Prasad Mani

Cloud, data & AI engineering for financial services & enterprises. From strategy to shipped solutions. Practical over hype. Views my own. @northeastern @PwCUS

[Prasad Mani @iampmani]

Everyone is talking about FDEs these days. Is it because it is popular, or is there real value?

I wrote down my view from working in both industry and consulting.

Short answer: both. 👇 https://t.co/JQSKlBtG5T

[Prasad Mani @iampmani]

@tanayj @dok2001 This is better than limit per month. Even better would be outcome based.

[Prasad Mani @iampmani]

@Cointelegraph @UBS spot on. Tokenization fixes the plumbing , not a market creator.

[Prasad Mani @iampmani]

@systemdesignone order matters as well

[Prasad Mani @iampmani]

@alexxubyte Only Microsoft is tagged for enterprise workflows. But, LangGraph and few of others look enterprise ready too. What options would you add for enterprises? or am I missing something that sets Microsoft apart.

[Prasad Mani @iampmani]

@gdb Scale is the storyline here - discover, validate and prep. The harder part for enterprises comes after that : regression testing, change controls, the team that have to absorb these patches. Doing this continuously into SDLC is what makes this stick.

[Amjad Masad @amasad]

AI agents running on employee endpoints are becoming a systemic security risk for enterprises & governments.

Some are responding by restricting tools like Claude Code, as Goldman Sachs reportedly has.

In this security advisory, we outline the risks and recommend a path forward.

[Prasad Mani @iampmani]

What if we have a new product wherein the low rates were transferable at a premium?

Ex: Seller has a 2.75% loan. Buyer takes it over at, say, 4.25%. The extra 1.5% pays investors and servicers for keeping the loan alive.

Buyer still beats 7%. Seller can finally move.

Hard part is the equity gap, which can be covered by a bridge loan provision.

[Prasad Mani @iampmani]

@unusual_whales Concerning !

[Aaron Levie @levie]

It’s almost incomprehensible how wide the distance is between someone who’s working at the frontier with AI and basically everyone else right now.

The crazy thing is these lines are not converging, but only growing farther apart. If the curve of AI progress had leveled off, it would certainly have given most people and companies time to catch up or implement their workflows in a standardized way. The technology would have neutralized competitive advantage because everyone would be using it the same way.

But what’s happened is the opposite. The curve of AI progress is basically going vertical right now, which means if you had codified your processes 3-6 months ago you’re likely already behind again. Now imagine most companies that kicked into gear a year ago and thought that they were done. Even further behind now.

I’ve never seen a technology in my life and career that improves at this rate, which consequently means you need to upgrade your expectations at a similar rate. Our brains weren’t wired for this, and our organizational change management processes certainly weren’t either.

With any form of recursive self improvement, things just get wilder. It’s a time when you will need to be constantly reevaluating the things that didn’t work just a couple months ago to see if they now can be solved. AI native companies certainly have a strong advantage due to this right now, so now it comes down to can the bigger companies keep up. Wild times.

[Prasad Mani @iampmani]

@sytaylor @Muse Muse answers like a task agent - short, cited, not many follow-up questions. The real takeaway is, experience (response) design should match the job to be done.

[Prasad Mani @iampmani]

@a16z business data is the context, using it well gives you the edge over others.

[Prasad Mani @iampmani]

@bhushansethi1 @HKane Bittersweet for spurs fans. Years of carrying spurs, and glad the move worked out for him achieve greatness. Well deserved !

[Prasad Mani @iampmani]

I help financial services firms and enterprises turn cloud, data and AI into systems that actually ship. Here to share what works in the field: architecture & design, delivery lessons, and where AI is (and isn't) paying off. Follow along.