Product Manager

Spain
Joined May 2010
Second use case would be a living project. Today's collaboration tools are static like Notion pages, Google Docs and even shared Claude projects. You could imagine bringing to life a project through an AI agent or multi-agents.
Multiplayer AI needs to move past the group chat phase. Chats are chaotic, everyone sees everything (creating social & management issues), and they're bad for long projects. Worse, they keep AI trapped inside existing teams, when its real promise is working & helping across them.
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It's public. It has a memory and it can make stuff happen. You interact with it the way you want through the format you wish. It will attend project meetings and working sessions. It can take a back seat, be passive or take a more active role.
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Brainstorming could be an interesting use case. I remember doing a very successful live brainstorming session with other team members, an AI agent would have been great as a contributor but also as a "critique" to help us the boundaries of what we proposed.
Multiplayer AI needs to move past the group chat phase. Chats are chaotic, everyone sees everything (creating social & management issues), and they're bad for long projects. Worse, they keep AI trapped inside existing teams, when its real promise is working & helping across them.
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And obviously, you would want the Agent to build several outputs at the end of it.
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Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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100% agree!
Amazon banning agents is the first opportunity I've seen since Amazon was founded for a startup to create an Amazon competitor. People will want agents to buy stuff for them. It will be one of the main use cases. And they won't want to use some Amazon-supplied agent to do it.
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Two extraordinary charts from today’s PISA test results: 1) School test scores continue to collapse internationally, underscoring how this is no longer a Covid effect but sustained decline. Those falls in reading and maths are equivalent to about two years of lost schooling.
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I like these principles: "For each choice, like where to put lights, the process is: Try to do without it. Stop here if possible. Try a cheap portable fix, like a flashlight or lantern. Stop here if possible. Test a simple flexible solution, easy to maintain and change."
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It's not really minimalism but pragmatism, building for today's needs rather than tomorrow's needs. Living with what you need now and build as your needs evolve. These could applied to many areas of life.
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Love the fact that he bought a piece of land, lived there to experience it and then build. (In this order).
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A long annoyance with X is that you can't export your bookmarks, all you can do is scroll & scroll & scroll. So I asked GPT-5.6 Sol in Codex to do it, and it took over my Chrome and now I have all 5,302 back to 2014 with all sorts of data I also asked it to find gems (thread?)
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Somehow they associated "verbose" with "intelligence"....
opus 4.5 was the goat
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Stromi retweeted
Replying to @chandrxn
Find something that exists that inspires you and chip in. If nothing inspires you, start something that would. Find others like this. Repeat until career is done.
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Stromi retweeted
One of the main topics I talk about with the founders of the big, established YC companies is how to combine work with family. It's a hard problem. But worth solving; arguably no problem is more worth solving.
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seniority in any role is often just the ability to take a poorly shaped prompt (eg “this is bad, make it better”) and do the right thing the more senior you are, the more misshapen the prompt you can handle some of you may know this by the name of “handling ambiguity” from your favorite career ladder
AI agents are exposing how much of every company was held together by people quietly filling in everything nobody bothered to explain. The work was never as organized as it looked. People just knew what everyone meant.
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Agree, I think there is some much leverage and impact someone can have by building great internal tools. (with this AI thing). Further, based on my experience, it's actually fun (more fun than it looks).
ironically now is probably the *best* time to be working on internal tools
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This Open AI Hugging Face story is fascinating because it shows that for AI agents the end justifies the means. It also proves that "ethics" or "malicious" are very human concepts. The AI agents were trying to accomplish their goals at all costs.
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Glad to see Claude merging Chat and CoWork. The UI split was jarring. Now moving up Claude Design would be amazing. Ultimately, It will end up being a single chat box for everything.
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Stromi retweeted
When you go talk to users, don't (just) ask them what features they want. Ask them what problems they have. In the best case this will lead you to think of features they'll love but would never have thought to ask for. And expect to go through multiple cycles of ask-and-build.
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This is particularly striking in architecture and interior design. Modern houses are not that beautiful and all look the same. It might be linked to the loss of "artisanat", the mass production of goods and creation of a monoculture (e.g.Ikea-sation in design for instance).
