Srinivas Rao

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[Srinivas Rao @UnmistakableCEO]

Skills were broken on https://t.co/ejjnhEiEaU for 5 days last week. During the outage Claude Code wrote this script, we edited it in a document editor it built, and uploaded it to YouTube through an uploader it built. None of that required the thing that was broken. @AnthropicAI

[Srinivas Rao @UnmistakableCEO]

"The organizations that eventually win with AI will not necessarily be the ones with access to the smartest models. They will be the ones that learn how to organize intelligence most effectively." @edans

[Srinivas Rao @UnmistakableCEO]

@gauravkheterpal Absolutely, the problem with flipping the 80/20 you have here is that you're asking a probabilistic model to perform deterministic operations. Recipe for failure.

[Annie Yang @annieqyang]

The most dangerous person in the age of AI is someone who was mediocre at coding but has taste, and can now build anything

[Srinivas Rao @UnmistakableCEO]

@sridharfyi When does your next batch start?

[Brett Calhoun @brettcalhounn]

The misconception is that you have to build by water to be successful.

As a VC, we want to fund a basket of opportunities. That includes the ambitious person uprooting their life to go to San Francisco to build, because they believe this is their best chance of success, and the person passionate about building at home who operates under different constraints.

One founder is in the comfort of their home and may be closer to customers, but is underrated, while the other is building in a new place with unlimited access, but life is taking a back seat to the business.

[Srinivas Rao @UnmistakableCEO]

I'm 48 years old, so I'm right on the edge. I had to drop out of CS at Berkeley and somehow built an entire AI-native OS with a coordination infrastructure. As far as vibe coding goes, what I've learned more than anything is not to just take the code and deploy it because that comes back to bite you almost every time, but to ask the AI questions about it. I've had to reason my way through this using nothing but first principles and asking the AI seemingly stupid questions, and somehow boiled my understanding of Python into something simple.

Import statements are like Chrome extensions. Defs are like the buttons. Input params are what you send the script. The function body transforms the input into the output. Some other stuff happens that talks to a server, checks schema, and causes output to go where it needs to go.

So most of the time I'll usually ask the AI - what does this do, and what does that do, what if we did it this way instead, which somehow is always simpler, more elegant, and more reliable. But my biggest takeaway is that if you understand the structure and data flow, then you can make the AI write the code to do whatever you want it to do.

And because of this i've been able to build things I never thought were possible.

[Srinivas Rao @UnmistakableCEO]

@Codie_Sanchez Much smarter than the "tokenmaxxking" nonsense

[Srinivas Rao @UnmistakableCEO]

@atShruti DM'd Yesterday and sent you our deck via Fedex, should have showed up yesterday. Would love to work with you guys given your investment thesis and values.

[Srinivas Rao @UnmistakableCEO]

@JakeFleshner https://t.co/d9OCboI4Z6

coordination infrastructure

[Srinivas Rao @UnmistakableCEO]

That and if that's a concern you've got a wrapper or derivative innovation that a model company can easily copy and make available. So it's really about leveraging the models in ways that model companies' aren't aware is possible and pushing the boundaries beyond what anyone thinks is possible.

[Paul Graham @paulg]

"What if the model companies do this?" is the new "What if Google does this?" I.e. the meaningless question investors ask that shows either that they're stupid or that they dislike you and are looking for ways to find fault.

[Srinivas Rao @UnmistakableCEO]

@JakeFleshner Coordination infrastructure.

https://t.co/d9OCboI4Z6

[Srinivas Rao @UnmistakableCEO]

@16vchq Autonomous execution of multi-step complex tasks. Let me know if you want to try it out i'll send you a link, literally describe what you want, add an item to a task list, press a button

happy to show you more.

[Srinivas Rao @UnmistakableCEO]

@sridharfyi https://t.co/d9OCboI4Z6

[Srinivas Rao @UnmistakableCEO]

One of the paradoxes of innovation is that every new technology solves one problem and creates others. This results in two main responses fueled by two key questions

What does this make possible that wasn't before?

What problems does this create that didnt exist before?

Derivative Innovation

Derivative innovators focus on the opportunities that a new technology enables or attempt to apply their predecessor's innovation to a different domain, what you can think of as the Uber for X strategy.

The first wave of the dot-com boom led to a rapid rise of business-to-consumer platforms, most of which enabled people to buy physical products, rent cars, and book flights without having to set foot in a retail store or talk to a travel agent.

