Ashwin Rajan @asystemone

One of the stickiest moats in product, which I think will remain valid in the AI era, is "functional fixedness". Functional fixedness is the idea that users become entrenched into a specific pattern in using an interface. Once that pattern becomes crystallised, it becomes progressively harder to break - even when newer, simpler patterns to do the same things are surfaced to them. That's why what started as a workaround out of a sub-optimal UI pattern entrenches users into becoming their default use pattern, even after the core UI problem the workaround solved for is eliminated. Nowhere are we more creatures of habit than in our use of technology.

Perhaps the most persuasive evidence of an individual's ability to build is the quality of their professional portfolio of work. After all, in an time when anyone can build, being able to tell one's own professional story compellingly - and represent their body of work in the most articulate way possible - can be seen as the foundation for their ability to build.

#tokenminiming

Bill Gurley @bgurley

a week ago

This is what’s causing Anthropic to aggressively beg for govt protection (see below). Customers are finding cheaper alternatives. Keeping employees requires continuing ultra-rich secondaries ($$$) that are dependent on revenue growth. When you can’t win on the field go to DC.

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The benefits of GLP-1 drugs extend far beyond weight loss, especially in a country like India. Given India’s high burden of metabolic disease, wider adoption as these drugs become more affordable and go off patent could trigger a significant wave of usage and significant second order effects.

Payment failure is a telling indicator of potential churn in a number of verticals. In others, it is a rather poor indicator. Often it need to be combined with other signals for confidence. Conversational AI products solve for this intrinsically, in that their product usage provides an unprecedented wealth of context to qualify the payment failue signal. For instance, if I fail my payment on @GammaApp, (where I am being subsidised to retain month after month, and not really using the product for value work, unfortunately) payment failure can be a high quality signal of impending churn. On @ChatGPTapp on the other hand, a payment failure - seen in the context of all the high-value cases I use the product for, combined with my stickiness within them - means @sama needs to lose no sleep about his money going anywhere.

The smaller and tighter the agent harness, the more you gain trust, control and confidence for scalability. Said differently - failure modes and error rates compound at the jagged frontier, so aim to maintain the smoothest possible, most lossless frontier at the earliest stages of harness development - because it’s exactly those tiny early losses that add up - and constrain tightly around those initial boundary conditions while scaling from there.

We are at an inflection point in global society where the value of quality one-to-one human relationships is about to go exponential 🚀✨

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The human edge in the age of AI might just be the - very - difficult task of making things simple enough for humans to understand and work with.

'Create Note': Interesting feature experiment there from ChatGPT, but its persistent - above its instantiated - utility isn't obvious. Simply put, how this works over time, not just in the moment - isn't clear... where do my 'notes' go, how can I revisit or organize them, for example? 🤔

For as long as humans have known and used 'machines', the concept has come to mean a tool that produces standardised, predictable outputs. GenAI is the first machine we know of which works counter to that definition, and that is it's chief upside. Wrapping our heads around this shift in what a machine now means is the key psychological transformation required to harness GenAI at the individual and team level.

Subscription plans are massively subsidized. And by massively, I mean absurdly: Claude Max 20x: $200/month, with usage reportedly worth around $8,000 ChatGPT Pro 20x: $200/month, with usage reportedly worth around $14,000

SemiAnalysis @SemiAnalysis_

3 weeks ago

Recently, we purchased one of each Anthropic/OpenAI subscription plan and randomly ran long horizon coding tasks until we exhausted the weekly limit. It's widely believed that a $200/month plan maxes out at ~$2000/month worth of tokens (assuming API pricing). However, we found

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Listening to Bill Maris on this panel say that users will jump ship from ChatGPT and Claude to Gemini if the latter drops prices by 20 or 30% - because the products are "basically identical" - is like saying users will jump ship from the Mac to the PC if the latter drops prices. Try getting a high-intensity AI user to tell you Gemini is basically identical to Claude or ChatGPT 😄 The history of personal computing demonstrates that users are willing to pay progressively more, not less, for technologies that come to dominate their time and attention, by providing the most value in the most critical use cases of their life. If anything, dropping the price will only signal to users that Gemini is an inferior product, and drive them more to the leaders, or to challengers like Kimi, which is doing a fantastic job on productization. Instead, Gemini will benefit more from relentless focus in the next 18 months on amping up overall product quality, breadth & depth of UX, and so gain in pricing power, rather than try undercutting the leaders. That will only make the product go the way of the PC vis-a-vis the Mac.

The All-In Podcast @theallinpod

3 weeks ago

LIQUIDITY: Bill Maris on Broken VC Math and Google's Secret Weapon Against OpenAI and Anthropic (0:00) Bill Maris joins the Besties! (0:33) Four critical lessons from a career in technology (5:58) Building Google Ventures with data and machine learning (9:51) Why small VC

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LIQUIDITY: Bill Maris on Broken VC Math and Google's Secret Weapon Against OpenAI and Anthropic (0:00) Bill Maris joins the Besties! (0:33) Four critical lessons from a career in technology (5:58) Building Google Ventures with data and machine learning (9:51) Why small VC funds beat big ones on average (14:36) OpenAI's valuation problem and the coming AI price war (19:09) AI is at the "Atari Stage": what comes next? (25:23) VC's broken incentives and the future of deep tech Thanks to our partners for making this possible! EY (@EYnews) - Agentic AI is introducing a new investment discipline. As AI shifts to consumption-based models, EY connects spend to enterprise value. ey.com/en_us/insights… NYSE (@NYSE) - Thank you to our partner, the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE. nyse.com Plaud (@PLAUDAI) - Never miss a moment. Plaud, our official wearable AI note-taking partner at All-In Liquidity Summit, captured every insight. plaud.ai