llm/9db4e77f-8dd5-46da-972e-40d33f3399ef/topic-2-f6ff8a03-bad7-48fa-b029-4a0d60223479-input.json
The following is content for you to summarize. Do not respond to the comments—summarize them. <topic> The One-Person Unicorn Startup # Debates on whether AI enables solo founders to build billion-dollar companies, arguing that while coding is easier, business bottlenecks like sales, marketing, and product-market fit remain unsolved by LLMs, despite rumors of stealth successes. </topic> <comments_about_topic> 1. My initial response to reading this post was "wow, I think I'd rather just write the code". I also remain a bit skeptical because, if all of this really worked (and I mean over a long time and scaling to meet a range of business requirements), even if it's not how I personally want to write code, shouldn't we be seeing a ton of 1 person startups? I see Bay area startups pushing 996 and requiring living in the Bay area because of the importance of working in an office to reduce communication hurdles. But if I can really 10x my current productivity, I can get the power of a seed series startup with even less communication overhead (I could also get by with much less capital). Imagine being able to hire 10 reliable junior-mid engineers who unquestionably followed your instruction and didn't need to sleep. This is what I keep being told we have for $200/month. Forget not needing engineers, why do we need angel investors or even early stage VC? A single smart engineer should be able, if all the claims I'm hearing are true, to easily accomplish in months what used to take years. But I keep seeing products shipped at the same speed but with a $200 per month per user overhead. Honestly I would love to be wrong on this because that would be incredibly cool. But unfortunately I'm not seeing it yet. 2. > shouldn't we be seeing a ton of 1 person startups? Here's the dirty secret: 1 person AI coding enabled startups don't want their customers to know that they are 1 engineer AI coding startups so they do not expose it or share that info. There is still a lot of negative sentiment associated with this. I know 3 such founders; none would advertise to their customers the extent of their AI usage. There is also a consideration that if they advertise their 1 eng status and success, it might attract other competitors or the customers might think they can do it themselves (maybe possible, but not for 95% of them since some tech know how is still required) or customers would see it as a business risk. All 3 have blown me away with what they are doing. All 3 have real, paying customers. (They occasionally reach out for some higher order architecture questions) 3. As of the middle of the year, there was no increase in publicly available indicators of new startups at all [0]. No change in the trend in steam releases, domain name registrations, app store releases, etc. People might be able to keep the fact that they're a one person team that built the app with AI secret, but they wouldn't be able to keep the fact that they made an app secret. Unless someone has evidence that's changed dramatically in the last six months, I have to conclude that the reason we aren't seeing a wave of AI enabled SaaS startups isn't that they're keeping the fact that they're solo operations with AI a secret, but rather that no such wave actually exists. [0] https://mikelovesrobots.substack.com/p/wheres-the-shovelware... 4. Can't speak for anyone else, but I personally know 3. 2 of the 3 existed as entities for more than a year already, but pivoted at least once (both were VC-funded but now doing something very different than what they started with when I first met founders) and ultimately let go of their offshore and contract engineers once AI became good enough some time early last year. Founders basically realized that the quality of code was as good or better than what they were getting from their engineers while reducing the turnaround time; now they can go from talking to customers to having a working prototype in the same day instead of waiting 24h+ for an offshore team. The other one started in November of 2024 and found traction around March. So two companies went from multi-person teams to 1 person teams and 1 team was a 1 person eng team from the get-go (with a business-oriented partner). I'd also point out that 2025 was a particularly volatile year because of shifts in the political and economic environment (including very high interest rates) so I wouldn't take your stat at face value without considering external factors that might affect the total number of net new business registrations. It still remains true that building a product is not the same thing as building a business. It may be that we'll see less SaaS startups as companies find that they can just in-house software instead of buying. Who knows? Startup I'm at canceled one of our subscriptions because we ended up building an in-house replacement because it is now cheap enough and easy enough that we could. 5. > Can't speak for anyone else, but I personally know 3. I'm not saying your three friends/acquaintances don't exist, I'm saying the evidence suggests they aren't representative of a trend. This is consistent with the other evidence we have (e.g. studies which show that LLMs produce at best relatively modest gains in productivity, not enough for a one person team to do the work of even two people. > I'd also point out that 2025 was a particularly volatile year because of shifts in the political and economic environment so I wouldn't take your stat at face value without considering external factors that might affect the total number of net new business registrations. Sure, it's always possible that without LLMs there would have been a significant contraction in these metrics. The issue is exactly that though: you can always make that argument. In other words, you've rendered your claims unfalsifiable. 