Prasanna Vaidya

We @GydeAI are bullish on “Specific Intelligence”. Worldview intelligence is valuable, yes! But it can’t mean worldwide convergence of how we do things.

@nikesharora Interesting take. I keep thinking how captured knowledge can continuously improve enterprise systems and compound advantage.

@getprasannav Depends - if you want to share your model, or rent your IP.

I love @satyanadella his ability to put technology transformations in simple terms is par none. In this instance I think it's important to understand the distinction in consumer, horizontal multi-tenant AIaaS and Enterprise which tends to be deep and vertical. 1. Consumer - this is not new news, the consumer has always been part of the product. Be it search (Bing or Google), social media (think TikTok, Snap, and of course FB), even unassuming products like Maps have always retained the knowledge learnt from customers, customers suspecting or unsuspecting have always had the choice. Use the product and share your prompts, location or preferences and that will be used to build a better product. So why is that surprising if it happens in AI, the model complex will continue to use consumer usage to train fundamental multiple modalities. This is the biggest technological event of our lifetime :). 2. Horizontal AIaaS (AI capability that doesn't need to be too enterprise specific - can be tuned, but is a 80% common use case) - Think coding, legal, many current SaaS categories - most likely agentic development for prosumers. All of this behavior is being used to train the model complex to get better at all these. The large swath of small medium size businesses will be fertile training grounds for such applications. They cannot deal with isolated apps and custom deployments. 3. Enterprise deployments - this is where I am not sure the reverse information paradox applies. There is an existing model of isolated single tenant public cloud deployments, deployments where our data, code and connectivity are both isolated and in the hands of the enterprise. This is the deployment we have for our development from all frontier models. All our grounding data, prompts, internal tribal knowledge is sequestered. This is important because this is where enterprise IP will reside. It will be a large task to capture, collate, interpret this data. Equally complex to maintain, evolve and make effective an enterprise AI architecture. But that is what we all will need to sign up for. This is not a cloud vs on prem debate, they can both be equally secured. On prem is probably more unwieldy at the moment given the fast pace of development.

@federicodonaton This is a great take.

Media is power. You gotta own the narrative.

@gabriel1 AI diffusion over humanity is the play. 🤝

we're reached a point where AIs effect on GDP is significantly more bottlenecked on people understanding how to push it to it's limits than model intelligence at best, people outside tech and sf use it as a fancy information lookup tool or automated reviewing

@federicodonaton Profound. 🤝

@getprasannav you said it, one small AI win turns leaders into unpaid internal salespeople 🤟

I don't want to keep telling my leaders what AI can do. I want every leader to taste success with AI. Those were the words of a leader at a 10,000-person company. This framing completely changed how I think about enterprise AI adoption. Most leaders already know AI matters. They've read the headlines and experimented with the tools. The harder problem is helping them identify opportunities within their function, understand what data and systems need to be in place, and turn an idea into an initiative that delivers measurable value. AI adoption will be driven by the leaders who experience their first real win.

@parrysingh Build in public. :) Would love to connect.

Social media is the best place to build ideas and the worst place to battle egos.

@chamath @Benioff @satyanadella Specific, Bespoke, Personalized Intelligence is what every company needs to own. Worldview models are important but you cannot give away your success recipe in the form of token exhaust.

When we look back, Alex Karp may have initiated an important preference cascade around AI sovereignty. It’s worth noting what @Benioff and @satyanadella are both saying: Your knowledge, as a company, is your sovereignty. If you lose it to someone else (anyone else) you are hollowing your organization out. There are many ways to accidentally leak intelligence so you need partners and tools who can sign up for the complexity required to give it to you. See Benioff below and see Satya’s essay linked below.

Specific, Bespoke, Personalized Intelligence is what every company needs to own. Worldview models are important but you cannot give away your success recipe in the form of token exhaust.

@vaibhavbetter And even after fathoming, mulling, architecting, triangulating, one may still not be Fable class.. but better than the class one is today.. is that the point? :)

You are not Fable class, if you are just thinking and not fathoming, mulling, architecting, triangulating...

@marty_kausas AI can write LinkedIn content. But you may not like it. :)

until ai can write my linkedin posts we are nowhere close to agi and ai is nowhere near close enough to being able to write my content and i'm really trying (documenting context, style, etc)

@petropavliuk Looks slick! Nice setup.

Good morning! Have a great and productive start of the week 👍

@paraschopra Although I agree its not easy to define Taste & Judgement. For simplicity can we say Judgement is if something should be built. And if it is to be built, Taste is how it should be built. Does this resonate? Or not really?

Taste is compressed experience in a domain that cannot be articulated. It’s that residual of experience left over once all the easy to spot patterns are explained away.

I have started asking AI to create a car narration of a thread that I can listen. It gives me better talking points, suggests where to focus, where to pause more clearly instead of just asking to summarise a thread for an upcoming meeting. Have you observed this?

@emollick Totally. And the narrative that AI labs will use your data to improve the models and you wont get any benefit is doing further harm to AI Adoption.

Very few people know the amount of useful work that the current models can do in Code/Codex/etc. with the right setup This is not a "rah rah you are so early" post, this is a "AI companies are doing a really bad job explaining what their systems actually do in a clear way" post.

@paraschopra Majority of us dont care about benchmarks either. That results in under appreciation of the model improvements as very few people care if frontier models can write 5% better command line commands.

For most people and for most tasks, frontier models are an overkill. You don’t need Fable to find grammatical mistakes in your email. What ought to happen is everyone using ultra-cheap local or small models that call frontier models as a tool only when required.

@owenthcarey It intensifies the work like crazy..

AI burnout is real.

@SNeurgaonkar u r welcome

@getprasannav Damnnn, thank you so much 🚀❤️

The only gift Im accepting for my 31st birthday is Claude tokens 🫠

@Mr_Holland_ haha ...Monday blues..

@getprasannav Getting ready for Monday

What are you doing this weekend? Touching grass or building?

@nikunj Any learnings from the great ones you could share?

There’s nothing more humbling than outbound sales. Like any skill, it’s learnable. But man, when you see the really great ones do it, you can’t help but walk away a bit envious. Going to be even more important as time progresses!