How to Spend Your 20s in the AI Era

AI's Impact on Traditional Career Paths and Education

• Unemployment rates for Computer Science majors in February were 6.1%, exceeding the 3.0% rate for Art History majors, according to New York Federal Reserve data.
• Entry-level roles previously considered safe, such as Microsoft Level 59 Product Managers, are diminishing as AI proves superior at reliably following instructions.
• Current university CS curricula often prohibit the use of modern coding tools like Cursor, preventing students from acquiring essential future skills.
• The value of a degree is shifting from teaching technical execution to credentialing reliability; in an AI era, human agency and independent decision-making will define competitive advantage.
• Real-world learning occurs more effectively through independent side projects and "forward-deployed engineering" (immersing oneself in a specific domain) than through traditional coursework.

The Viability of "Last Window" Capitalism Theories

• Speculation that this is the final window to get rich relies on the premise of imminent AGI/ASI; if machines replace human labor, the value of "human money" and the race to accumulate it may become obsolete.
• The pace of growth for AI startups has accelerated to an order of magnitude faster than historical norms, with companies like Cursor reaching $10B valuations just two years out of college.
• Traditional Series A funding is evolving into a "fake credential" driven by external validation; modern success is defined by direct revenue generation (e.g., $10M-$12M ARR) achieved by small teams (5-10 people) without external validation.
• B2B SaaS companies are now experiencing hyper-growth previously reserved for consumer social apps, creating an inversion in startup growth models.
• Technical expertise is the new constraint in software building, whereas domain expertise was the primary differentiator in the pre-AI web era.

Founding Strategies and Market Approaches

• Success requires "building taste," which founders acquire by deeply understanding customer needs and technical execution, often through undercover work in target industries.
• Founders without industry experience can rapidly acquire domain expertise (e.g., building AI agents for dentists) by leveraging AI's ability to simulate work and selling the "magic" of new capabilities.
• Starting a company requires a "positive maxims" mindset (excitement, building value) rather than a "fear-based" mindset (racing to exit before an event horizon).
• Entrepreneurship programs that teach "fake it till you make it" or simulate success via retreats are warned against as they risk fostering the dishonesty seen in scandals like FTX and Theranos.
• Niche markets remain the optimal entry strategy; Airbnb started with airbeds, Stripe began as a developer API for instant payments, and Coinbase targeted users buying crypto with a simple UI.
• The moat for future AI companies lies in combining proprietary data systems with AI models in "weird" or unlikely niches where human competition is low.

Operational Advice for Founders and Students

• Social media and "aura farming" are dismissed as simulacrum; founders should prioritize "utility under the curve" and tangible value creation over brand building.
• Marketing strategy should be integrated into product development via "working backwards" from a narrative (e.g., a Loom video) to drive feature prioritization.
• Founders should avoid treating startups as a series of exams to pass; entrepreneurship is an open field where the builder sets the rules and goals.
• Dropping out of college is recommended only if the individual is genuinely done with the academic environment and seeks to build technology, rather than out of FOMO or peer pressure.
• Founders should aim to work at or launch "superlative" companies with "heat-seeking missile" energy, as the median startup is likely to fail.

Preparation for Full-Time Entrepreneurship

• Founders should secure 6 to 9 months of runway to live frugally, treating saved capital as non-critical operational funds.
• For first-time founders, securing a co-founder is critical due to the steep learning curve; founders must synchronize quitting their jobs to maximize timing alignment.
• Founders should evaluate potential startups with the rigor of an investor, creating spreadsheets to assess the objective quality of the team and market.
• The "niche" strategy allows founders to wedge into a market with high willingness to pay (buying "work" via AI) before expanding to adjacent markets.