6. I'm not saying it's evidence for some larger trend; I'm presenting the reason why single-person teams might not advertise why they are single person and that these teams are not necessarily starting as single person teams, but sometimes collapsing down to single person teams. 7. Maybe you don't mean to, but when you present an anecdote you're implying evidence of some trend, otherwise it's just a pointless statement. And unless a multi-person team is collapsing down into multiple single person teams, there's no increase in productivity and we're actually in a worse position as a whole. 8. Except in context that was very much what was suggested. The implication of the comment I replied to is that there actually are "a ton of 1 person startups" (and by implication, that LLMs do enable the massive increases in productivity that their proponents like to claim), but that they just keep the fact that they are quiet. 9. This matches what I’ve been seeing as well. Small teams can move surprisingly fast now, but the bottleneck usually shifts from engineering to distribution and positioning. We’ve found that building the product got easier, but turning it into a sustainable business still required just as much manual effort around sales, onboarding, and retention. 10. You're moving the goalposts; building the product never equaled writing some code, it's always involved all of the efforts you reference. The expectation is that you optimized the code generation and shifted the bottleneck, but are overall more productive (i.e. the cycle is shorter). If you're not iterating faster then there's be no productivity gain. 11. Those companies weren’t multiple person teams. They were one person teams with contract work. Maybe you know the details of the kind of money they were paid or how involved they were with the work but that could mean so many things. I’d have to say when I hire someone in Fiverr to make a logo for my app I’m not suddenly a multi-person team. If I use AI to make my logo instead of paying a human $50 to make one I didn’t exactly experience a productivity revolution. The other thought that popped into my head is that offshore contractors have access to AI, too. So shouldn’t we see their output go up and prices go down? Again we have another facet of this lack of market indicators. 12. They were multi-person teams. Some had employees (which were let go when they pivoted). Some were contractors doing all of the engineering work. 13. The majority of businesses fail within 5 years. Are they using AI because it’s better or because they have no other choice? If I hire two sandwich artists for 6 months but nobody buys my sandwiches, I don’t have much choice but to fire them. This word “pivot” is strong. 14. > Are they using AI because it’s better Because it's better (versus the engineers they were able to hire). > If I hire two sandwich artists for 6 months but nobody buys my sandwiches Pivot is strong and in both cases where they went n -> 1, the pivots were dramatic. One went from building a (credit) card switching SDK to building a legal assistant AI. One went from building a fin-tech compliance product to a CRM for managing collections. Because they went back to the drawing board, they ended up letting go of their teams and started using AI to build MVPs and then found that they could ship faster and better. 15. I don't think cheaper/easier software development can be the limiting success factor for many startups. Success is more about the skills and business aptitude of the founder(s), which is why VCs invest more in people than ideas, and don't seem to flinch when founders pivot to something completely different. I could see AI coding leading to more attempted startups, and more people shipping initial products and attempting to get traction with them, but whether they do get traction and achieve PMF, and are able to actually grow it into a business is going to come down to the startup expertise of the founders, not how quickly/cheaply the code of the product was written. 16. I expect you see the world this way because you are a software developer. People who know how to sell and understand the problems to solve do not routinely understand how to build software to solve those problems so they can sell them to customers. Now that the bar for building software is lowering, the world of building a startup is changing. A relatively newcomer to software is able to ship a medium complexity vibe-coded app to a few test customers and kick off revenues. 17. I agree that the bar for building software has dropped significantly, but I think the harder part still shows up right after the first few customers. Shipping something workable is easier now, but understanding which problems are actually worth solving — and getting consistent feedback early — still seems to be the main separator between hobby projects and real businesses. 18. I totally concur. That said, technology is evolving fast, and I think it's clear that the bar for solving those problems with non-technical people will drop dramatically in the next 12 months. 