Ariel Cohen recently shared something that made me stop scrolling: "🚨 BREAKING: OpenAI just dropped the ChatGPT App Store.

This is the iPhone moment for AI. Most founders are about to miss it." That opening line framed the opportunity in a way that cut through the noise for a lot of people in my feed — and for good reason.

As Ariel Cohen pointed out, OpenAI hit $12B ARR in three years, ChatGPT mobile crossed $3B in consumer spend, and analysts expect the AI app market to add $32.3B by 2029 at a 44.9% CAGR. Ariel summed it up perfectly:

That's not "growth."
That's a new economy booting up in real time.

In this post, I want to unpack why Ariel's "ChatGPT App Store" thesis matters so much, especially if you're a founder, operator, or product leader trying to turn AI into actual revenue — not just experiments.

The ChatGPT App Store as AI's iPhone Moment

When Ariel calls this "the iPhone moment for AI," the comparison is intentional. The original iPhone wasn't just a better phone; the App Store turned it into a distribution platform for an entire new software economy. Overnight, small teams could build apps that reached millions of users without signing enterprise deals or buying TV ads.

The ChatGPT App Store has the same structural ingredients:

A huge, engaged user base
A simple way to find and use new capabilities
Built-in trust and payment rails

But there's a twist Ariel highlighted that makes this even more powerful than Apple's ecosystem: ChatGPT already has hundreds of millions of people showing up every week, and those people are already in the middle of tasks, workflows, and buying decisions.

Unlike Apple's App Store, ChatGPT launches with an "unfair advantage": 800M+ weekly users and "agentic commerce" baked in.

In other words, you're not just putting an icon on someone's home screen and hoping they open it. You're inserting your solution into the conversation while the user is literally asking for help.

From Discovery to Purchase Inside One Conversation

Ariel used a phrase that deserves more attention: "agentic commerce." Put simply, it means the assistant doesn't just recommend things; it can do things on the user's behalf.

Instead of searching Google for options, the user asks ChatGPT.
Instead of clicking through landing pages, ChatGPT calls tools or apps.
Instead of filling out forms or checkout fields, the agent completes the transaction.

As Ariel wrote, "the store doesn't just discover apps, it can buy things for people." That collapses the traditional marketing funnel:

Awareness
Consideration
Evaluation
Purchase

into a single, fluid interaction.

That's why he calls this moment a "platform land grab." The bottleneck is no longer building the underlying tech — it's securing your place in the new default workflows users will adopt through ChatGPT.

The Real Competition: Shelf Space, Not Features

One of Ariel Cohen's sharpest points was this:

This is a platform land grab. The winners won't be the best builders. They'll be the ones who lock revenue models first.

Most teams instinctively think, "We just need a better AI product." But on a platform like this, the competition shifts:

From best features to best placement
From "Who has the most funding?" to "Who becomes the default answer in the chat?"

Ariel laid out what first-movers are already capturing:

Brand discovery with zero SEO or paid ads — If ChatGPT can surface your app when a user asks for help, you're skipping the years of content and ad spend it usually takes to rank.
Chat-to-checkout with no landing page or funnel — The agent can explain, answer objections, and then complete a purchase without ever sending the user to your website.
SaaS distribution without acquisition costs — Your app becomes a capability inside ChatGPT, which means usage can grow without your own marketing engine.
"Default choice" lock-in before rankings solidify — Early winners can become the go-to answer in specific niches (e.g., "best AI for X"), making it harder for later entrants to displace them.

This is why McKinsey is calling this a trillion-dollar opportunity: whoever locks in the early default slots will enjoy compounding discovery, usage, and revenue over years — even if their v1 product isn't perfect.

What Founders Should Do in the Next 90 Days

Reading Ariel Cohen's post, I couldn't help but think: the window between "early" and "irrelevant" really is measured in months, not years. So what should you actually do with this insight?

Here's how I'd translate Ariel's argument into a 90-day plan:

1. Define a ChatGPT-native use case

Don't just wrap your existing product as a ChatGPT app. Ask: What does my user already ask ChatGPT for that my product can uniquely solve?

If users are saying, "Help me draft a cold email," "Compare pricing between X and Y," or "Plan a marketing campaign," you want to be the capability ChatGPT invokes to deliver that outcome.

2. Design for agentic workflows, not pages

Traditional UX is about pages and buttons. In this world, UX is about flows inside a conversation.

Map out:

What the user says first
What data the agent needs from them
What decision or action you want the agent to take
How success is confirmed back to the user

Then build your integration so ChatGPT can drive that entire loop with minimal friction.

3. Treat the store listing like high-intent SEO

In a sense, your ChatGPT App Store presence is the new search result page for your niche.

Invest in:

Clear, outcome-driven naming
Concise descriptions that mirror real user prompts
Social proof that builds trust quickly (ratings, case studies, logos)

People browsing the store are not cold traffic; they're already using AI to get things done. Speak their language.

4. Lock in a simple, testable revenue model

Ariel is right that "locking revenue models" is more urgent than perfecting features.

Experiment quickly with:

Usage-based pricing for API-heavy tools
Tiered subscriptions for prosumers and teams
Transaction fees or revenue share where ChatGPT drives the sale

The key is to make it effortless for someone who just had a great in-chat experience to pay you without leaving that context.

5. Instrument everything and iterate fast

Because this ecosystem is so new, nobody has the perfect playbook. What you can do is:

Track which prompts and use cases convert best
Double down on flows that lead to repeat usage
Ruthlessly cut or redesign flows that confuse users

In a land grab, learning velocity beats long-term planning.

Rethinking Distribution in the AI App Era

The deeper message in Ariel Cohen's post is about distribution. Your competitors may not be building better products — as he put it, "They're locking better shelf space."

If you keep thinking of distribution as content, ads, and outbound, you'll miss the shift happening inside AI-native interfaces like ChatGPT. Distribution is becoming embedded:

Inside conversations
Inside workflows
Inside agents that act on behalf of users

Founders who internalize this now will design products that assume the assistant is the primary interface, not the website or mobile app.

Closing Thoughts

Ariel Cohen made the case that the ChatGPT App Store isn't just another channel; it is the starting gun for a new AI economy. With 800M+ weekly users, agentic commerce built in, and a trillion-dollar upside on the table, the question isn't whether this matters. It's whether you'll move fast enough to matter within it.

You don't have to be the biggest team or the most funded startup to win here. But you do have to:

Show up early
Design for conversational, agentic flows
Lock in a revenue model while discovery is still fluid

If you take Ariel's warning seriously, the next few months are less about "experimenting with AI" and more about claiming your shelf space in the ChatGPT economy before someone else does.

This blog post expands on a viral LinkedIn post by Ariel Cohen, I Turn AI into ROI. View the original LinkedIn post →