You've Seen This Before (You Just Don't Know It Yet)

What six technology transitions taught one person about surviving the seventh

There’s a moment early in every technology shift that looks exactly the same. I’ve stood in it six times now — semiconductors, PCs, networking, mobile, crypto, AI — and I want to tell you what the moment feels like, because you might be standing in it right now.

It doesn’t feel like a revolution. It feels like a Wednesday.

The Warehouse

In early 2001, I walked into a warehouse belonging to a major networking company to pull some memory modules off a shelf. This company was the darling of Wall Street — one of the most valuable on the planet. Everybody in the supply chain was double-ordering and triple-ordering because they were terrified of shortages. The entire industry narrative was that demand was through the roof and nobody could build fast enough.

The warehouse looked like Costco. Pallets of chips stacked on industrial racking as far as I could see.

I found the program manager who’d been calling me for three days straight, frantic about being “lines down” on their flagship product. I sorted through pallets and found a couple hundred known-good units. Brought them over and asked how many he needed.

“About ten. But we might need another twenty next week.”

I stood there trying to process that. Their hottest product. Middle of the boom. The entire world believed these things were flying out the door. And they needed ten.

I drove home that night and told my wife something bad was coming. Within months, the dot-com bubble burst. That networking company alone wrote off billions in excess inventory that year.

The signal was sitting right there on pallets in a warehouse in Silicon Valley. But almost nobody was standing in that warehouse. They were reading the same analyst reports everyone else was reading, believing the same narrative everyone else was believing.

The Breakfast

A couple years later, I was at a semiconductor company trying to win a piece of business worth eight figures that everyone told me was impossible. A competitor had owned this account for years. The customer had never used our chips. Our newest chip wasn’t even in production yet. My own management thought the odds were single digits.

Here’s what I had: the customer’s actual circuit boards. I’d studied them until I could draw their entire architecture from memory — every chip, every connection, every cost. I knew their system better than most people inside their own company.

I set up a breakfast meeting with their head of engineering. One on one, outside the office. I stepped him through his own architecture with the cost of every component, then showed him what it would look like redesigned with our parts — faster, cheaper, smaller.

He stared at the diagrams for a while and asked how I’d figured all this out. I told him that was in the past and what I really needed to know was whether the proposal made sense.

He slowly came around. “If these chips were in production today at these prices and capabilities, you would have a good case and we would be foolish not to consider it.”

That was all I needed. Months of maneuvering later — including a meeting between the two CEOs that I’d scripted, an engineer who built us a working test version on the spot, and a senior executive who told me afterward he’d thought there was a coin-flip chance he’d be fired for approving it — we won the whole thing.

The competitor’s sales rep, who had her own badge at the customer site and walked the halls like she owned the place, didn’t see it coming until the design kick-off meeting.

The Shutdown

Fast forward to 2025. I’m looking at the math on a different business — a consumer products company I’d built over close to two decades. Seven-figure annual revenue, good margins, a small team, a couple of warehouse locations. We sold through a major e-commerce platform.

The end didn’t come from one direction. It came from five.

First, the platform launched competing products under their own brand. Then a foreign mega-distributor started selling knockoffs at half our price. Then the platform let that competitor advertise directly on our product listing. Then the overseas factories that had been our suppliers figured out they could sell direct on the platform themselves, cutting us out entirely. Then tariffs hit — but structured in a way that hurt us more than the foreign factories, because tariffs are calculated on landed cost, and their landed cost on a fraction of our base was a fraction of ours.

The policy designed to protect domestic businesses was actually accelerating their destruction.

Last shipment arrived in early 2025. We’re shutting down. Buildings up for lease. Liquidators coming.

What This Actually Means for You

I’m telling you these three stories because they contain the same pattern, and that pattern is playing out right now with AI.

The warehouse lesson: The gap between the narrative and the reality is where the danger lives. In 2001, the narrative was unlimited growth. The reality was sitting on pallets nobody was counting. Right now, the narrative about AI is split between “it will solve everything” and “it will destroy everything.” Both are wrong. The reality is specific, measurable, and visible — if you’re willing to go look at it yourself instead of reading what everyone else is reading.

The breakfast lesson: Deep knowledge of how things actually work beats surface-level familiarity every time. I didn’t win that design by having better chips. I won it by understanding the customer’s system better than they did. The same principle applies to AI: the people who understand what these tools actually do — not the marketing version, the actual mechanics — will have leverage that the surface users never will. And right now, most people are surface users.

The shutdown lesson: Platforms welcome you, learn from you, then compete with you. This is not a new pattern. It has played out in semiconductors, retail, media, and every other industry where a platform sits between the producer and the customer. AI platforms will do the same thing. The question is whether you’re the one building on the platform, the one who owns the platform, or the one who understands the pattern well enough to position accordingly.

The Actual Opportunity

Here’s what I’ve learned from standing in the same spot six times: the people who come through technology transitions well are not the ones who predict the future correctly. They’re the ones who see the present clearly.

Seeing clearly means three things.

First, go look at the warehouse. Don’t take the analyst’s word for it. Don’t take the headline’s word for it. Find the primary data — the actual metrics, the real customer behavior, the unfiltered results — and count the pallets yourself.

Second, learn the architecture. You don’t need to become a programmer. But you need to understand what AI tools are actually doing when you use them, the same way you need to understand what a financial advisor is actually doing with your money. Not the marketing explanation. The mechanical one.

Third, watch for the platform pattern. If you’re building a business, a skill set, or a career that depends entirely on one platform — whether that’s a search giant, a cloud provider, or any AI company — you’re standing exactly where I was standing in 2024. The platform is not your enemy. But the platform is not your friend. The platform is a business that will optimize for its own survival, and your interests align with theirs only until they don’t.

I’m not selling panic. I’m not selling utopia. I’ve just been through this before — six times — and the pattern is always the same. The technology changes. The human behavior doesn’t.

If you’re in your fifties or sixties and AI just showed up at your company, you’re not behind. You’re experienced. You’ve seen systems change before, even if you didn’t call it a technology transition at the time. That experience is worth more than any twenty-five-year-old’s comfort with the latest chat interface.

Trust your experience. But update your inputs.

This is part of an ongoing series about navigating the AI transition from someone who has been through six technology shifts in thirty years of business. No jargon, no hype — just pattern recognition from the inside.