A market bifurcation is underway where investors prioritize AI startups with extreme growth rates over traditional SaaS companies. This creates a "changing of the guard," forcing established SaaS players to adopt AI aggressively or risk being devalued as legacy assets, while AI-native firms command premium valuations.

The current tech landscape is not a universally rising tide. While investor enthusiasm buoys AI-native companies, the disruptive threat of large language models is simultaneously depressing valuations and venture capital interest for traditional software companies whose business models are now at risk.

For AI companies experiencing explosive growth like Harvey (tripling ARR in a year), traditional TAM analysis is an obstacle, not a tool. Such growth signals the company is capturing a new budget pool (e.g., labor costs) that dwarfs the existing software market. In these cases, the revenue trajectory itself becomes the best indicator of the true TAM.

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.

In hyper-growth markets like AI, intense, zero-sum competition is delayed. While the market is expanding rapidly and is less than 60% saturated, multiple players can grow explosively without directly competing. The real 'knife fight,' where one company's win is another's loss, only starts once the market matures and new customers become scarce.

Unlike traditional software where growth implied de-risking, AI companies can achieve billion-dollar revenues without validating unit economics. This breaks the historical inverse relationship between scale and risk, creating a paradigm where larger companies are not necessarily safer investments.

Michael Burry's comparison of OpenAI to Netscape is apt regarding market share erosion due to intense competition. However, the AI market is expanding exponentially. Unlike the browser market of the 90s, OpenAI can lose market share percentage yet still see massive absolute revenue and usage growth.

The narrative of "0 to $100M in a year" often reflects a startup's dependence on a larger, fast-growing customer (like an AI foundation model company) rather than intrinsic product superiority. This growth is a market anomaly, similar to COVID testing labs, and can vanish as quickly as it appeared when competition normalizes prices and demand shifts.

The traditional SaaS "Rule of 40" (Growth + Margin) is insufficient for the AI era. A better heuristic to gauge a company's AI leadership is to combine the percentage of its sales derived from AI with its market share in that specific AI category.