It's Alberto.

Quick question before we dive in.

How many times this week did you hear someone talk about which AI model is smarter?

Probably a lot. Now here's a question you almost definitely didn't hear: where does the electricity come from?

That's the story nobody's telling. And it's the one that matters most to your portfolio right now.

Here's the situation.

Big Tech is planning to build 44 gigawatts of AI data center infrastructure. That's enough to power roughly 44 million homes.

The problem? Only 25 gigawatts of power are actually coming online in the next three years.

That's a 19-gigawatt gap. A gap that OpenAI, Microsoft, Google, and Amazon are all racing toward simultaneously — and nobody has a clean answer for how to close it.

Jensen Huang said it's the main obstacle to AI expansion. Satya Nadella said the same thing. Even Virginia, the most data-center-dense state in the US, nearly had a blackout last year when 60 data centers dropped off the grid at once.

This isn't a future problem. It's happening now.

Here's the part that hits close to home.

One Ohio family saw their electric bill jump 60% in a single year. Their neighbor? 130 new data centers in Central Ohio.

PJM Interconnection — the grid operator serving 65 million Americans across 13 states — is already projecting a 6-gigawatt shortfall in reliability requirements by 2027.

And here's the kicker: when utilities expand the grid to feed data centers, everyone shares the cost. Not just the tech companies.

So while OpenAI is promising to "pay its own way" on energy after Trump pressure, your utility bill is already quietly absorbing the burden of the AI arms race. Data center energy demand is projected to grow from 4.4% of all US electricity today to up to 12% by 2028 — a near tripling in just four years.

The grid, by the way, was largely built in the 1950s and 70s. About 70% of it is approaching the end of its life cycle.

Here's a private markets lesson that Wall Street's been ignoring.

Every major technology wave creates two kinds of winners. The companies building the shiny thing everyone talks about — and the companies building the infrastructure that makes the shiny thing possible.

In the gold rush, it wasn't the miners who got rich. It was the people selling pickaxes and jeans.

In the internet boom, it wasn't just Amazon and Google. It was Akamai (content delivery), Cisco (networking), and the data center operators powering it all.

AI is following the same playbook. And right now, the infrastructure layer is massively underpriced.

This week, a startup called C2i Semiconductors quietly raised $15M from Peak XV Partners (the firm that split from Sequoia). They're building one thing: a chip that fixes how power moves from the grid to a GPU.

Right now, 15–20% of all electricity fed into a data center is lost just converting high-voltage power down to something GPUs can use. That's like pouring 20 cents of every dollar straight down the drain. C2i's solution cuts that loss by around 10% — saving 100 kilowatts for every megawatt consumed.

At hyperscale? That's worth billions. Goldman Sachs estimates data center power demand grows 175% by 2030. Deloitte says it grows 30x by 2035.

C2i is two years old. It's raised $19M total. The chips ship for customer testing in April.

That's the picks-and-shovels play. That's where the smart private market money is going right now — into energy infrastructure, power efficiency, grid tech, and the startups solving the bottlenecks nobody's Instagramming about.

Let's zoom out and connect the dots.

The AI infrastructure wave is producing three categories of investment opportunity that most retail investors haven't found yet:

1. Power efficiency startups (like C2i) — Companies fixing how electricity moves inside data centers. Tiny team, massive addressable market, zero consumer competition.

2. Energy generation — Nuclear SMRs, fusion plays, behind-the-meter natural gas projects. Microsoft just restarted Three Mile Island. Google signed the world's first nuclear energy deal for AI. The demand is forcing Big Tech to become energy companies.

3. Grid infrastructure — Transmission upgrades, smart grid software, battery storage. The US grid is aging and underpowered, and AI just lit a fire under the urgency. The Belfer Center at Harvard published a full report on this two weeks ago calling it "a watershed moment."

The pattern from every major tech cycle? The infrastructure companies get funded first, grow quietly, and go public just as the consumer wave peaks.

In the internet era, that was Cisco (1990 → $500B at peak). Akamai. Equinix. Companies your grandparents probably never heard of — until they were some of the biggest on the planet.

The same playbook is running right now. The companies solving AI's power problem are raising early rounds. Most of them aren't names you'll read about in TechCrunch.

That's the opportunity.

What's Different This Time

Here's where it gets interesting.

These three companies represent something we haven't seen before: They're going public while still growing at venture-scale rates.

They're not going public because they need capital. They're going public because:

But that doesn't mean you should wait for the IPO to invest.

In fact, it means the exact opposite.

We partner with 50+ active venture capital firms to bring you access to pre-IPO opportunities that most investors will never see.

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While everyone's waiting for the IPO announcements, here's what's actually happening:

SpaceX shares trade regularly on secondary markets. Right now, they're going for around the $800B valuation, half of the expected IPO price.

Anthropic secondaries are happening through VC fund partnerships at valuations 20-30% below the IPO target.

OpenAI? Same story. Employees and early investors are selling stakes to growth funds and family offices at discounts to the eventual IPO valuation.

This is the window.

Not when CNBC announces the IPO.
Not when your broker sends you an email alert.
Not when your coworker texts you "Should I buy?"

Right now. In the secondary markets. Through VC partnerships. Before the ticker symbol exists.