llm/9db4e77f-8dd5-46da-972e-40d33f3399ef/topic-10-18ea51cd-ae19-4ae9-a5b8-5d45f05feb0a-input.json
The following is content for you to summarize. Do not respond to the comments—summarize them. <topic> SaaS Commoditization and Moats # Predictions that AI will drive the marginal cost of software to zero, eroding traditional SaaS business models, and that future business value will rely on proprietary data, domain expertise, and distribution rather than code. </topic> <comments_about_topic> 1. 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. 2. 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. 3. But eventually people will catch up you can basically create a working product alone with the help of AI. My prediction is that this will lead to a margin free-fall for many software products where the main moat is the software itself. And a lot of SaaS companies will also become redundant when the AI can code up a tailored solution in an hour for free. 4. 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. 5. > 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. I totally agree. I think going forward the primary value of SAS will be the embedded domain expertise in a pre-built product. The comparison of Asana versus Notion comes to mind for project management. Asana forces abstractions of good project management upon you, whereas Notion lets you build it yourself. I think this principle will scale to all software in the future, where the only real value of software or it becomes exported maintenance obligations and a predetermines domain abstraction. But as you mentioned, I think companies will rapidly find that their own specific abstraction is worth a lot less than they believed. 6. This is mostly correct IMO. SaaS is extremely vulnerable, companies will be able to modify open source tools to do exactly what they need, and agents will make managing those services easier. This will lead to downward pressure on SaaS prices, and cause them to become more like cloud data management platforms that they let customers build on top of rather than one-size-fits-all apps. 7. I agree with this completely. I forsee an era of enterprise level 'template' saas products that are expected to be tinkered with and highly customized. I think products like Notion that have an incredibly robust customizability and integration layer are going to thrive, where every single company can use a template engine to build extremely customized applications - and the barrier to building on top of these will essentially become the rate of human speech. 8. I predict that the commercial market for a lot of software will evaporate as people find that getting AI to whip up a custom solution that fits their unique problem space like a glove is actually cheaper and simpler than trying to make COTS software do the job. We're not quite here yet, but maybe in a few years. 9. > I predict that the commercial market for a lot of software will evaporate Counterpoint: Windows, Oracle DB, etc. have had free/cheaper alternatives for decades and still thrived. 10. Yes/no. Regardless of the code complexity reduction there is still architecture, planning and implementation. Could someone come by and clone my work afterwards? Absolutely. Will they retain customers with only a little understanding of the product or model? Questionable. 11. You aren't just buying software, you're offloading liability of continued support and functionality. 12. Sure, but there's a whole lot of businesses already using custom solutions made with excel/access/etc that are held together with duct tape and chicken wire, so I think the adventurous spirit necessary is there. 13. In the same pattern there are a lot of businesses where these solutions are not efficient and they MOVED from them to expensive commercial software. It's actually an antipattern to build a bunch of in-house, Excel-based solutions - with AI or not - for these companies. 14. I'm not. That edge eventually converges to 0 when you have 10+ competitors that offer the same for 10x less money. If you don't have some kind of cult following like Apple eventually you'll get margin-squeezed till death and all that marketing, sales, etc. will get cut down to stay afloat. Of course all of the above is just my theory how this will play out in the long run, I'm no oracle by any means. 15. I'm not entirely disagreeing. There are limits there that means we can't assume the margins will go to their theoretical minimum. But you're also in part assuming the models don't increasingly know the domain or know how to research the domain and compile the information for you . They'll be squeezing margins out of a lot more than just the tech. 16. Discounting Apple, their products and their customers to a cult is at best jealousy but still blatantly wrong. Lots of competition has been trying to out-Apple them for decades with no luck, and it's not because an iPhone customer is stupid & brain-washed. 17. Disclaimer: not an """AI""" enthusiast. I think it takes away the joy of coding, which makes me sad. With that out of the way, I don't think there will be "people inheriting codebases" for much longer, at least not in the vast majority of business-related software needs. People will still be useful insofar as you need someone responsible and able to be sued for contract breach, failures and whatnot, but we'll see more and more agents inheriting previous agents codebases. And in the other hand, "small software" that caters to particular customized workflows can be produced entirely by LLMs. I can totally relate how some of us would want to be off raising goats, planting watermelons or whatever. 18. I'm not discounting your experience, but purely from experiment design, you don't have any sort of pre/post AI control. You've spent 3 years becoming a subject-matter expert who's building software in your domain; I'm not surprised AI in it's current form is helpful. A more valuable comparison would be something like If you kept going without AI, how long would it take someone with similar domain experience who's just starting their solution to catch using AI? 19. 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. 20. 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. 21. > 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. 22. Do you think you could build craigslist? Why are they worth so much? 23. I think that's comparing something different. I've seen the one-day vibe code UI tool things which are neat, but it feels like people miss the part that: if it's that easy now, it's not as valuable as it was in the past. If you can sell it in the meantime, go for it and good for you, but it doesn't feel like that business model will stay around if anyone can prompt it themselves. 24. > 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) 25. 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. 26. Owning the means of cognition is going to be more and more importan as it allows one to scale more than linearly. Outsiders will be tied to limited or pay per use because owning the means of cognition will be a massive extractive economy </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.
SaaS Commoditization and Moats # Predictions that AI will drive the marginal cost of software to zero, eroding traditional SaaS business models, and that future business value will rely on proprietary data, domain expertise, and distribution rather than code.
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