To identify truly significant trends, look for three signals: 1) a deep and broad 'possibility space' with many potential intersections; 2) a high rate of discovery and accelerating momentum; and 3) the creation of new language because existing words are insufficient to describe what's happening.

The platform where you encounter an idea indicates its stage in the trend lifecycle. Ideas originating on niche, pseudonymous platforms like Reddit are early. Once they hit mainstream, professionally-oriented platforms like LinkedIn or Facebook, the opportunity is gone.

The most opportune moment to focus on a new technology is when it is dynamic, exciting, and poorly understood. The point at which it becomes mainstream and easily explainable is often the signal that the period of exponential change is over, and it's time to shift attention to the next frontier.

Despite dreaming of self-driving cars for decades, the host found himself bored and checking his phone within minutes of his first ride. This reveals how quickly truly revolutionary technology can shift from a marvel to a background utility, losing its novelty upon proving its reliability.

The novelty of new AI model capabilities is wearing off for consumers. The next competitive frontier is not about marginal gains in model performance but about creating superior products. The consensus is that current models are "good enough" for most applications, making product differentiation key.

Analysis shows that the themes venture capitalists and media hype in any given year are significantly delayed. Breakout companies like OpenAI were founded years before their sector became a dominant trend, suggesting that investing in the current "hot" theme is a strategy for being late.

A live poll showing over 70% of a business audience now uses AI tools like ChatGPT instead of Google for some searches proves that attention platforms can lose dominance in under two years. This makes reliance on any single marketing channel a major risk.

Ramp's AI index shows paid AI adoption among businesses has stalled. This indicates the initial wave of adoption driven by model capability leaps has passed. Future growth will depend less on raw model improvements and more on clear, high-ROI use cases for the mainstream market.

Unlike the classic S-curve model which ends in saturation, most marketing channels eventually experience a decline in performance. This "Elephant Curve" (growth, plateau, then decline) means you must constantly explore new channels rather than relying on optimizing existing ones forever.