Every second startup in India right now claims to be "an AI company." Open a pitch deck, scroll a feed, sit in a demo day — the phrase is everywhere. And most of the time, what's behind it is a thin layer of prompt engineering wrapped around someone else's model. That's not a company. That's a feature wearing a company's clothes.

We say this as people who build with AI every day. We're not anti-AI — Mira, our first product, would be impossible without it. But the way the word is being used right now obscures the single most important distinction in this entire wave of technology: the difference between AI as a product and AI as a feature.

AI is electricity. Nobody's an "electricity company" — they're a company that does something with it.

The wrapper trap

Here's the uncomfortable test. If a major model provider shipped a slightly better default experience next quarter, would your product still have a reason to exist? For a huge number of "AI startups," the honest answer is no. They've built a nicer text box on top of a capability that is rapidly becoming free, commoditized, and built into every platform you already use.

That's the wrapper trap. It feels like progress because the demo is impressive on day one. But you have no moat, no proprietary advantage, and no defensibility — you're renting your entire value proposition from a company that could replace you with a checkbox. The model is doing the work, and the model isn't yours.

AI as a feature vs. AI as a product

The distinction isn't about how much AI you use. It's about where the value lives.

AI as a feature

The AI is the product. Take it away and there's nothing left. The user is essentially talking to a model with your branding on it. Your differentiation is a prompt, and prompts are not defensible.

AI as a product

The AI is one component inside something larger that solves a complete problem. There's workflow, integration, judgment, memory, and accountability around it. The intelligence matters — but so does everything you've built so the intelligence can actually do a job in the real world. Take the model away and swap in another, and the product still stands, because the model was never the whole point.

How we think about it with Mira

Mira is our AI accounts representative. She recovers overdue invoices on WhatsApp in your exact brand voice. It would be easy to describe her as "an AI that sends payment reminders" — and easy to build that as a wrapper. But that's not the product.

The product is everything around the intelligence. Mira has to learn a specific business's tone and speak like a real person from that company. She has to read a client's payment history and decide when to be firm and when to be flexible. She has to manage an entire conversation — first touch, follow-up, objection handling, partial-payment acknowledgement, escalation — not fire a single message and stop at "hello." She has to do all of this reliably, day after day, with money on the line.

The model is the engine. The product is the car, the road, the destination, and the promise that you'll actually get there. A better engine ships next year? Great — we'll drop it in. The reason to use Mira doesn't move.

How to build with AI anyway

None of this means avoid AI. It means use it the way you'd use any powerful tool — in service of a problem you understand deeply. A few principles we hold to:

  • Start with the problem, not the technology. The first question is still "why doesn't this already exist?" — not "where can we put an LLM?"
  • Own the part that compounds. Your data, your workflows, your domain judgment, your relationship with the customer. Those get more valuable over time. A prompt doesn't.
  • Treat the model as replaceable. If your architecture assumes one specific provider forever, you've built a dependency, not a product.
  • Be honest about the wrapper test. If a default feature could kill you, you don't have a company yet — you have a head start. Use it to build the thing that can't be copied with a checkbox.

AI is the most powerful tool builders have been handed in a generation. But a tool builds nothing on its own. The companies that matter from this era won't be the ones that used AI — almost everyone will. They'll be the ones that used it to finally build something that should exist but didn't.

That's the only kind of product worth building. Talk to us if you're building one.