Will AI make software companies worthless?

“If AI gets to the point where anybody can easily create any software, what will happen to all these software companies? Do they just become worthless?”

That question recently sparked a 200+ comment thread on Reddit. And it’s not hard to see why people are asking it. Earlier this year at Davos, Anthropic CEO Dario Amodei said something that got a lot of attention: “I have engineers within Anthropic who say, ‘I don’t write any code anymore. I just let the model write the code. I edit it.’” He went on to predict that AI might handle “most, maybe all” of what software engineers do within six to twelve months. When the CEO of one of the most advanced AI companies says his own engineers have stopped writing code, it’s worth paying attention. So is the software industry headed for collapse? The short answer: no. But the long answer is more interesting. This question fundamentally misunderstands what a software company actually is.

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The sandwich shop paradox

Think about restaurants for a second. Anyone can make a sandwich. You’ve got bread, some meat, maybe cheese, whatever sauce you like. Five minutes, done. So why do sandwich shops exist? Why isn’t the entire restaurant industry collapsing under the weight of home kitchens? Because making a sandwich isn’t the same as running a sandwich shop. People pay for convenience. They pay for consistency. They pay for not having to clean up afterward. They pay for the expertise that makes a sandwich better than what they’d throw together at home. And they pay for the entire experience surrounding that sandwich. Software works the same way. The code is the sandwich. But the business? That’s everything else.

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The 1/3 rule

Here’s a reality check that often gets lost in these conversations. Take a software company with 300 employees like Upsun. How many of them write code? Maybe 100. A third at best. The other two-thirds? Sales, marketing, customer success, legal, finance, HR, operations, security, compliance, support. The people who answer the phone when something breaks at 2 AM. The folks who handle enterprise contracts and negotiate SLAs. The team that ensures you’re GDPR compliant and won’t get sued into oblivion. AI can help you write code. It can’t (yet) replace the entire organizational machinery that turns code into a business. A solo developer with AI can build an app. Building a company that supports thousands of customers across multiple time zones, handles their data securely, maintains uptime guarantees, and evolves the product based on market demands? That’s a different beast entirely.

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Creating software is not the same as keeping it running

This is where the “anyone can build software” argument falls apart. Because building is the fun part. It’s the honeymoon phase. Everything works in your dev environment, your demo looks slick, and you’re feeling pretty good about yourself. Then reality hits. Your app needs to handle ten times the traffic you expected. A security vulnerability shows up in one of your dependencies. Users start requesting features you never anticipated. The database schema you designed in week one doesn’t scale to week fifty. Some edge case you never considered crashes the whole thing. Maintenance, security, scalability, updates, patches, monitoring, incident response. This is where software gets expensive. This is where it gets hard. And this is where most vibe-coded projects go to die. Professional software companies have entire teams dedicated to keeping things running. They have on-call rotations, automated testing pipelines, staging environments, rollback procedures, and years of accumulated knowledge about what can go wrong. A weekend project built with AI prompts doesn’t have any of that.

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The vibe coder ceiling

Let’s talk about vibe coding for a minute. It’s a real phenomenon. Non-technical people are building functional apps by conversing with AI. They’re creating personal tools, automating workflows, and prototyping ideas that would have required a developer a few years ago. This is genuinely impressive. And it’s genuinely useful. But it has a ceiling. Vibe coders hit walls. Weird bugs they can’t diagnose. Performance issues they don’t understand. Security flaws they can’t even see. The AI can get you 80% of the way there, sometimes 90%. But that last 10% often requires understanding what’s actually happening under the hood. Here’s a typical scenario: someone builds a personal CRM with AI assistance. Works great for the first 500 contacts. Then the searches start slowing down. The app hangs when loading lists. The AI suggests adding indexes, but the vibe coder doesn’t know which ones or why. They copy-paste the solution, and it helps for a while. Then another bottleneck appears. And another. Each fix creates new complexity they don’t fully understand. Eventually, the codebase becomes a house of cards. It works, mostly, but nobody knows why. And when it stops working, nobody knows how to fix it without potentially breaking something else. And when you’re running a business on that software? When customers depend on it? When there’s money and reputation on the line? That’s when the ceiling becomes a serious problem. Professional developers aren’t going away. What’s changing is what they spend their time on. Less boilerplate, more architecture. Less repetitive CRUD, more complex problem-solving. The entry bar for creating something has dropped. The bar for creating something reliable, secure, and scalable hasn’t moved much at all.

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Software companies get AI too

Here’s something the doomsayers often forget: software companies also have access to AI. If AI makes individual developers more productive, it makes development teams more productive too. The company that previously needed 50 engineers to build and maintain a product might need 30 now. Or those 50 engineers can build something three times as complex. Software companies aren’t standing still while the world changes around them. They’re adopting the same tools, automating their own workflows, and using AI to extend their capabilities. The competitive dynamics shift, but the gap between professional operations and amateur builds doesn’t necessarily shrink. In fact, it might widen. A well-funded company with experienced engineers using AI effectively can produce software at a pace and quality level that a solo vibe coder can’t match. The tools are the same, but the expertise in wielding them isn’t.