19. I think so too. But in the meantime there is a quiet goldrush for people who spot niches where they can extract decent (or a lot) of value right now, and for long enough to be worthwhile. If they can get scale enough that thinner margins makes for a worthwhile business when the market catches up, great. If they can't, then we stay lean we might make off with decent ROI. But that is also a reason to be cautious of chasing capital and think hard about whether you can spend it sensibly fast enough to improve your own ROI... E.g. I have a project right now where I won't consider taking VC cash because I don't think I can spend it fast enough to buy me enough additional leverage to make enough additional money to compensate for the dilution and the other usual shenanigans before I expect margins will be squeezed out of the niche in question. It also means I don't think the opportunity will ever scale above a certain level, but that's fine - it'll be a quick attempt at grabbing what profit I can. Also, while we of course shouldn't diminish the potential moat created by understanding the product in favour of only value the tech, we need to also consider that AI's are a levelling factor there too. Claude knows (I've verified what it's said) more about the niche I'm vaguely talking about than I do - it knows pricing, it knows positioning/marketing, it knows conventions and requirements of the niche, and while I'm sure I could have found all of it myself starting from scratch too it shortcircuited an enormous amount of effort to get an infodump that let me know precisely what to look for to verify it. A lot of tech companies will find the institutional knowledge they thought would shore up their moat is worth a lot less than they thought. 20. Perhaps for extremely basic products. Most non-engineers can barely write and untangle their messy thoughts and you think they can just build a spec for an AI to build a product? Hopefully I'm wrong, but I doubt it. 21. You are discounting sales, marketing, and branding. Take drop shipping for example: anyone can do this, but the successful ones are those that know how to brand and market the product well. Not to mention having the right mindset for startups and building a business. The code and product is maybe only 20% of the story. 22. > that offer the same for 10x less money. Not likely because there is still a lower bound. These 1 person startups are winning partially because they are already 10x cheaper than the incumbents. But beyond that, it's not likely that there are 10x the number of people who know the domain and have the right mindset plus appetite for risk. 23. I am one of those founders who does not want their customers to know. I have one specific very large customer that is quite an old school company. My software has become pretty pivotal for some of their workflows and if they knew it was one guy on his laptop keeping things afloat with the help of a mysterious AI I am pretty sure they'd reconsider our contract. 24. Most startup -> enterprise deals are like this in nature. Enterprise buyers are already wary of small startups (for various reasons). A 1 person startup? Wouldn't even get a meeting with the buyers in many cases even if your software was 10x cheaper and exactly solved the business problem. 25. I worked for a public health care Enterprise early in my career and I make a joke to one of the VPs once about how it seemed like the real career success would be finding one of our pain points as a patient or employee, leaving to start a company that solves that, and selling it back to us. He laughed and said several people had done that but you better take a half dozen executives with you or you'd never get the first meeting no matter how good the product was. 26. > you better take a half dozen executives with you or you'd never get the first meeting no matter how good the product was I spent ~16 years of my career in life sciences and this is also my experience. There's no way you get into an enterprise account with a pharma as a startup without a lot of deep connections; life sciences space is very high in regulatory requirements and risk and the risk/reward ratio with startups simply isn't worth it. In my specific space, clinical trials can run for years. A company that might fold if they run out of runway? Non-starter. I was a member of a small company that did make this work and it required that we put our code in escrow with a large multi-national IT company that owned the support contract (customer paid us for licensing, paid multi-national IT company for support, our source code went into escrow). 27. Agreed, it's never been a better time to start a startup with a very small team. 28. The key (based on my exp with these 3) is the composition of the team. At least 1 person on the team needs to have domain experience and if solo, that solo founder needs to have domain experience and good connections or the wherewithal to get the first handful of paying customers via cold calling, cold emails. The main challenge remains sales, marketing, and branding. There are free CRMs and anyone can build a CRM. Why do some CRMs succeed while others fail? Branding, marketing, awareness. So I don't see it as "there will just be 10x more competitors" because I've built enough stuff that I failed to sell and used enough shitty software to know that the software itself is rarely the reason why people buy X over Y. It's because they didn't even know Y existed. 