The AI Boom Hasn't Started — Here’s Why That Matters

Marc Andreessen is bullish on AI. Of course he is. But his recent take stopped me: the real AI boom hasn’t started yet.

Most people hear that and think "more hype." I hear something different. He’s saying the infrastructure wave is still being built. The application wave hasn’t even begun.

If you’ve been watching the AI space, you know the pattern. First comes the platform shift (cloud, mobile, AI models). Then the buildout of tools and plumbing. Then—then—the real applications that change how businesses work.

We’re still in the plumbing phase.

Why that’s good news for founders

When the platform is new, everyone rushes to copy. Chatbots on top of GPT-4. Copilot wrappers. These are features, not companies.

The real durable advantage comes when the plumbing becomes invisible. When you don’t think about the model, you think about the workflow. That’s where long-term value lives.

Think about the internet. Early winners were things like browsers and email. The real winners came a decade later: SaaS, e-commerce, social platforms. They didn’t care about TCP/IP. They cared about solving a customer problem.

Same with AI. The models are getting commoditized fast. The real money is in systems that use AI to remove a bottleneck in an existing business process. Compliance checks. Packaging design validation. Supply chain exceptions.

What a founder should actually do

Don’t build another wrapper. Don’t chase the benchmark leaderboard.

Instead:

• Pick a domain you know inside out.
• Find the task that takes your customers 5 hours that could be done in 5 minutes with AI.
• Build a system around that task. Own the workflow, not the model.
• Stack the learning. Every year the models get cheaper and better. If your workflow gets smarter with each new model, you get a compounding advantage.

That’s the play. Not waiting for the boom to start, but preparing for it while everyone else is still hyping the last demo.

TL;DR

• The AI boom is still early. Most real applications haven’t been built yet.
• Models are becoming a commodity. Durability comes from workflow and domain expertise.
• Pick a specific customer bottleneck. Build a system that uses AI to remove it.
• Stack learning across model generations to create a compounding advantage.
• Ignore the hype. Focus on the customer problem that AI can solve cheaper and faster.