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The real victims: simple SaaS and indie hackers

Alright, so total industry collapse isn’t happening. But that doesn’t mean everyone survives unscathed. Simple, single-purpose SaaS apps are in trouble. The habit tracker. The basic CRM. The minimal project management tool. The productivity app that does one thing reasonably well. These are exactly the kinds of products that motivated individuals can now build for themselves. Why pay $10 a month for a habit tracker when you can spend a weekend building one that does exactly what you want, customized to your specific workflow, with no subscription fees? People are doing this. They’re canceling subscriptions and building personal tools. Not everyone, but enough to matter. The market for commoditized, undifferentiated software is getting squeezed. Indie hackers building small products face similar pressure. The barrier to entry has dropped, which means more competition. And when your product is something an AI-assisted weekend project can replicate, your differentiation disappears. The math used to work like this: spend months building something, charge enough users $10/month, reach sustainable revenue. Now the equation changes. Potential customers look at your product, think “I could build that,” and some of them actually do. Your total addressable market shrinks. Your conversion rates drop. The users who do sign up expect lower prices because they know the alternative. This doesn’t mean all indie products are doomed. Unique value propositions, strong communities, excellent support, and genuine expertise still matter. But “I built a thing that works” isn’t enough anymore when anyone can build a thing that works.

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The enterprise moat

On the other end of the spectrum, enterprise software looks pretty safe. Think Adobe, Microsoft, Salesforce, SAP. These companies aren’t selling code. They’re selling ecosystems. Integrations with hundreds of other tools. Compliance certifications that took years to obtain. Support contracts with guaranteed response times. Training programs and consultants who know the product inside out. Decades of accumulated features that address every edge case in every industry. No amount of vibe coding replicates that. You might be able to prompt your way to a basic photo editor or a simple CRM. You’re not prompting your way to Photoshop or Salesforce. The complexity is too deep, the ecosystem too interconnected, the trust too hard-earned. Consider what it actually takes to sell software to a large enterprise. Security audits. SOC 2 compliance. GDPR readiness. Integration with their existing identity provider. Custom SLAs. Dedicated account management. The ability to survive a procurement process that takes six months and involves legal, security, IT, and finance teams. A solo developer with an AI-built app can’t offer any of that. The software itself might be functionally equivalent for a narrow use case. Everything surrounding it isn’t even close. Enterprise buyers aren’t looking for the cheapest option. They’re looking for the safest option. The vendor who’ll still be around in five years. The platform that won’t collapse when their business depends on it. AI makes building things easier, but it doesn’t make building trust easier.

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The race to the bottom (and what lies beyond)

For simple apps, expect a race to the bottom. Prices will drop. Competition will intensify. Products that don’t differentiate will struggle. But markets have a way of finding equilibrium. When everyone can build basic software, basic software stops being valuable. The premium moves to complexity, reliability, and service. The businesses that survive will be the ones that offer something beyond “it works.” Customer relationships matter more. Support quality matters more. Institutional knowledge matters more. Brand trust matters more. All the things that AI can’t easily replicate become the differentiators. We’ll probably see a boom in personal tools. People building exactly what they need, for themselves, maintained as long as they care to maintain it. That’s fine. That’s even good. It doesn’t eliminate the need for professional software any more than home cooking eliminates restaurants.

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The uncomfortable question

Of course, clients are already asking it: “Can’t you do this with AI for one-tenth the price?” The honest answer is: sometimes, yes. For straightforward tasks, AI dramatically reduces the effort required. Pricing models will adjust. Expectations will shift. The market will recalibrate. But the follow-up question matters more: “And who’s going to maintain it? Who’s on call when it breaks? Who’s liable when something goes wrong? Who’s going to update it when requirements change?” Building software has gotten cheaper. Running a software business hasn’t. And as long as that gap exists, software companies have a reason to exist too.

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Where this leaves us

AI isn’t making software companies worthless. It’s making bad software companies worthless. The ones coasting on complexity that AI can now handle. The ones whose only value proposition was “we can write code and you can’t.” The companies that survive and thrive will be the ones that always understood: the code was never the whole product. The business is the product. The reliability is the product. The support is the product. The trust is the product. If your entire value can be replicated by someone with a laptop and a ChatGPT subscription, you had a problem before AI came along. You were selling a commodity and charging for scarcity. The scarcity is gone. Time to sell something else. The software industry has survived paradigm shifts before. The rise of open source didn’t kill proprietary software companies. Cloud computing didn’t eliminate the need for software vendors. Each wave changed who won and who lost, but the industry adapted. AI is the next wave. It’ll reshape the landscape, not erase it. The winners will be the companies that understand what they’re really selling has never been code. It’s always been everything around it.