29. My biggest question now is - since now anyone can build a SaaS, and since everything is now optimized not for "employment" but for "enterprise" (run your own business), just how many 1-2 person companies can we build? I mean how many genuine sell-able ideas are there. Can we as a society have a 100,000s small software enterprises (and not a few hundred employing 1000s)? I would love to start my own SaaS company, even if it generates $1000 a month I will be elated. And I have 20+ years of experience programming and in FinTech, but what do I build? Not to mention, without sales & marketing nothing will really work. 30. Two of the startups are lead by non-technical founders who have strong industry specific experience (legal and finance). The third has a partner that has industry experience (is the ICP). So you definitely still need strong sales and marketing and a deep understanding of a business domain. 1 person and AI is not sufficient to create a business. 31. > shouldn't we be seeing a ton of 1 person startups? After months of hearing that people are producing software in months that would normally take years, the best examples of vibe coded software I've seen look like they would normally take months, not years. If you don't care how they're built or how long it took (which a user generally doesn't), much of the remaining shine comes off. If I'm wrong, I'd love to see it. A genuinely big piece of software produced entirely (or near entirely?) with AI that would've normally taken talented engineers years to build. 32. Linux is 34 years old, most large software projects are not. Also your using a specific version of Claude, and sure maybe this time is different (and every other time I've heard that over the past 5 years just isn't the same). I don't buy it, but lets go along with it. Going off that, we have the equivalent of 2 years development time according to whats being promised. Have you seen any software projects come out of Claude 4.5 Opus that you'd guess to have been a 2 year project? If so, please do share 33. I’m building an ERP system, I’ve already been at it for a 3 years (full time, but half the system is already in production with two tenants so not all of my time is spent on completing the product, this revenue completely sustains the project). AI is now speeding this up tremendously. Maybe 2x velocity, which is a game changer but more realistic than what you hear. The post AI features are just as good and stable as pre AI, why wouldn’t they be? I’m not going to put “slop” into my product, it’s all vetted by me. I do anticipate that when the complexity is built out and there are less new features and more maintaining/improving, the productivity will be immense. 34. I do stuff in my free time now that would have been a full time job a year ago. Accomplishing in months what would have taken years. (And doing in days what would have taken weeks.) I'm talking about actually built-out products with a decent amount of code and features, not basic prototypes. I feel like the vibe is "put up or shut up", so check out my bio for one example. I think your logic goes wrong because you assume that more productivity implies less desire for engineers. But now engineers are maybe 2x or 5x more productive than before. So that makes them more attractive to hire than before. It's not like there was some fixed pool of work to be done and you just had to hire enough to exhaust the pool. It's like if new pickaxes were invented that let your gold miners dig 5x more gold. You'd see an explosion in gold miners, not a reduction. For another example, I spend all my free time coding now because I can do so much now. I get so much more result for the same effort, that it makes sense to put more effort in. 35. > It's not like there was some fixed pool of work to be done and you just had to hire enough to exhaust the pool. I'm my opinion you are failing to consider other bottlenecks, a la the theory of constraints. An analogy: Imagine you have a widget factory that requires 3 machines, executed in sequence, to produce one widget. Now imagine one of those machines gets 2x-5x more efficient. What will you do? Buy more of the faster machines? Of course not! Maybe you'll scale up by buying more of the slower machines (which are now your bottleneck) so they can match the output of the faster one, but that's only if you can acquire the raw material inputs fast enough to make use of them, and also that you can sell the output fast enough to not end up with a massive unsold inventory. Bringing this back to software engineering: there are other processes in the software development lifecycle besides writing code -- namely gathering requirements, testing with users (getting feedback), and deployment / operations. And human coordination across these processes is hard, and hard to scale with agents. These other aspects are much harder to scale (for now, at least) with agents. This is the core reason why agentic development will lead to fewer developers -- because you just don't need as many developers to deliver the same amount of development velocity. The same logic explains (at least in part) why US companies don't simply continue hiring more and more outsourced developers. At a certain point, more raw development velocity isn't helpful because you're limited by other constraints. On the other hand, agentic development DOES mean a boon to solo developers, who can MUCH more easily scale just themselves. It's much easier to coordinate between the product team, the development team, the ops team, and the customer support team when all the teams are in the same person's head. 36. I "just" created a real-time strategy game before christmas because I could have Claude writing all the code and test it itself. It wrote the spec too, by me telling it to plan out a game "a bit like X but with A, B, C features instead". It works. It's playable. I might put it online some-time when I get a chance. [EDIT: My involvement apart from the code-skimming mentioned below was mostly play-testing after Claude had "play-tested", and giving it feedback on what to add or change] My best estimate from having written much simpler games before was that it churned out many months worth of working code in days. I've not written a line of it - just skimmed some code and told it to make a few architectural refactors. It's absolutely crazy. 