The Dot-Com Test: A 30-Second Framework for AI Tool Decisions

I use AI tools every day. I also ignore most of what gets launched. Over the past year I've developed a simple filter — three questions I run before I spend money or time on anything new. I call it The Dot-Com Test. It takes 30 seconds.

Here's why it works, where it comes from, and how to use it before your next AI purchase.

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The Three Questions

Before you buy, renew, or recommend any AI tool, ask:

1. Does it solve a real problem today? Not next quarter. Not "when the feature ships." Today.
2. Would you still pay for it if the hype disappeared tomorrow? Strip the AI label. Is this still a product you need?
3. Is it faster or cheaper than the alternative right now? Not in theory. In your actual workflow.

Yes to all three = infrastructure. This is a tool your business needs. Buy it.

No to any = speculation. You're buying a lottery ticket dressed up as a software subscription.

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Where This Comes From

It was 1999. The internet was going to change everything. And it did. But not before it destroyed companies that confused hype with value.

Pets.com raised $82.5 million. Their Super Bowl ad was iconic. They sold pet food online at a loss and called it "internet strategy." They were dead within a year of their IPO.

Amazon was also an "internet company." But Amazon solved a real logistics problem. People actually wanted to buy books without driving to a store. The internet made that faster and cheaper. Real problem. Real solution. Real value.

Both were "internet companies." One passed the test. One didn't.

The companies that survived the dot-com crash had one thing in common: they solved problems people would pay for on a boring Tuesday. No hype needed.

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Why Most AI Tools Fail The Test

No real problem

"It uses AI to summarize your meetings."

I go to meetings where I actually listen and participate. I don't need a bot generating notes I'll never read. If something is important enough to remember, I write it down myself. If it's not — a summary won't change that.

The real problem here isn't "I need better notes." It's "I'm in meetings that don't require my attention." An AI summary tool doesn't fix that. It just makes a bad habit more comfortable.

Hype-dependent value

"AI-powered project management." "AI-powered CRM." "AI-powered email."

Strip the AI label. What's left? Usually a worse version of a tool that already exists, with a higher price tag and a waitlist. If the product can't stand on its own without "AI" in the pitch deck, it's speculation.

Slower or more expensive

"It automates your invoicing with AI."

Does it process invoices faster than your current system? Does it cost less? If it takes your team two hours to set up, breaks on edge cases, and costs 3x what your current tool charges, you're paying an AI premium for worse results. Not in six months. Right now.

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Tools That Pass The Dot-Com Test

Not every AI tool fails. The ones that pass share characteristics:

They replace manual work that was already painful. I built a document processing pipeline for a dental clinic that extracts patient data from lab orders, X-rays, and invoices. Before: a staff member spent hours daily on manual data entry. After: automated extraction with human review only on edge cases. No viral demo. Just hours saved every day.

They work today, not next quarter. The pipeline I built didn't need a roadmap to become useful. It processed its first real document on day one. No "coming soon." No beta waitlist. Real results on day one.

They survive the "boring Tuesday" test. On a regular workday, with no conference hype, no LinkedIn posts about innovation, no pressure to "not fall behind" — you'd still use this tool. Because it makes your work faster, cheaper, or both.

Here's what actually passes in my daily work: AI agents that scan team chats and surface things I'd otherwise miss. Automated task progress updates so I'm not chasing people for status. Code pipeline monitoring that catches and resolves CI/CD failures before they block the team. Document processing that eliminated manual data entry. None of these went viral. All of them solve problems I had before AI existed — they just solve them faster now.

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How to Run It in Your Organization

Next time someone proposes an AI tool, run the test in your next meeting. Three questions. Out loud.

1. "What specific problem does this solve today?" Not "what could it do." What does it do.
2. "If we removed the AI label, would we still buy this?" This question alone kills 60% of proposals.
3. "Is this faster or cheaper than what we already have?" Measure it. Don't guess.

If the answers are clear yeses, move fast. Infrastructure advantages compound.

If any answer is shaky, you're speculating. That's fine if you know it. It's expensive if you don't.

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The 30-Second Version

Every major technology has a bubble phase. The internet had one. AI is having one.

The bubble will pop. The technology will stay.

Your job isn't to avoid AI. It's to avoid the AI equivalent of Pets.com.

The Dot-Com Test helps you tell the difference. Three questions. 30 seconds. Could save you six figures.

Run it before your next purchase.

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I build Business Operating Systems -- SOPs backed by software, executed by AI agents. Every tool in my stack passes The Dot-Com Test. If you want help evaluating which AI tools are infrastructure vs. speculation for your business, let's talk.