The AI Bubble is Bursting… Here’s How to Profit From It

Tier Zero: Energy Infrastructure [00:18]

• AI's reliance on electricity makes energy infrastructure, data centers, utilities, and generators a critical and profitable sector.
• Companies like Hanley Energy, which builds data centers, exemplify the opportunities.
• Specialized contractors offering 24/7 emergency services for data centers in specific regions can also find significant demand.
• The advice is to "copy the homework" of successful companies and become a specialist contractor for these facilities.

"We're looking at utilities, generators, grid plays, or even buying or starting businesses that service energy infrastructure because look at this consumption level."

Tier One: Chip Manufacturing Support [01:14]

• Controlling chip manufacturing, like Nvidia and AMD, is paramount to global innovation, but the real money can be in supporting roles.
• This includes building the fabs, maintaining clean rooms, and handling HVAC and installation for these multi-billion dollar facilities.
• Smaller contractors can specialize in tasks like filter changes, which large contractors may not want their high-priced engineers to handle.
• Companies like Promera, formerly DataClean, grew by obsessively focusing on keeping mission-critical environments particle-free.

"I think most people think, 'Hey, this is just for the big guys. I'm out.' You know what? I guess you're right. But the contractors building these 10 billion dollar facilities, they've been around for 20 years."

Tier Two: Data Centers [02:26]

• The data center sector received $455 billion in investment last year, a 51% increase.
• Opportunities lie in providing essential services like plumbing, roofing, wiring, and insulation to these AI infrastructure hubs.
• Companies like JM Tech Group, which clean data centers, also identify missed detection systems, fire hazards, and disconnected cables, positioning themselves as risk management consultants.
• The play is to show up to clean, inspect, and fix, transitioning from a janitorial role to a higher-paid consultant.

"This is AI translated for bluecollar domination."

Tier Three: Foundation Models [03:25]

• This tier involves big players like OpenAI, X, and Google, representing high investment and uncertain returns.
• For individuals, the opportunity is not to build the foundation models but to sell tools or services to those who do.
• Early AI startups burn significant amounts of money, with $500,000 a month spent on GPUs being common.
• Even $10 million for a startup only buys about 20 months of runway.
• The orchestration layer, including tools, APIs, and frameworks, is presented as the "AWS of AI" and a lucrative, though less glamorous, area.
• Companies servicing one another, like Nvidia investing in companies they sell to, and Amazon investing in Anthropic, highlight a complex ecosystem of "circular financing."

"You don't need to build the oil rig. You just need to sell the fuel tools or whatever tacos to the guys on it."

Tier Five: AI Native Applications [05:30]

• This tier focuses on user-facing applications, but many are built without a clear business model.
• The key is to focus on apps that replace cost centers and drive real productivity.
• Tools like Replit and Cursor allow for quick prototyping, but scaling requires robust back-end infrastructure.
• A major threat in this tier is "key person risk," where big tech companies poach top engineers with high compensation packages.
• To succeed, a technical co-founder with equity, vesting schedules, retention bonuses, and a strong company culture are crucial. Alternatively, one can aim for a lifestyle business.

"If you build to millions, tens of millions, maybe even unicorn status, and suddenly Meta slides into your senior engineers DMs with a $2 million package and unlimited Lacroy. Who can say no to that?"

The Broader AI Economy and Bubble Concerns [07:13]

• The US is making a significant bet on AI, with its economy and markets heavily reliant on its success.
• There are concerns that the AI market might be a bubble, with $400 billion being spent and 40% of S&P gains tied to AI stocks.
• However, unlike past bubbles, AI is already integrated into the economy, with 90% of GDP growth being AI-related.
• Big tech companies are trading at more reasonable multiples compared to the dot-com bust era.
• The advice is not to time the market, short it, or blindly invest, but to build a moat and focus on cash flow.

"So, bubble or boom, that's how you stay rich."

Profiting Through Cash Flow and Workflow Fixing [08:17]

• Launching a digital storefront using AI tools like "Build Your Store" can be a fast way to build cash flow with zero tech skills or inventory.
• AI should be leveraged for margin expansion within existing businesses by automating customer service, pre-qualifying leads, and cutting costs.
• Companies like Temple and Webster saw a 60% cost reduction by layering AI across various functions.
• The real winners will be "scrappy operators" who provide essential services to the AI boom, such as wiring data servers, cooling server farms, and cleaning labs.
• Focus on being a "workflow fixer" who solves real problems, not just an "idea guy," exemplified by legal tech company CoCounsel Legal.

"The money won't go to the flashiest chatbot. It would go to the one that saves law firms 40 hours of doc review like Co-Counsel Legal."

Ownership and AI Agents [11:10]

• Waiting for AI to feel safe means missing out on opportunities; using AI to speed up ownership is key.
• The biggest opportunities lie in using AI before others do, especially as human creativity is an underrated bottleneck.
• AI agents, which can understand goals, plan, make decisions, and take initiative without constant human direction, are seen as a significant future development.
• The key to making money in the AI age is not letting AI think for you, but making it think with you, directing AI's generative capabilities with originality and speed.

"The biggest benefits will likely come in the form of AI agents."