For years, we've watched major platforms like Shopify, HubSpot, and Salesforce expand relentlessly into adjacent territories — payments, marketing, fulfillment, customer service. The prevailing wisdom was simple: businesses would consolidate onto these sprawling platforms because switching costs were too high and integration headaches too painful to maintain multiple specialized tools.

But two forces are quietly dismantling this assumption. First, switching costs are collapsing. Modern APIs, cloud-native architectures, and improved data portability have transformed what used to require months-long IT projects into straightforward migrations. Second — and far more revolutionary — AI is fundamentally changing what "simple" platforms can do.

The result? A complete inversion of the consolidation playbook. Instead of businesses grudgingly accepting the compromises of all-in-one platforms, they're discovering they can combine best-in-class focused tools with AI assistance to create setups that are simultaneously simpler, more powerful, and more flexible than complex enterprise software.

The technical foundation of this shift

The drop in switching costs stems from several converging factors: standardized APIs, cloud-native architectures, improved data portability standards, and the rise of integration platforms. What used to require months of IT projects now happens with a few clicks or API calls.

The platform expansion paradox

Companies like Shopify, HubSpot, and Salesforce are expanding far beyond their original value propositions — but this creates vulnerability. As they stretch into adjacent territories, they're competing with specialized players who may offer superior solutions in those specific areas, while their core differentiation gets diluted.

The vertical convergence phenomenon

You're seeing software categories that were once distinct, starting to overlap significantly. Project management tools add CRM features, CRM tools add marketing automation, marketing tools add e-commerce capabilities. This convergence is forcing businesses to choose between "good enough" integrated solutions versus best-in-class specialized tools.

Strategic implications

For businesses, this means procurement strategies are shifting from "platform consolidation at any cost" toward "best tool for each job with easy integration." For vendors, it means the moat of switching costs is evaporating, making product excellence and innovation more critical than ever.

Some examples

Here are some concrete examples that illustrate this trend.

Shopify has moved from e-commerce platform into payments (Shopify Payments), fulfillment (Shopify Fulfillment Network), marketing (Shopify Email, social media tools), and even business lending. But specialized competitors are eating into these expanded areas:

The switching cost drop: modern headless commerce solutions like Medusa or commercetools make it easier to migrate store functionality while keeping existing integrations.

HubSpot expanded from marketing automation into sales CRM, customer service, operations hubs, and even website building. Yet companies are increasingly mixing and matching:

Notion expanded into project management, Slack added workflow automation, Asana added messaging features. But teams are finding optimal combinations like:

QuickBooks, FreshBooks, and Wave all expanded into payments, payroll, and banking. But businesses are choosing:

The key insight: companies have been realizing they can get 90% of the integration benefits with 120% of the functionality by thoughtfully combining best-in-class tools rather than accepting the compromises of platform expansion.

But that's not the only shift going on…

AI is fundamentally reshaping this platform consolidation equation. The AI layer is creating a new type of "Swiss Army knife" effect that's different from traditional feature expansion.

Let's take Notion as a particularly striking example. Before AI, Notion was limited by its interface and workflow constraints. But now:

Model Context Protocol is a game-changer here. Instead of platforms building every feature internally, they can become AI-extensible. This means:

Real-world impact examples

I'm seeing businesses make moves like:

The "AI-Native" advantage

Platforms that were built with AI integration in mind (like Notion's recent AI features) suddenly have massive advantages over legacy platforms that are retrofitting AI capabilities. They can offer 80% of the functionality at 20% of the cost.

This creates a fascinating dynamic where the "switching cost drop" I mentioned isn't just about easier migration — it's about AI making simpler platforms suddenly viable alternatives to complex enterprise software.

I've just dropped Mailchimp, Podio, multiple web hosting providers in favor of Notion and Substack as an example.

What's fascinating about my example is how it demonstrates the "AI-amplified simplicity" principle. I've essentially gone from:

To:

Substack is particularly interesting because it's not trying to be everything to everyone — it's just really good at email + publishing, but AI makes that foundation incredibly powerful. You can now:

What makes this trend so powerful is that once I've simplified my stack, adding AI capabilities becomes much easier. Instead of trying to get AI to work across 5 different platforms with different APIs, I'm now working within 1-2 environments that are designed to be extensible.

And exactly here we've hit on something important: the "overengineering vs. artificial constraints" problem that plagues so many SaaS platforms.

Dysfunctional SaaS: the Mailchimp trap

Mailchimp is a perfect example of this dysfunction:

Meanwhile, Substack gives you exactly what you need — clean email delivery, audience growth tools, and monetization options — without artificial limits or feature bloat.

AI as the flexibility layer

AI acts as this incredible "customization engine" on top of simpler platforms. Instead of Mailchimp's pre-built automation sequences that may or may not fit your use case, you can:

The "right-sized" solution

My setup demonstrates what I think will become the dominant pattern:

This is why legacy SaaS companies should be nervous. Their entire pricing model is based on feature differentiation and usage tiers that AI is making obsolete.

Development pace is absolutely wild right now. Before you know it it's added to the mix (or you add it yourself). What used to take months or years of platform development cycles is happening in weeks.

This is something that traditional software companies aren't equipped to handle. When you hit a limitation in your Notion+Substack setup, you don't have to:

Instead, you can literally just ask Claude "how do I build X in Notion?" and have a working solution in an hour.

This creates a massive competitive disadvantage for traditional SaaS:

I'm seeing this pattern everywhere now. Someone will say "I wish Notion could do X" and within days there's either:

Innovation acceleration

What's really crazy is how this creates a feedback loop. As more people consolidate onto flexible platforms + AI, those platforms get more investment, better AI integration, and faster development cycles. Meanwhile, legacy platforms are stuck maintaining complex feature sets that fewer people actually need.

We're essentially riding the wave of this acceleration while traditional software companies are trying to figure out how to respond to a fundamentally different paradigm.