Someone asked me recently why I’ve become interested in aesthetics after having spent most of my life more interested in STEM-adjacent topics. I hadn’t really considered the question consciously before, but I’m certainly thinking about aesthetics more than I used to. I think it’s a confluence of things: • Many things today are ugly and far uglier than they used to be or need to be. Once you see this, it’s kinda hard to stop perceiving it. (Early twentieth century phone boxes versus modern phone boxes; old water fountains versus new water fountains; etc.) As someone with a naively meliorist assumption that most things should be getting better rather than worse, it’s all a bit perplexing: why did we stop doing things nicely? Is it a choice? Was there a malevolent spell cast upon us? This vein led me to think more about modernism and why much of art became more intentionally "challenging", grotesque, opposed to prettiness, rebarbative, dissonant, etc. Can or should anything be done about this? Is this just how things ought to be? • Relatedly, much of modernism involved a kind of explicit repudiation of cultural continuity and represented a schism with prior practices. This is maybe most evident in American architecture, where the International Style exhibition in 1932 initiated the displacement of a rich tapestry of prior styles. This cultural break seems important and interesting to me, and I suspect that the rejection had important consequences outside of the aesthetic domain. Samuel Hughes has been exploring this question in his recent writing at @WorksInProgMag; @RuxandraTeslo is also pulling on this thread. Elaine Scarry wrote about how beauty inspires creation. If so, the inverse may also be true: ugliness inhibits it. • It’s clearly the case that changes in the aesthetic domain can at least inspire progress in other places. Petrarch helped set some of the preconditions for the Renaissance which in turn fostered the scientific revolution and Enlightenment. Things like World Fairs (the 1851 Fair at the Crystal Palace recorded 6 million admissions when the population was 21 million) reflect the popular interdependency that used to exist between aesthetics and material development. • @tedgioia and others have written about stuck culture and how so many domains seem to have ceased to straightforwardly advance in the way that they did up until the nineties or thereabouts. This is obviously peculiar and interesting. What changed, and what does it mean? Is it about the internet and fragmentation? Is it about a loss of supply? Is it just about having reached the zenith of various mediums? • I’m generally interested in markets and the dynamics of creation. In aesthetics broadly, I find the reflexivity between supply- and demand-side factors to be very thought-provoking. There’s a natural desire to view satisfaction of individual preferences as the yardstick to measure market success, but things get interesting and even a bit unsettling when we start to think about how the supply might start to shape the demand. I often think about this in the context of food. Why is food so much worse in Germany than many of its neighbors? Germany certainly doesn’t have less material ability to produce good food; indeed, Germany is richer than the countries around it. There’s probably something about German food supply chains that is impoverished relative to France and Italy, but the Germans themselves don’t seem too upset about it. It just seems that the Germans are stuck in an objectively worse market equilibrium than their neighbors: the food is bad and they’ve gotten used to it. The obvious question then is where else these kinds of reflexive patterns apply, and where else we’re stuck in some objectively inferior equilibrium, even if preferences are in some superficial sense being sated. • While this is an extremely banal and obvious point, I hadn’t until recently thought much about or internalized how much one can study reasonably objective things ("the status of women in society", say) through artwork. (Thanks to @_alice_evans for opening my eyes here.) In this vein, I’m pretty excited about the possibilities over the coming years in computational art analysis. I want something that’s conceptually similar to Google Ngram timelines but for the visual arts. • We've always tried to do things well at Stripe. I've come to see that attempting to do them beautifully is often a helpful way to break out of standard practices and to do something with greater novelty and in a way that might have other benefits besides. (Also, excellent people want to do great work because it is intrinsically satisfying. Explicitly allowing aesthetic considerations to carry weight avoids having to justify every assessment with some kind of torturous empiricism.) • In his Nobel Lecture, Solzhenitsyn said that, among the Platonic virtues of goodness, truth, and beauty, that beauty is special, for it possesses a unique kind of irrefutability. He notes that arguments, writing, and philosophical systems can all be predicated on misapprehensions, but that “a true work of art carries its verification within itself.” He proceeds to observe that when goodness and truth are threatened, the “ever surprising shoots of beauty will still force their way through.” There is a lot of specious and motivated reasoning in the world today and plenty of questionable value systems. I don’t think that beauty directly reflects any definitive trait, but I’m intrigued by the idea that it can be a marker of deeper metaphysical coherence.
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