What Comes After SaaS: The Shift to AI-Native Software

21 Months Later, the SaaS Landscape Looks Different

In June 2024, we published a post arguing that the SaaS model was heading for a fundamental disruption. At the time, a lot of people thought we were being hyperbolic. SaaS was a trillion-dollar market. Subscription software was the dominant business model in tech. Saying it was dying felt like saying the sun was going to stop rising.

Twenty-one months later, the evidence is becoming hard to ignore. Every week, we help businesses replace SaaS subscriptions with custom-built software that costs less and works better. The thesis is not a thesis anymore. It is our daily work.

This post is about connecting the dots. Everything we have written about over the past two years -- vibe coding, MCP, AI agents, the consulting playbook we use with clients -- it all points to the same conclusion. The era of one-size-fits-all software sold on monthly subscriptions is ending. What comes next is going to be radically different.

The Three Forces That Broke the Model

When we wrote the original post in 2024, we were looking at early signals. The AI models were getting good enough to write code, but the tooling was not there yet. It was like seeing the first cracks in a dam and knowing what was coming. Now the dam has broken, and three specific forces caused it.

Force 1: AI Agents That Actually Work

The first generation of AI was a chatbot in a box. You could ask it questions and get answers, but it could not do anything. It was intelligence without agency. That changed with the rise of AI agents -- systems that can take actions, not just generate text.

The technology that made agents real is MCP -- the Model Context Protocol from Anthropic. MCP gave AI the ability to connect to databases, APIs, email systems, CRMs, and anything else with a programmatic interface. We wrote about this in detail in our MCP servers explainer, but the short version is: AI went from a brain in a jar to a team member that can actually operate your business tools.

This matters for SaaS because a huge portion of what SaaS does is automate workflows between systems. If an AI agent can do that same automation -- but customized to your specific workflow instead of a generic one -- the value proposition of the SaaS tool evaporates.

Force 2: CLI Agents Made "Build Your Own" Viable

This is the piece that a lot of commentators miss. They see browser-based AI coding tools like Lovable and Bolt and think that is the disruption. It is not. Those tools are fine for landing pages and prototypes, but they hit a wall fast when you try to build real business software.

The real disruption is CLI-based AI agents, and Claude Code specifically is the tool that changed our business. We go deep on its capabilities in our complete guide to Claude Chat, Cowork, and Code. After early experiments with browser-based tools fell short on production projects, we moved to Claude Code and never looked back. It works in the terminal, with real codebases, deploying to real infrastructure. It can build, debug, and deploy production-quality software through natural language conversation.

This is not a subtle distinction. The difference between a browser-based AI coding toy and a CLI agent like Claude Code is the difference between a go-kart and a truck. One is fun to play with. The other can haul freight. And hauling freight is what businesses actually need.

With Claude Code, we routinely build custom applications in 1-2 weeks that replace SaaS tools our clients were paying hundreds of dollars per month for. The applications are tailored to the client's exact workflow, hosted on their infrastructure, and they own the code. No subscription. No vendor lock-in. No paying for features they will never use.

Force 3: The Cost Curve Crossed

For decades, the math was simple: building custom software was orders of magnitude more expensive than buying SaaS. A custom CRM might cost $200,000 to build. A SaaS CRM costs $100/month. Even over ten years, the SaaS option was cheaper.

That math has inverted. A custom CRM built with Claude Code -- specifically scoped to what a business actually needs -- costs $5,000 to $15,000 to build and $20 to $100/month to host. Break-even against a $100/month SaaS subscription happens in months, not decades. And the custom version does exactly what you need instead of forcing you to work around what it does not.

This cost curve crossing is the event that SaaS cannot recover from. You can compete on features, on ease of use, on ecosystem. But you cannot compete when your product costs 10x more and does less than the custom alternative.

The Evidence Is Overwhelming

We are not relying on theory here. Here is what we have seen in our own practice over the past year.

• Client SaaS replacement engagements have tripled since Q1 2025. This is now the most common type of project we do.
• Average SaaS cost replaced per client: $800-$1,500/month. That is $10,000 to $18,000 per year in savings per client, not counting the productivity gains from having software that fits their actual workflow.
• Zero clients have gone back to their previous SaaS tools after switching to custom. Not one. The custom solution works better because it was built for them.
• Build times are compressing. Projects that took us 4 weeks a year ago take 2 weeks now as Claude Code and our own processes have improved.

