Meta's ad recommendations excel because Apple's privacy changes created a do-or-die situation. This necessity forced them to pioneer GPU-based AI for ad targeting, a move competitors without the same pressure failed to make, despite having similar data and talent.
To overcome fierce competition in seed rounds, Offline Ventures allocates 20% of its fund to an internal studio. This capital pays for incubating ideas, which, if successful, result in the fund owning ~33% of the company, compared to the typical ~10% from a standard investment.
AI struggles to provide truly useful, serendipitous recommendations because it lacks any understanding of the real world. It excels at predicting the next word or pixel based on its training data, but it can't grasp concepts like gravity or deep user intent, a prerequisite for truly personalized suggestions.
Historical inventions have atrophied human faculties, creating needs for artificial substitutes (e.g., gyms for physical work). Social media has atrophied socializing, creating a market for "social skills" apps. The next major risk is that AI will atrophe critical thinking, eventually requiring "thinking gyms" to retrain our minds.
A paradox of rapid AI progress is the widening "expectation gap." As users become accustomed to AI's power, their expectations for its capabilities grow even faster than the technology itself. This leads to a persistent feeling of frustration, even though the tools are objectively better than they were a year ago.
The role of a senior developer is evolving. They now focus on defining outcomes by writing tests that a piece of code must accomplish. The AI then generates the actual implementation, allowing small teams to build complex systems in a fraction of the traditional time.
People feel lonely because they fill their finite capacity for social connection (Dunbar's number) with one-sided parasocial relationships from social media. These connections occupy mental "slots" for real friends, leading to a feeling of social emptiness in the real world.
To differentiate hype from reality, seed investors should practice "vibe coding": daily, hands-on experimentation with new developer tools. This provides an intuitive understanding of current technological capabilities, leading to better investment decisions and inoculating them against unrealistic expectations.