Important Warning Before You Start:
Don’t expect to make $1 million a year in your first year, second year, or even your fifth or seventh year using this guide. This is not a shortcut or a “get rich quick” trick. What you’re building is a long-term path — a 10+ year journey of skill, reputation, consistency, and execution. If you expect instant results, you’ll get frustrated, quit early, and end up like the millions of people who bounce from idea to idea without ever compounding anything.
What this guide does give you is clarity. It helps you stop chasing 95 different distractions that won’t get you anywhere near your goals. Instead, it gives you a focused plan you can look at for the next decade, so you can work with precision, direction, and discipline toward exceptional outcomes. If you follow your SL path consistently — whether you’re SL 0–3, SL 4–8, or SL 9–10 — you’ll be building the skills and momentum that make $1 million per year realistic over time.
Now before the examples, here’s a quick refresher:
SL 9–10 (High Studying Level)
If you’re at SL 9–10, your brain is wired for technical learning. You naturally enjoy digging into math, engineering, coding, physics, chemistry, AI, robotics, or other complex subjects. You don’t need to be forced to study — curiosity pulls you in. You can handle complexity better than most people, and you can compound those advantages for years.
Your biggest risk is spending too many years studying without building real-world money-making skills. This is extremely common: the “smart kid” trap. SL 9–10 people often end up with deep technical knowledge but no customer-acquisition skills, no publishing habits, and no ability to sell themselves or their work.
But when you combine your natural technical strengths with the ability to attract customers, publish consistently, and build a reputation early — you become unstoppable. This is where the $1M/year path becomes realistic much earlier than for most people.
In other words…
… you naturally enjoy technical subjects—math, engineering, physics, chemistry, AI, robotics, computer science, anything complex. You’re not motivated by grades; you’re driven by curiosity. You can sit with difficult concepts for hours because the process itself feels meaningful.
This gives you an enormous advantage in the modern economy. SL 9–10 students can combine two rare abilities:
- Understanding technical systems deeply
- Learning customer-growth work early (how companies get paying customers)
That combination is extremely powerful. It lets you rise extremely fast inside companies, create high-value content that attracts industry attention, build a specialized personal brand, and then scale to extremely high income—whether through consulting, entrepreneurship, or technical leadership roles.
And because someone at SL 9–10 naturally enjoys technical subjects, they can do something most people can’t: combine deep learning and college (classes, tests, exams, etc.) with real-world execution at the same time.
While they study chemical engineering, mechanical engineering, robotics, AI, or another complex field, they can also build expertise in a specific industry and do customer-generating work for companies in that space. This dual track — learning the technical side while simultaneously helping real companies grow — compounds their skills far faster than traditional students.
By the time they graduate, they’re not just “smart”; they’re valuable, proven, and already positioned to earn well into the top 1%.
Below are five detailed paths that show exactly how someone with SL 9–10 can realistically start at age 18, move through college, build technical and commercial skill at the same time, and compound toward $1 million+ per year.
SL 9–10 Example 1 — Chemical Engineering + Oil & Gas Revenue Growth (Chevron Path)
At age 18, he already enjoys chemistry and math, so chemical engineering feels natural.
But instead of waiting for college and hoping for a good job later, he studies the industry structure: oil & gas isn’t like selling clothes; revenue growth comes from better engineering decisions, improved operational efficiency, better talent pipelines, better technology adoption, and better investor relations. He picks Chevron as his “anchor company” — the company he will study, publish about, and eventually help.
So instead of waiting until after graduation to be “useful,” he starts studying the commercial side of the industry immediately. He looks at Chevron, ExxonMobil, Shell, and other majors. He asks one question: “How do these companies actually make more revenue?” Not theory—actual customer behavior, contracts, B2B relationships, large-scale procurement, fuel markets, industrial buyers.
He begins publishing simple breakdowns online:
- How downstream and upstream operations work
- What determines long-term fuel contracts
- How engineering improvements affect commercial outcomes
- How energy companies win (or lose) customers
This content attracts attention from engineers, mid-level managers, and vendors. He keeps going. In college, while studying chemical engineering, he also starts a small newsletter or blog focused on commercial growth in heavy industry. This alone positions him uniquely. Most chemical engineering students talk about thermodynamics; he talks about how thermodynamics affects revenue.
By year 2–3 of college, he’s consulting for small energy-related suppliers, helping them with outreach, customer acquisition research, and positioning. His technical understanding means he can speak the language of industry customers in ways other “marketing people” can’t. That becomes his advantage.
After graduation, he has two paths:
- Join a major (Chevron, Exxon) in a commercial-technical hybrid role and rise quickly
- Start a niche consulting firm helping energy suppliers win large industrial customers
Both scale.
He eventually specializes in helping companies win multi-million-dollar industrial contracts. Landing just one contract per year with a commission structure can push him into:
- $200k–$300k base consulting revenue
- $400k–$700k+ in deal commissions
Totaling $1 million+ per year by his late 20s or early 30s.
His technical background + commercial skill compounds into something extremely rare and extremely valuable.
