LeverageMaxxing 2025
If you are chasing an internship this summer, please read this first.
I've been seeing people post internship applications, LinkedIn celebrations of corporate summer programs, and advice threads about "maximizing your internship experience." It feels like watching people queue up for a museum exhibit while the building burns down behind them.
We're living through the most dramatic shift in human capability since the printing press, and we're still organizing our summers around fetching coffee for middle managers who learned Excel in 2018.
The Invisible Obsolescence Event
Last month, I watched a 19-year-old deploy an AI agent that automated the entire lead-qualification process for a $50M logistics company. The project took him three weeks. The company had been considering hiring two full-time business-development reps.
He charged them $15,000.
Meanwhile, his peers are competing for unpaid internships at the same types of companies, grateful for the "experience" of sitting in meetings about meetings.
This isn't just another "kids these days don't understand hard work" take. This is about recognizing when the fundamental economics of skill development have shifted. The traditional internship model (trading your time for experience in someone else's system) made sense when systems knowledge was scarce and hard to access.
That scarcity just evaporated.
Every Fortune 500 company is desperately trying to figure out how to integrate AI into their operations. Most of their current employees can barely use advanced Excel functions. But somehow we've convinced ourselves that the best use of a 20-year-old's cognitive prime is shadowing these same overwhelmed employees?
LeverageMaxxing vs. Resume Building
Here's where I'll admit something that might sound arrogant: I think most career advice is designed for a world that no longer exists.
The traditional path assumed scarcity. Scarce information, scarce tools, scarce opportunities to build real things. So we built elaborate credential systems to signal competence in the absence of demonstrable results.
But we're entering an abundance era. The tools to build sophisticated automation are free or nearly free. The tutorials are on YouTube. The distribution platforms are open to everyone. The only thing standing between a motivated 20-year-old and a $100K AI consulting business is the belief that they need permission first.
This is why I hate the internship industrial complex. It's not just inefficient, it's actively harmful. It teaches young people that their value comes from institutional validation rather than problem-solving ability. It trains them to think like employees instead of builders.
What if we flipped the script entirely?
Instead of spending summer 2025 learning how to navigate corporate Slack channels, what if you spent it learning to build AI agents that companies desperately need? Instead of adding "Summer Analyst at BigCorp" to your LinkedIn, what if you added "Automated customer service for 12 local businesses, saving each $3K/month in labor costs"?
Which resume line do you think will matter more in 2027?
The Productivity Paradox of Building vs. Learning
The schedule I've been following (and advocating for) isn't just about AI skills, it's about a fundamentally different relationship to time and leverage.
Traditional internships optimize for learning through observation. You watch. You assist. You gradually get trusted with bigger responsibilities. It's a reasonable model when the skills you're learning are complex, tacit, and hard to acquire elsewhere.
But AI automation isn't rocket science. The tools are designed to be accessible. A motivated person can go from zero to deployable solution in weeks, not years.
The real learning happens when you're trying to solve actual problems for actual businesses that will pay actual money for solutions. Not when you're sitting in a conference room learning about "stakeholder alignment" and "corporate synergies."
This creates a weird paradox: the activities that feel most like "real work" (internships, structured programs, formal training) are often the least productive. The activities that feel most unstructured and risky (building stuff, selling directly to businesses, learning through iteration) are where the actual value creation happens.
I dropped out of university twice because I kept running into this paradox. The classroom version of learning never matched the intensity and retention I got from building actual projects. But I thought I was an anomaly—too impatient, too practical, too unwilling to delay gratification.
Now I think I was just early.
Every Business Is an AI Business (They Just Don't Know It Yet)
Here's the thing that makes me bullish about the "build AI agents and sell them" approach: the market demand is essentially infinite right now.
I'm not exaggerating. Every business with more than five employees has repetitive processes that could be automated. Most of them are still doing these processes manually because they don't know that tools like n8n and Make exist, let alone how to use them.
But they also can't afford to hire McKinsey to come in and build enterprise AI solutions. They're stuck in this weird middle ground, too small for the big consulting firms, too intimidated by the technology to figure it out themselves.
That gap is where the opportunity lives.
A 20-year-old who can build reliable automation workflows and explain them in plain English is worth more to a local restaurant chain than someone with an MBA who can't code. The restaurant doesn't need strategy consulting about AI, they need someone to build a system that automatically schedules staff based on historical sales data.
The beautiful thing about this moment is that the tools are powerful enough to solve real business problems, but simple enough that you don't need a computer-science degree to use them effectively. You just need to be willing to learn through experimentation and comfortable with ambiguity.
Most people aren't. But if you are, you're essentially operating in a blue-ocean market.
The Personal Brand Insurance Policy
The other piece of this puzzle is content creation—what some people dismissively call "personal branding" but what I think of as building your own media leverage.
Here's why this matters: when you're building AI solutions for businesses, you're not just trading time for money. You're developing pattern recognition about what works, what doesn't, and why. That meta-knowledge is incredibly valuable, but only if you can articulate it and distribute it effectively.
Creating content around your AI building process serves multiple purposes:
Documentation: Writing about what you're learning forces you to understand it more deeply
Distribution: Public content attracts potential clients and collaborators
Differentiation: Most AI consultants are terrible at explaining what they do in simple terms
Insurance: Building an audience gives you optionality if the consulting market gets saturated
But here's the key insight: you don't need to be an expert to create valuable content. You need to be one step ahead of your audience and willing to share what you're learning in real-time.
When you commit to posting daily about your AI experiments, you naturally start paying more attention to what works and why.
The Hidden Costs of Traditional Paths
I realize this all sounds like typical "grindset" content, and I'm wary of that association. The difference is that I'm not advocating for working longer hours, I'm advocating for working on higher-leverage problems.
