The traditional asset management industry's product development is structurally flawed. Firms often launch numerous funds and market only the one that performs well, a "spaghetti cannon" approach. Products are designed by what a "car salesman" thinks can be sold, prioritizing upfront commissions over sound investment opportunities.

In a rising market, the investors taking the most risk generate the highest returns, making them appear brilliant. However, this same aggression ensures they will be hurt the most when the market turns. This dynamic creates a powerful incentive to increase risk-taking, often just before a downturn.

The boom in leveraged ETFs, heavily concentrated in tech and crypto, forces systematic buying on up days and selling on down days to maintain leverage targets. This creates a "negative gamma" effect that structurally amplifies momentum in both directions and contributes to market fragility.

Unlike traditional B2B markets where only ~5% of customers are buying at any time, the AI boom has pushed nearly 100% of companies to seek solutions at once. This temporary gold rush warps perception of market size, creating a risk of over-investment similar to the COVID-era software bubble.

The modern ETF landscape is characterized by issuers launching a high volume of specialized products, including leveraged single-stock and long-tail crypto ETFs. They accept that many will fail, hoping a few become highly profitable hits.

In the early stages of a disruptive technology like AI, the market lacks concrete data, leading to a wide range of predictions. This uncertainty causes sentiment to swing dramatically from euphoria to panic based on narratives and thought pieces, as seen with recent software selloffs.

When an asset sees a massive price surge, it's effectively a "price compression" that pulls years of expected returns into a short period. This raises the probability of future volatility or stagnant performance, as the future gains have already been realized.

In a race to capture investor appetite for AI, ETF issuers are filing paperwork for products based on companies that haven't even gone public. This includes covered call ETFs for SpaceX, OpenAI, and Anthropic, a strategy to be first-to-market for hyped IPOs.

A true investment thesis isn't just a popular idea. It must be a specific, actionable, and testable hypothesis that outlines growth drivers, expected performance, and the conditions for holding or selling the asset.