SL 9–10 Example 2 — Mechanical Engineering + Robotics + Industry Customer Growth
He loves physics and math, so mechanical engineering or robotics engineering is an obvious fit. But instead of only focusing on school, he chooses a robotics niche (warehouse automation, agricultural robotics, manufacturing robots) and goes deep.
Starting at 18, he asks: “Which robotics companies are growing fastest? Who buys their products? Why?”
He studies:
- Warehouse automation sales cycles
- How SMB factories buy robots
- What objections buyers have
- Where robotics companies struggle to get customers
Then he starts publishing: simple explainers, teardown videos, industry case studies. Within one year, he becomes one of the few young people producing consistent content linking robotics engineering → commercial growth.
During college, robotics firms start contacting him for help with outreach, research, customer insights, and content creation. Because he understands the actual technology, his content resonates with engineers and executives.
By graduation, he has:
- A portfolio of case studies
- A respected robotics industry newsletter
- Warm connections inside robotics companies
He structures his career into two parallel tracks:
- Technical product/engineering role inside a robotics firm
- Independent consulting helping robotics startups attract customers, raise funding, and close deals
Once he has 3–5 robotics startups as clients, each paying him $8k–$20k per month for growth advisory plus performance incentives, he crosses $500k–$700k per year. Then he adds equity or rev-share deals with a few of them. Over time, one hits. Now he’s at $1M+/year between cash + equity.
This is a classic SL 9–10 compounding path.
SL 9–10 Example 3 — Technical AI + LLM Engineering + B2B Customer Growth
She loves coding, machine learning, and math. At 18, she already understands basic AI models. But instead of choosing a purely academic AI path, she chooses the hybrid:
“I will become exceptional at AI technical work AND learning how AI companies get paying customers.”
She studies:
- LLM architecture
- RAG systems
- AI agents
- Enterprise AI workflows
And in parallel, she studies:
- Why companies buy AI products
- How AI teams evaluate vendors
- What drives enterprise adoption
- How AI consulting firms pitch clients
She starts publishing highly technical breakdowns, open-source experiments, architecture diagrams, evaluations, and practical AI deployments for businesses. Her content becomes extremely valuable and starts getting shared by developers and founders.
In college, she works part-time for AI startups helping with:
- Technical documentation
- Developer-focused content
- Customer-facing demos
- Early sales engineering roles
She becomes a rare hybrid: someone who can build and explain AI systems and help companies acquire paying customers. After graduation, she becomes a:
- Developer advocate
- AI solutions engineer
- AI consultant
- Technical founder
By 25–27, she launches a niche technical AI consulting studio specializing in building agentic workflows for enterprises. Clients pay $50k–$200k per project. With 8–12 clients per year, plus retainer support contracts, she crosses $1M+ per year.
SL 9–10 Example 4 — Electrical Engineering + Renewable Energy + Commercial Scaling
He enjoys electronics, physics, and systems. At age 18, he chooses electrical engineering but also becomes obsessed with the commercial side of renewable energy. He studies solar installers, battery companies, EV fleet vendors, grid software companies, and microgrid operators.
He publishes content around:
- Solar economics
- EV fleet procurement
- Grid stabilization tech
- How renewable companies get their customers
During college, he begins helping small renewable installers run lead generation, content, and outreach (B2B and B2C). Because he understands the tech behind inverters, grid tie-ins, and panel efficiency, his content feels credible.
By graduation, he’s helped several companies grow, which means he has real case studies. He then starts a consulting firm for renewable energy companies focused specifically on customer acquisition, partner channel growth, and revenue strategy.
He closes his first major installer client at $5k/month. Then a battery supplier at $8k/month. Then a grid software startup at $12k/month. Within 2–3 years, he has 8–10 clients paying a combined $400k–$600k/year, plus success-based bonuses.
He later adds:
- Equity advisory roles
- Revenue-share agreements
- Government contract support
His income crosses $1M/year by his early 30s.
SL 9–10 Example 5 — Computer Science + Cybersecurity + Enterprise Growth
He loves computing, systems, and problem-solving. He chooses computer science or cybersecurity for college. But at 18, he also studies the business side: how cybersecurity companies get customers. He analyzes companies like Palo Alto Networks, CrowdStrike, Zscaler, Cloudflare, Wiz, and SentinelOne.
He publishes content explaining:
- How modern attacks work
- How cybersecurity products prevent them
- Why enterprises buy certain tools
- What CISOs care about
This content gains traction because it bridges two worlds: technical clarity and commercial understanding.
During college, he works as:
- A cybersecurity content researcher
- A technical sales engineer intern
- A security lab assistant
- A product explainer for cybersecurity startups
He becomes a trusted voice for both engineers and revenue teams. After graduation, he joins a fast-growing cybersecurity company as a technical sales engineer or solutions architect. These roles often reach $300k–$500k/year within a few years.
At scale, he transitions into:
- Independent cybersecurity consulting
- Enterprise architecture advisory
- Large-client deal support
Just a few enterprise contracts per year ($200k–$400k each) pushes his income beyond $1M/year.