But with the hype of any kind, common sense seems to get thrown out of the window. In retrospect, it seems obvious that shipping a 40-pound bag of dog food is only going to be profitable if you charge more than what it costs to ship and manufacture. And for most people, going to the pet store is clearly a better option.

Eventually, investors came to their senses and realized that counting page views and putting the words 'dot com' at the end of something wasn't a business model. This eventually led to the dot com crash, and most of the early dot com startups went out of business with very few exceptions. Most of these companies were derivative innovators; they built companies that the internet enabled them to build.

Mobile device proliferation led to the Uber for X approach to derivative innovation: Uber for haircuts, pet sitters, etc. The problem with this type of derivative innovation is layered. Not only is it not an innovation at all, but it doesn't account for context. The assumption baked into these types of innovations is that if it works for x, it will work for y. But they might have wildly different requirements to work at scale.

Many of the earliest AI startups realized that they could wrap a user-friendly interface around an API call to a language model provider. This realization gave birth to the first generation of AI startups: AI writing assistants, AI note takers, AI website designers. And they have all become known as the "wrapper" startups.

Derivative innovations initially reward the first movers, then commoditize them, and eventually make them obsolete. The innovators' graveyard is filled with failed attempts at derivative innovations.

Infrastructure Innovation

Infrastructure innovators focus on the problems that new technology creates. Amazon didn't outlive the dot-com bust because they were bigger, had more customers, or were better at selling books.
Amazon outlived the others because they eventually shifted their focus to the problems that the internet created: the backbone required to make the internet functional at scale.

Google thrived while the rest of the search engines died because they focused on the problems the internet created and continues to create to this day: the exponential increase in the volume of information on the internet.

AI startups that outlive the current wave of hype will be the ones that solve the problems that AI creates and will continue to create.

But this is where almost nobody looks because it isn't glamorous. And often unglamorous and essential are birds of a feather.

An instagram post with a toilet that lets you flush a bowling ball, while simultaneously washing, wiping and your rear end is going to get a lot more views the pipes with shit flowing through it. But the pipes and your questionable diet solve the problem that this super toilet creates.

The greatest opportunities in AI aren't going to come from what it makes possible, but from the problems that it has created and will continue to create for the foreseeable future.

Don't ask what AI can do. Ask yourself, what problems is AI creating that nobody is solving or paying attention to? And given that nobody is paying attention to them, you likely won't read about them in articles or find people talking about them on Twitter.

This requires you to discard your assumptions, disregard hype, question conventional wisdom, and even possibly dismiss the industry experts. Look where nobody else is looking. Better to be the person who starts a trend instead of the person who follows one.

[Srinivas Rao @UnmistakableCEO]

Infrastructure innovators  focus on the problems that new technology creates.  

Amazon didn't outlive the dot com bust because they were bigger, had more customers or were better at selling books. Amazon outlived the others is because they eventually shifted their focus to the problems that the internet created: the backbone required to make the internet functional at scale

Google thrived while the rest of the search engines died because they focused on the problems the internet created and continues to create to this day:  the exponential increase in the volume of information on the internet.

AI Startups that outlive the current wave of hype will be the ones that solve the problems that AI creates and will continue create.

[Srinivas Rao @UnmistakableCEO]

The greatest opportunities in AI aren't going to come from what it makes possible, but from the problems that it has created and will continue to create for the foreseeable future. And nobody looks here because its not as sexy as an instagram demo with the vibe coder who has 6 monitors and weird nodes that look like some futuristic crap.

What nobody else is building- the equivalent of AI's sewage infrastructure-pipes that make the shit flush down the toilet instead of back up into the chat window.

[Srinivas Rao @UnmistakableCEO]

@jointhebridge https://t.co/d9OCboI4Z6

[Srinivas Rao @UnmistakableCEO]

The greatest opportunities in AI aren't going to come from what it makes possible, but from the problems that it has created and will continue to create for the foreseeable future.

Don't ask what AI can do. Ask yourself, what problems is AI creating that nobody is solving or paying attention to? And given that nobody is paying attention to them, you likely won't read about them in articles or find people talking about them on Twitter.

This requires you to discard your assumptions, disregard hype, question conventional wisdom, and even possibly dismiss the industry experts. Look where nobody else is looking. Better to be the person who starts a trend instead of the person who follows one that someone else has started.

[Srinivas Rao @UnmistakableCEO]

@415venture Coordination infrastructure for autonomous AI that lets you run 1000's of tasks without ever talking to a chatbot. Builds tools, websites, api integrations etc.

https://t.co/d9OCboI4Z6