AI-first or die: the SaaSpocalypse is here

Why the per-seat model is obsolete and how to ride the AI tsunami.

Many people ask me, "Boris, is the AI wave the same thing you’ve encountered with the internet boom working at the first internet provider in Benelux (Eunet/Ping)?" Indeed, I’ve had the privilege to live through several crazy waves of technology-from the late-nineties internet access boom and the rise of Mobile and IoT to the foundational shifts of Cloud and SaaS in 2011 with my own startup Rydoo. Each felt transformative. But what I now see happening with AI is something on a completely different scale.

Of course, the crucial difference is speed. The internet took years to become mainstream. Cloud adoption took years before corporations started using it at scale. AI just reinvents itself in months-sometimes in weeks. What once required an eighteen-month planning cycle now unfolds before the next board meeting.

This isn’t evolution. It’s a tsunami, and it’s happening now.

At Pitchdrive, this shift is the core of our work: finding and funding startups that can tear down established SaaS markets and rebuild them on AI-First foundations. This isn't a strategy choice. It’s survival for many existing SaaS startups in the world. I will try to outline here why this is going so fast and give our view on how to cope with this revolution in 7 lessons learned in the last 6 months.

The hyper-speed engine fueling AI startups

I see two main forces accelerating AI adoption at a pace we’ve never seen before:
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1. Enterprises are going all-in with AI behind the scenes‍

This isn’t just C-level decision-making anymore. Boards and shareholders-private equity included-are demanding end-to-end AI integration with immediate and massive operating cost reductions. Some concrete results are already proving this thesis in our own portfolio:

• With just four people, a Pitchdrive startup is signing multi-million ARR deals in the US by replacing entire logistics processes and call centers that once required thousands of employees-with AI.
• A 6-man band in our portfolio closes contracts with the biggest ecommerce companies in the world, gaining full control over manual courier claims thanks to AI.
• A 10-person startup completely automates how consultants answer emails and wins hours back per day per employee, and is growing at a high pace.
• A London-based startup is orchestrating hundreds of agents, enabling employees to work from a single prompt and deliver 200% more output - with humans only needed for 20% of critical decision points.
• Another, just 20 people strong, is helping a multi-billion-dollar enterprise expand operating margins by 40% in a matter of months by managing and checking all documents of visitors by AI.

Sales cycles that once dragged on for a year now close in weeks, all driven by enormous gains on operating margins. Big companies are not telling this publicly (yet), but we see it just happening in front of us. The academic world and mainstream media seems only interested in what they see, but not what's happening under the iceberg.

2. Bottom-up AI adoption is just exploding (= shadow AI)‍

Employees aren’t waiting for management. Today, 90% already use tools like ChatGPT at work - yet only 40% of companies have official subscriptions. This bottom-up adoption acts as a magnet, pulling AI into every department and forcing leadership to catch up. Look to one of the fastest-growing startups in the world like Lovable; they enable product teams to spin up working software in hours instead of weeks, bypassing traditional IT bottlenecks. A product like Cursor gives developers an AI-augmented coding environment that can 10x their productivity, quickly becoming the default tool engineers demand. Across functions-from compliance to sales-employees are pushing AI into workflows long before management formally approves it.

Together, these forces create an unprecedented growth engine for startups, resulting in Q2T3 growth expectations for founders: quadruple for 2 years, then triple for 3. In other words: 80–100x growth in just 5 years. 🚀 That’s not a business plan; that’s a rocket launch countdown.
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Why SaaS must pivot now

The old SaaS playbook-charging per seat, selling features, scaling department by department-is collapsing. AI changes everything: it scales per workflow, not per human user. A single AI agent can deliver the output of dozens of employees. Instead of 1,000 seats at €50/month, enterprises are ready to pay €200k/month for an AI-First system that automates the end-to-end process. This means founders must rebuild from scratch. Investors must focus on AI-First bets. And enterprises must commit fully. Delay equals disruption.

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Our 7 non-negotiable insights for (SaaS) founders

Here are the harsh truths for founders navigating this AI-First world:
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1. The Death of the subscription per-seat model

The problem: Traditional SaaS pricing (per-user/per-seat) is collapsing. AI agents and co-pilots enable a single augmented user to achieve the output of ten. Customers won't pay for ten seats.
The mandate: You must pivot immediately to a consumption, outcome, or value-based pricing model where cost aligns with the superior results delivered by the AI, not the number of human logins.
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2. The AI-native competitor threat

The threat: Startups are building entire products AI-First-no legacy code, no entrenched pricing. They will automate the entire workflow end-to-end, solving your customer's problem faster, cheaper, and with superior intelligence.
The risk: Waiting means handing them your market share.
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3. Customers demand outcomes, not features

The shift: Buyers want a measurable, guaranteed business outcome. AI shifts the value proposition to "Here is a guaranteed result."
The advantage: An AI-First approach allows you to sell predictive results (e.g., “20% more operating margin”, “50% reduction in churn,” “2X sales forecasting accuracy”)-a value proposition legacy systems cannot match without a deep AI core.
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4. Your data Is decaying without intelligence

The reality: Your proprietary data is passive and static in a legacy system-it's a liability, not an asset.
The fix: An AI-First architecture treats data as a dynamic, competitive asset. It continuously learns, creating proprietary models and network effects that grow smarter with every interaction, building an impossible moat for competitors.
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5. The end of the GUI-centric workflow

The future: The future is Agentic AI-autonomous systems that bypass your user interface (UI) to complete tasks directly via APIs.
The necessity: If your product isn't architected with agent-friendly APIs and designed for "Zero-UI" orchestration, your customer's own AI tools will simply route around your application, leaving you as an expensive, irrelevant data silo.
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6. The urgency of cost and margin

The economics: AI-First companies use AI to automate their own internal operations (support, code generation like a cursor, infra optimization).
The impact: This lowers their marginal cost of service, granting them superior gross margins and the ability to aggressively undercut your pricing.
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7. Talent and culture warring against you

The crisis: The best AI and ML talent will refuse to work on legacy-only platforms. You also don’t need big teams. A decent multi million ARR startup can easily run on 4 people today..
The solution: The pivot must be CEO-driven to rewire your engineering culture, empower data teams, and signal to the market that your company is where the most cutting-edge work is happening.  You need small teams that eat AI like cookies every day not only in product development but also in operations, sales, marketing,....We only fund companies committed to this technical and cultural transformation.
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My Takeaway

AI is not a feature you can tack on. It is the foundation on which the next generation of market leaders will be built like never before.

• Founders: rebuild AI-First, or risk irrelevance.
• Investors: back AI-First, or be left holding legacy.
• Enterprises: embed AI end-to-end, or watch competitors lap you.

​I haven't even touched on the broader macroeconomic effects of this AI transformation but one thing is sure: this will impact all of us in the coming years. Society will need to come up with solutions, but what they are will require leadership, deep understanding of the situation, and quick actions on all levels.

Fasten your seatbelts please , the window of opportunity in the next 12 months for native AI startups is limitless, they aren’t just on the track-they’re already lapping the competition at lightening speed.