of just replacing an existing process and doing it more efficiently. Companies are working through their versions of this individually because it’s different per industry, but this often remains both the most exciting and higher upside uses of AI.

Many more topics discussed recently, but overall it’s clear that there’s a ton of change going on with much more to come.

[mandira bedi @mandybedi]

What a journey. What a fight. Sweet victory, so well deserved ! Big congratulations to Team India! Women’s cricket has come SUCH a long way. ❤️🇮🇳🙌🏽

[Israeli Elegance @IDFMAGA]

Tomorrow, we rise and go again.

Thank you AB

[Firdose Moonda @FirdoseM]

This is why the global game won when India won. Maybe there will be now be a cultural shift and girls can have sporting dreams too. What happens after this moment matters.

As for us here in South Africa: our hearts are sore. But this is a resilient nation. We'll go again.

[Pallavi @pallavi_sreeram]

Indian Women’s Cricket team is WORLD FUCKING CHAMPIONS!

[Parsley @Parsleymael]

‘A succulent Chinese seal?’

[সিদ্ধার্থ (Siddhartha) @quinoa_biryani]

Jane Goodall died today. While smarter and more informed people will talk about her work, I want to share a snippet from her Wikipedia page - the two greatest paragraphs ever on Wikipedia. The first parts are amusing and interesting, but the last sentence elevates it to high art.

[Usain St. Leo Bolt @usainbolt]

Can’t Identify one good thing we good at.. #unimaginable

[Jessie Pegula @JPegula]

When you lost 4 points on serve in the 3rd but you lost the match

[Zealand @theoldzealand]

Sir Alex Ferguson is rolling over in his grave and he's still alive

[Sudarshan @soda_89]

Not sure about Anime, but i can recommend a clown show ...

[David de Gea @D_DeGea]

Recommend top tier animes I should watch 👀

[Satya Nadella @satyanadella]

🏏 25 days. 5 battles. Scores tied 2-2.

This isn’t just a game — it’s Test Cricket in all its timeless glory.

A series for the ages. Hats off to IND & ENG for the drama, grit, and greatness.

[Himanish Ganjoo @himganj153]

From "I only believe in Jassi Bhai" to "I'm always believe in myself". Siraj. What a guy.

[Mohammed Siraj @mdsirajofficial]

You asked. I delivered.

Really appreciate coming from you ❤️

[Sudarshan @soda_89]

@krtgrphr Interesting that the Devanagari board has transliterated the anglicized name

[Bharat Sundaresan @beastieboy07]

Washington Sundar averaging 44.86 with the bat & 27.87 with the ball after 12 Tests is elite all-rounder areas. With seven of those Tests coming in Australia & England and despite his actual role in the team still not quite defined #EngvInd

[Baahubali @BaahubaliMovie]

CEO & HR of Maahishmathi 🤗

[Classical Studies Memes @CSMFHT]

Damn they caught Achilles and Patroclus on the Coldplay jumbotron