37. "Built out products" like you're earning money on this? Having actual users, working through edge cases, browser quirks, race conditions, marketing, communication - the real battle testing 5% that's actually 95% of the work that in my view is impossible for the LLM? Because yeah the easy part is to create a big boilerplate app and have it sit somewhere with 2 users. The hard part is day to day operations for years with thousands of edge cases, actual human feedback and errors, knocking on 1000 doors etc. Otherwise you're just doing slot machine coding on crack, where you work and work and work one some amazing thing then it goes nowhere - and now you haven't even learned anything because you didn't code so the sideproject isn't even education anymore. What's the point of such a project? 38. > "Built out products" like you're earning money on this? No, I'm not interested in monetizing stuff, I make enough money from $dayjob. > Having actual users, working through edge cases, browser quirks, race conditions, marketing, communication - the real battle testing 5% that's actually 95% of the work that in my view is impossible for the LLM? Yes, all of those. Obviously an LLM won't make a tiktok ad for me, but it can help with all the other stuff. For example, you mentioned browser quirks. I ran into a bug in safari's OPFS implementation that an LLM was able to help me track down and work around. I also ran into the chrome issue where backdrop effects don't work if any of the element's parents have nonzero transparency, and claude helped me find all the cases where that happened and fix them. Both of these are from working on the app in my bio. It's a language app too, so however many edge cases you think there are, there's more :D I don't want to give the impression that it was not a lot of work. It was an enormous amount of work. It's just that each step is significantly faster now. > and now you haven't even learned anything because you didn't code so the sideproject isn't even education anymore. I read every line. You could pull up the github right now and point to any line of code and I could tell you what it does and why it's there and what will break if you remove or change it. > What's the point of such a project? I originally made it because I wanted a tool to help me learn French. It has succeeded in helping my enormously, to the point where I can have short conversations with my french family members now. Others seem to find it useful too. 39. Because a startup is NOT just writing code. It's also understanding what you are building, and for whom. The issues of product market fit did not suddenly disappear: https://www.wired.com/story/artificial-intelligence-startups... 40. They are absolutely crushing it. I know of a one-man shop that just got notice they were selected for an eight-figure revenue contract. They would NEVER go public with their head count or their product being built by AI. 41. > shouldn't we be seeing a ton of 1 person startups Oh, man, they're just waiting for their poster boy to show up. Once first unicorn "built by a single person" pops up you'll regret having a single social network account. 42. > shouldn't we be seeing a ton of 1 person startups? Who should be seeing that? The thing about 1 person startups is that it requires little to no communication to start up, and also very little capital. Seems easy to fly below the radar. Also "a ton", idk. Doing a startup is still hard, for reasons outside of just being able to write a lot of code. In my experience churning out all this code at 10x is coming with a significant complexity tax: Turns out writing code and thinking about code problems was the relaxing part. When that goes away you have to think about real world problems only. What a fucking mess. Still, I would assume that it's more of a thing now, and something you could observe when you have YC data for example. Do we know that's not the case? I am in no position to say, one way or the other. 43. My favorite movie quote as it pertains to software engineering has for a long time been Jurassic Park's: “Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.” That’s how I feel about a lot of AI-powered development. Just because you can have 10 parallel agents cranking out features 24/7 and have AI write 100% of the code, that doesn’t mean you’re actually building a product that users want and/or that is a viable business. I’m currently in this situation, working on a greenfield project as founder/solo dev. Yes, AI has been tremendously useful in speeding things up, especially in patching over smaller knowledge gaps of mine. But in the end, as in all the projects before in my career, building the MVP has rarely been the hard part of starting a company. 