A traditional internship might teach you valuable skills about navigating corporate environments, managing up, and understanding business operations. These aren't worthless skills. But they're also skills you can learn later, when you have more leverage and can command higher compensation for your time.
The opportunity cost is what kills me. Every summer you spend in a structured program is a summer you're not spending building your own leverage. And in a rapidly changing field like AI, that timing matters enormously.
The people who get really good at AI automation in 2025 will have a massive head start over the people who wait until 2026 to start learning. Not because the technology will be that different, but because they'll have two extra years of pattern recognition about what businesses actually need.
There's also a psychological cost to traditional paths that doesn't get discussed enough. When you spend your early twenties optimizing for other people's systems, you develop a learned helplessness about building your own systems. You start to believe that real opportunities only come through institutional gatekeepers.
That belief becomes increasingly expensive as the world becomes more entrepreneurial and the tools for independent value creation become more accessible.
The 2025 Window
So why is this summer specifically important? Why not just do a traditional internship now and build AI skills later?
Because we're in a narrow window where the technology is accessible but not yet commoditized. The tools are good enough to solve real business problems, but not so automated that you don't need to understand the underlying logic.
In 2-3 years, AI automation will probably be much easier. There will be better interfaces, more templates, more automation of the automation. But there will also be much more competition. The current advantage of being young and willing to learn through experimentation will be smaller.
This is similar to what happened with web development in the early 2000s, or social-media marketing in the early 2010s. There are these brief windows where the barrier to entry is low but the market opportunity is still huge. If you can recognize these windows and position yourself accordingly, you can build disproportionate leverage very quickly.
I think we're in one of those windows right now with AI automation.
What This Actually Looks Like
Let me get concrete about what a "LeverageMaxxing" summer might look like in practice, because I realize the schedule I outlined earlier might sound abstract.
Weeks 1-2: Foundation Building
Learn the basics of n8n or Make.com through their tutorials
Build 3-5 simple automations for yourself (email sorting, social-media cross-posting, data collection)
Document your learning process publicly—write about what you're building and why
Weeks 3-4: First Client Projects
Identify 10 local businesses that could benefit from automation (restaurants, service providers, small retailers)
Reach out with specific automation ideas—don't ask what they need, tell them what you can build
Complete 1-2 small projects for free or very low cost to build case studies
Weeks 5-8: Scaling and Iteration
Use the case studies to attract paying clients
Increase your rates based on demonstrated value
Start documenting patterns about what types of automation work best for different business models
Weeks 9-12: Strategic Positioning
Use your content creation to establish yourself as an expert in specific automation niches
Build relationships with other AI builders and potential collaboration partners
Plan your approach for the academic year—will you go back to traditional school, or double down on building?
The key is that each phase builds on the previous one, and the content creation runs parallel to the technical building. You're not just learning skills—you're building a reputation and a network around those skills.
The Contrarian Bet
Here's what I think is really happening: we're in the early stages of a massive disintermediation of traditional career paths. The same forces that eliminated travel agents and disrupted taxi companies are coming for corporate training programs and entry-level white-collar jobs.
But instead of just complaining about it or trying to resist it, what if we embraced it? What if we recognized that this disruption creates enormous opportunities for people willing to build their own leverage?
The traditional advice is to get good grades, get into good schools, get good internships, get good jobs. Each step validates you for the next step in someone else's system.
The alternative is to get good at solving problems, get good at building solutions, get good at finding customers, get good at articulating value. Each step increases your ability to create value independently.
I'm not saying everyone should drop out of school or reject all traditional institutions. But I am saying that if you're in your early twenties right now, you have an unprecedented opportunity to build real leverage before you get locked into institutional tracks.
The question is whether you're willing to bet on yourself instead of betting on the system.
The Real Summer Internship
If I'm being honest, I think the "ideal day in the life" I outlined is actually more educational than most internships. Not because it covers more topics, but because it forces you to engage with the full stack of business problems.
When you're building AI automation for real clients, you have to understand their business model well enough to identify optimization opportunities. You have to learn the technical skills to build solutions. You have to develop sales and communication skills to find and serve customers. You have to manage projects, handle customer service, and iterate based on feedback.
That's a more comprehensive business education than you'll get in most MBA programs, let alone summer internships.
The difference is that instead of learning these skills in a simulated environment, you're learning them while creating real value for real people who pay you real money. The feedback loops are immediate, the stakes are meaningful, and the pattern recognition you develop transfers to other contexts.
Plus, you end the summer with a business, not just a line on your resume.
I realize this approach isn't for everyone. It requires a high tolerance for ambiguity, comfort with sales conversations, and willingness to fail publicly. Some people genuinely prefer more structured learning environments and clearer hierarchies.
But if you're already reading this far into a blog post about rejecting traditional career paths, you're probably not most people.
The question isn't whether this approach is better for everyone—it's whether it might be better for you. And the only way to find out is to try it.
What's the worst that could happen? You spend a summer learning valuable technical skills, building a portfolio of real projects, and developing an audience around your expertise. Even if the consulting business doesn't work out, those assets remain valuable.
What's the best that could happen? You build a sustainable business around high-leverage skills, develop deep expertise in an emerging field, and create optionality for yourself that doesn't depend on institutional gatekeepers.
The risk-reward ratio seems pretty compelling to me.
This summer, instead of asking "How can I get the best internship?" maybe ask "How can I build the most leverage?" The first question optimizes for other people's systems. The second optimizes for your own.
The choice is yours.
(also for those who made it to the end, this whole post was written using an automation I build that turns any piece of content into any other piece of content. This time I turned this LinkedIn post into what you just read. Pretty cool.)