I'm going to say something that pisses off a lot of founders: freemium is a drug. It feels incredible for the first six months. Your user numbers explode. VCs are blowing up your phone. You feel like you're on top of the world. But it's a high that never lasts. And the hangover is brutal: spiraling cloud bills, a support team drowning in tickets from non-paying users, and a business that's fundamentally, structurally broken.
I've seen this movie before. I've seen it as a founder with RemoteTeam, as an advisor to startups that got hooked on the "free" crack, and as an investor in over 200 companies. And let me tell you, it's a particularly lethal game when you're playing with AI.
The Siren Song of the Free Lunch
Look, I get the appeal. Freemium feels like a cheat code for growth. It drops your customer acquisition cost to zero, theoretically. It gets your product in front of tons of people and sparks that coveted word-of-mouth flywheel. For a hot minute, it was the undisputed playbook for SaaS. And yeah, it worked for companies like Slack and Dropbox. They became giants on the back of a free plan.
But that was a different era. The world has changed. The easy money is gone, and the idea that you can just convert a tiny fraction of free users into a massive business is a fantasy. For AI companies, it's not just a fantasy—it's a ticking time bomb.
I learned this the hard way at RemoteTeam. We were pumped about our product and wanted to get it into everyone's hands. So we launched with a super generous free tier. The sign-ups were insane. Thousands in the first few weeks. We thought we were killing it. Then the bills came due. Our AWS bill started to look like a phone number. Our support team was completely swamped by people who would never, ever pay us. And our free-to-paid conversion rate? It was a joke. Something like 0.5%.
We were torching cash to acquire users who were actively costing us money. It was all vanity, no sanity. We were on a collision course with bankruptcy, and it taught me a lesson I'll never forget: free is never free.
The Hidden, Astronomical Costs of Freemium in AI
The core problem with freemium is that it pretends all users are created equal. They're not. A tiny sliver of your users—the power users—will drive the vast majority of your costs. In the world of AI, those costs aren't just high; they're astronomical.
Think about it. Every single API call, every inference, every time a free user plays with your AI model, it's a real, hard cost to you. You're paying for the GPUs. You're paying for the cloud infrastructure. You're paying for the model provider. Those costs stack up with terrifying speed.
I've looked under the hood of AI companies with millions of free users, and they were literally losing money on every single one. They were trapped. They couldn't kill the free plan because it was their only user acquisition channel. But they couldn't afford to keep it because the unit economics were a death spiral.
It's the classic tail wagging the dog. And it's a one-way ticket to the startup graveyard.
Let's get specific. Here's what a "free" user really costs you:
- GPU and Infrastructure Costs: This is the monster under the bed. Running AI models is brutally expensive. Every free user is a direct hit to your gross margins.
- Support Costs: Free users don't just use your product; they need help. And they can be shockingly demanding for someone who isn't paying you a dime.
- Opportunity Cost: Every dollar and every engineering hour you burn on a free user is a dollar and an hour you can't invest in your actual, paying customers.
- Product Devaluation: This one is subtle but deadly. Freemium trains your users to believe your product has no value. It sets the price anchor at zero, making it incredibly hard to ever convince them to pay up.
The Grown-Up Alternative: Usage-Based Pricing
So if freemium is a trap, what's the answer? For any AI SaaS, I am a massive advocate for usage-based pricing.
It's not complicated. You pay for what you use. It's a fair, transparent, and sustainable model that directly ties the price a customer pays to the value they get. It's the only model that makes sense for AI.
With usage-based pricing, you're not just giving away the farm. You can still offer a free trial or a certain number of free credits to let people kick the tires. But you're establishing from day one that this is a professional tool with real costs and real value. It encourages people to use your product seriously, not just play around.
And it's a model that's proven to work. Look at the foundational companies in the AI space: OpenAI, Anthropic, Scale AI. I'm an investor in all three. They are all built on usage-based pricing. They are all monsters.
Sure, implementing it takes work. You need to actually understand your cost of goods sold (COGS). You need to instrument your product to track usage accurately. But it's the necessary work of building a real business, not a hobby project.
How to Build a Moat When AI is a Commodity
I can hear the question already. "But Sahin, if I don't have a free plan, how will anyone ever discover my product?"
That's the wrong question. The right question is: "How do I build a product so good that people are willing to pay for it?"
In a world where the underlying AI models are becoming commoditized—available to anyone with an API key—your moat isn't the model itself. It's everything you build around it.
Your moat is the workflow. It's the user experience. It's the proprietary data you have that nobody else does. It's the brand you build that stands for something.
Here's where to focus:
- Proprietary Data: Do you have a unique, private dataset you can use for fine-tuning? That can create a model that's demonstrably better for a specific niche than any generic foundation model.
- Network Effects: Can you build a product that gets more valuable for every user that joins? Think of collaboration features or data network effects. That's a classic, powerful moat.
- Brand & Trust: In a world of black-box AI, being the brand that people trust is a massive advantage. If customers know you'll deliver, that you'll be a reliable partner, they'll choose you even if a cheaper, no-name alternative pops up.
The Bottom Line
Freemium is a trap for AI SaaS. It's a relic of a bygone era that simply doesn't map to the economic reality of this technology. It's a siren song that will lure your startup onto the rocks.
If you're building in this space, I'm begging you: just say no. Resist the temptation of vanity metrics and easy sign-ups. Focus on building something people will actually pay for. Build a real, sustainable business with real unit economics. Build a moat that goes beyond the algorithm.
It's not the easy way. But it's the only way to win.
Frequently Asked Questions
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.