44. I agree with you. I don’t think number of startups or less reliance on funding is the measure though. Businesses are not code. They solve problems, find their customers, convince them to buy their solution, and maintain that relationship. Code has always been a factor but not the critical one. 45. > shouldn't we be seeing a ton of 1 person startups How do you know this is not happening. There is always a lag. By the time you visibly see it, its already past. 46. My brother is selling a CRM he developed for his business to others for a couple thousand a month. There is no way he would have built the CRM as quickly pre-AI. He built, in a few months, what would have taken maybe one to two years before. It's probably going to be a while before someone builds the next Instagram with AI. But I think that's more a function of product fit and idea. Less so how fast one person can code. The first billion-dollar solopreneur likely is going to happen at some point, but it's still a one-in-a-million shot, no matter how fast a person can code. Look at how many startups fail despite plenty of money for programmers. But I am seeing friends get to revenue faster with AI on small ideas. 47. > The first billion-dollar solopreneur likely is going to happen at some point I'm pretty sure that this has already happened, see: https://en.wikipedia.org/wiki/Plenty_of_Fish Not quite 1bn (but 575mn in 2015 dollars) and mostly done by one person. 48. He began hiring in 2018. Also, "Plenty of Fish uses a Microsoft-based platform for itself, including IIS, ASP.NET, and Microsoft SQL". 49. So if I make a website that uses Nginx, Ruby, and Postgres, does that mean that I don't get credit for making it since I use other tools? 50. I think the other issue is that the leading toolchain to get real work done (claude code) is also lacking multi modality generation, specifically imagegen. This makes design work more nuanced/technical. And in general, theres a lot of end-product UI/UX issues that generally require the operator to know their way around products. So while we are truly in a boom of really useful personalized software toolchains (and a new TUI product comes out every day), it will take a while for truly polished B2C products to ramp up. I guarantee 2026 sees a surge. 51. Link to the crm? I'm asking because all tge crms I have encountered so far were vastly more complex than Instagram. I would actually expect that current coding AIs would create something very close to Instagram when instructed. 52. Here it is: https://thedefinedcrm.com/ > I would actually expect that current coding AIs would create something very close to Instagram when instructed Agree 100 percent! I think a lot of us are conflating writing software with building a business. Writing software is not equal to building a business. Instagram wasn't necessarily hard to code, it was just the right idea at the right time, well executed, combined with some good fortune. AI is enabling solo founders to launch faster, but those solo founders still need to know how to launch a successful business. Coding is only 10% of launching a business. My brother has had some success selling software before AI, so he already knows how to launch a business. But, AI helped him take on a more ambitious idea. 53. > My brother is selling a CRM he developed for his business to others for a couple thousand a month. There is no way he would have built the CRM as quickly pre-AI The thing is, if AI is what enabled this, there's no long term market for selling something vibe coded for thousands a month. Maybe right at this moment and good for him, but I have my doubts these random saas things have a future. 54. A lot of people either a) don’t know about the good tools or b) aren’t using them enough/properly. There is a ton of anti-AI sentiment, and not all LLMs are equal. There is a lot of individual adoption that is yet to occur. I know at least two startups that are one person or two people that are punching way above their weight due to this force multiplier. I don’t think it’s industry-wide yet, but it will be relatively soon. Check back in on your assessment in a year. 55. I'm a 1-person startup doing pretty well. I got laid off in the first half of 2025 and decided to use my severance to see if I could go full-time with my side project. Over the last six months I've gone from zero to about $200k in ARR, and 75% of that was in the last three months. My average customer is paying about $250 / month. I have zero help, I do everything myself: coding, design, marketing, sales, etc. The product uses AI to replace humans in a niche industry, so the core of the product is AI, but I also increasingly build it with AI. I rarely code manually these days, I'm just riding herd on agents, often in between sales calls, dealing with customer support, etc. I may eventually hire a VA-type person to help with admin and customer support stuff where it changes often enough that it's not worth it to build an AI workflow for, but even there...I don't know. If we get reliable computer use models in 2026 or 2027, I probably won't ever hire anyone. I've never talked openly in tech circles about this product, nor will I. The technical challenges are non-trivial, so I don't think it'd be easy to replicate for another engineer, but my competitors are all dinosaurs and getting customers to switch to me is incredibly easy. The last thing I need is another engineer spinning up a competitor. 