Quotesby GlyphStartups quotes
29 quotes from 15 people
- The solo founder is part of a list of maybe new archetypes that I think we’ll soon see a lot more of - and I’ll make both the pro and con case for each here: Solo founders Why: Solo founders can do 100x with AI, so they can ship a v1 when previously they couldn’t have before Why not: Maybe a team of cofounders still makes more progress.Unverified
- These days at a16z I’m mostly working on Speedrun , where we write the first check into brand new startups (up to $1M), and a lot of what we focus on is founder backgrounds/profiles. What are the right ones? How will the profiles change as we enter the age of AI?Unverified
- That’s a fair question at the dawn of the AI age when an app might take about as much time to build as editing a Youtube video. So this means average product retention will collapse, and the days of seeing >20% D30 will feel like a dream.
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- The obvious AI variant is to let your users opt in to training your model on their interactions with it. Many will resist that, but if some don't, the model they get to use will outperform the vanilla one used by the others.
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- Founders running successful AI companies should all take a cold hard look at exiting in the next 12-18 months, which may be a value maximizing moment for outcomes.
- The sum of random vectors is zero, but if you align your vectors, then you can go in a direction.
- But if you sell the work, every improvement in the model makes your service faster, cheaper, and harder to compete with.
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- The speed of advancement in AI demands a different approach to how we build, how we organize, and where we focus. Labs gives us room to break the mold and explore...
- In 2026, we’re going to see the emergence of a $0 to $1B club.
- AI projects, on the other hand, are taking far more capital, by far smaller teams, and turning that into historic growth rates for both new users and revenue.
- In the future, it is unlikely that many new core LLM companies will get started due to capital moats, barring some new breakthrough that somehow doesn’t spread quickly.
- We absolutely were taking on the right problem probably two to three years too early.
- In recent years, innovative AI products that didn’t build their own models were derided as low-tech “GPT wrappers.” Yet consumer products for the past few decades have been low-tech, with seemingly small moats and yet have generated huge value.
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- It was either going to be a startup or someone outside the current center of leadership and innovation in AI, which is mostly clustered around trillion-dollar companies in the US.
- One undeniable trend over the past, let's call it five years, has been the collapse of the Chinese startup sector.
- At Neeva, which converged onto a view of what search should be that was very similar to Perplexity, we were just two, three years early. And timing ends up being everything.
- Regulatory agencies are being green lit in real time to do the same to Artificial Intelligence.
- But at the end, products need to be having some magic to them and the magic comes from letting you be more lazy.
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- In fact, I feel the primary difference of Perplexity from other startups that have explicitly laid out that they’re taking on Google is that we never even tried to play Google at their own game.
- We would rather take a more dramatic position, that the best way to actually make a dent in the search space is to not try to do what Google does, but try to do something they don’t want to do.
- Every quote from Aravind Srinivas
- Because one of the things you can definitely guarantee is where there are no customers, there are also no competitors.
- The reason why I wouldn’t do it, and it goes back to why it’s so hard, is building a company and building Nvidia turned out to have been a million times harder than I expected it to be, any of us expected it to be.
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- Nonetheless, these early signs of success don’t change the reality that a lot of AI companies simply do not have product-market fit or a sustainable competitive advantage, and that the overall ebullience of the AI ecosystem is unsustainable.
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