And this is just one small AI consulting firm in Florida. Multiply this pattern across thousands of companies doing similar work, and you start to see the scale of what is happening.

What SaaS Becomes Next

SaaS is not going to disappear. But it is going to bifurcate into two categories, and the middle is going to get hollowed out.

Category one: infrastructure SaaS. Stripe, Twilio, AWS, Snowflake -- tools that provide genuine technical infrastructure that is unreasonable to replicate. These are safe. You are not going to vibe-code your own payment processing network. These companies provide real value that scales.

Category two: AI-native platforms. New tools built from the ground up around AI capabilities -- not traditional SaaS with an AI feature bolted on, but fundamentally new approaches to business software. These are emerging now and they look very different from traditional SaaS.

The category that is in trouble: application SaaS. The CRMs, project management tools, marketing platforms, HR systems, invoicing apps, form builders, reporting dashboards, and every other tool that is basically a database with a user interface and some business logic. This is the vast majority of the SaaS market by company count. And this is what custom AI-built software directly replaces.

These companies built their businesses on the assumption that their customers could not build alternatives. That assumption protected them for years. It no longer does.

What This Means for Business Owners

If you are running a business, the implication is straightforward: you have leverage now that you did not have before. You are no longer at the mercy of software vendors who built a generic tool and told you to adapt your business to it.

Practically, here is what we recommend:

• Audit your SaaS spend. Look at every subscription and ask: what percentage of this do we actually use? What do we work around? What frustrates the team?
• Identify your highest-pain tools. The ones where your team spends the most time fighting the software instead of using it. Those are your first candidates for replacement.
• Start with one replacement project. Pick the tool that is most painful and least complex to replace. Prove the model works in your business before scaling up.
• Think about ownership. When you build custom software, you own it. No price increases. No feature removals. No vendor pivots. No "that will be in our enterprise plan." The software works for you, not for shareholders.

What This Means for SaaS Founders

If you are building a SaaS company, you need to be honest with yourself about which category you are in. If you are building infrastructure that is genuinely hard to replicate -- keep building. If you are building an application that is essentially a database, UI, and business logic -- you need a new strategy.

The SaaS companies that survive the next five years will be the ones that either move down the stack into infrastructure, move up into AI-native capabilities that go beyond what custom builds can do, or build such strong network effects and data moats that the switching cost remains high. Everyone else is going to face relentless downward pricing pressure as the cost of building alternatives approaches zero.

This is not a reason to panic. It is a reason to adapt. The best SaaS founders we know are already thinking about this and repositioning accordingly.

What This Means for Developers

If you are a developer, this might sound like a threat. It is not. It is the biggest opportunity in a generation.

The demand for custom software is about to explode. Every business that stops paying for SaaS and starts building custom tools needs someone to build and maintain those tools. The role changes -- less writing code from scratch, more directing AI to write code, more architecture and system design, more integration work -- but the demand for technical talent is going up, not down. The developers who learn to work with AI coding tools effectively are going to be the most valuable people in the market.

What Comes Next

We have been thinking about where this goes for the next 3-5 years, and here is our honest assessment.

In the near term (12-18 months), the SaaS replacement trend accelerates. More businesses discover they can build custom tools. More consultancies like ours emerge to help them. SaaS companies start feeling real revenue pressure and respond with price cuts and AI feature additions.

In the medium term (2-3 years), the tools get good enough that many businesses can build and maintain custom software with minimal outside help. As we wrote in our piece on why vibe coding is real, AI coding agents become as common as spreadsheets. The SaaS shakeout begins in earnest -- consolidation, acquisitions, and shutdowns across the application SaaS layer.

In the longer term (3-5 years), the concept of "buying software" starts to feel as outdated as "buying music" does to someone who grew up with streaming. Software becomes something you describe and it gets built, maintained, and updated continuously by AI. The distinction between "off-the-shelf" and "custom" dissolves because everything is custom.

We know that sounds like science fiction. Twenty-one months ago, "build a custom CRM in a weekend" sounded like science fiction too. We just did it three times last month.

The SaaS era is not ending with a bang. It is ending with a thousand small decisions by business owners who realize they have a better option. Those decisions are being made right now, in every industry, in every market. The era of custom AI-powered software built for each business is not coming. It is here.