56. > shouldn't we be seeing a ton of 1 person startups? Too early. Wait a year. People are just coming to grips how to really make these agents make good changes and large enough changes to really start accelerating. Also, expect a number of those startups to be entirely stealth and wait longer to raise, as well as maybe in many cases be more fleeting and/or far more fast moving (having to totally re-invent what they're doing at a pace you wouldn't expect to before). I've been full in on this for 2 years now, and I'm only just at the stage where I feel my setups and model capabilities are intersecting to produce results good enough that I've started testing if one project I'm working on will actually manage to generate revenue. I'm not going to tell you what it is, because if I did there's too little moat and HN is crawling with great people who could probably replicate it and execute on it faster than me, and Claude is capable of doing all the heavy lifting entirely by itself - that in itself is what makes it potentially viable -, so sorry for being vauge. If it shows signs of generating revenue, it'll be so cheap to scale because of Claude, that I'll be able scale it far before I need to raise any capital. But other people will figure it out, most likely other people are already doing the same thing. As a result I have a short window, and it likely will close as model improvements will make it more and more trivial to do what I'm trying to do, so my approach is to try to extract as much return as I can in as little time as I can, hoping there isn't yet too much competition, and then move on. This last part will also limit - a lot of people just won't be able to move fast enough (I might not have), and so a lot of these "one person startups" won't ever become visible because they won't even get to a stage where people are ready to talk about it. In this case, it is easily measurable how much time Claude has saved me, because I've done the same thing before, manually, and made money from it, and the fastest turnaround I've achieved before was 21 days. So far, my first test run with Claude + me in the loop produced the same quality in 3 days, my second in 2 days, my third 12 hours, and I think I can drive it down towards 1-2 hours of my time, with me being the blocker to speeding it up beyond that. At 21 days it wasn't really profitable. At 1-2 days it "should be" wildly profitable unless I'm already too late. If I can get it down to an hour or two of my time, then I'd also be able to hire to scale it further with good margin, and the question is just finding the sweet spot. This opportunity will never be a unicorn, but there's a lot of money there if you don't need to raise, and the cost of scaling it to the sweet spot where I maximise my returns is something I should be able to finance without outside money the moment I validate that the unit economics are right. You might not hear about this "one person startup" again until it either has failed and I decide to tell the story, or it's succeeded but the opportunity has closed and I've made what I can make from it. I suspect there will be many cases like mine that you'll never hear about at all. (and yes, I realise a lot of people will just dismiss this as bullshit because I won't give details; that's fine) 57. I'm not dismissing it. I've been working on something secret-squirrel for over 5 years. It wasn't until November that I made a major breakthrough, resulting in four computer science revelations. At first, I wrote about it in a blog post; people didn't even believe me. Some researchers I wrote to validated it. I hadn't really used Claude before, but if nobody cares ... then commercialize it, delete the blog post and code from the open source world. In the last month, Claude has helped turn it from a <700 line algorithm into nearly a full-blown product in its own right. But yeah, the moat is small. The core of everything is less than 5k LoC; and it'd be easy af for my soon-to-be competitors to reproduce. The only thing I've got going for me is a non-technical cofounder believing in me and pounding on doors to find our first customer, while I finish up the technical side. With the computer science revelations, we can basically keep us 6-8 months ahead for the next couple of years. This is the result of years of hard work, but AI has let me take it to market at an astounding speed. 58. Depends on the project you are working on. Solo on a web app? You probably have 100s of small things to fix. Some more padding there, add a small new feature here, etc. 59. The captive audience is not you, it's people salivating at the train of thought where they can 100x productivity of whatever and push those features that will get paying customers so they can get bought from private equity and ride out on the sunset. This whole thing is existential dread on a global scale, driven by sociopaths and everyone is just unable to not bend over. 60. Painfully true. A lot of YouTube on LLM coding tools has become just that. Make quick bucks, look it generated a dashboard of some sort (why is it always dashboards?) and a high polished story of someone vibing a copy of a successful Saas and selling it off for a million. A shame really, for there are good resources for better making use of LLMs in coding. </comments_about_topic> Write a concise, engaging paragraph (3-5 sentences) summarizing the key points and perspectives in these comments about the topic. Focus on the most interesting viewpoints. Do not use bullet points—write flowing prose.
The One-Person Unicorn Startup # Debates on whether AI enables solo founders to build billion-dollar companies, arguing that while coding is easier, business bottlenecks like sales, marketing, and product-market fit remain unsolved by LLMs, despite rumors of stealth successes.
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