The current mass-adoption phase for AI tools means buying decisions that would normally take 5-7 years are being compressed into 1-2 years. Startups that don't secure customers now risk being shut out, as enterprises will lock in with their chosen vendors for the subsequent half-decade.

Unlike traditional SaaS where product-market fit meant a decade of stability, the rapid evolution of AI models makes today's PMF fleeting. Founders face the risk that their product could feel obsolete within a year, requiring constant innovation just to stay relevant in a rapidly changing market.

Investor Elad Gil holds a paradoxical view: while the AI boom is a 'once in a lifetime transformation,' many individual AI startups should seek an exit in the next 12-18 months. This suggests a belief that most startups lack durability against the major AI labs and volatile market shifts, despite the macro tailwinds.

Unlike traditional software development, AI-native founders avoid long-term, deterministic roadmaps. They recognize that AI capabilities change so rapidly that the most effective strategy is to maximize what's possible *now* with fast iteration cycles, rather than planning for a speculative future.

Don't wait until you're completely exhausted to sell your company, as buyers will sense your desperation and gain the advantage. The ideal time to exit is when your passion for the market wanes or growth slows, allowing you to negotiate from a position of strength before burnout sets in.

The AI era's high velocity of change, where market leaders can be displaced in 1-2 years, resembles the volatile dot-com bubble, not the last decade's predictable SaaS growth. This means founders must consider that even massive scale doesn't guarantee durability, making exit timing a critical strategic question.

A key trend TinySeed observes among AI-focused applicants is extremely high churn, often 10-20% per month. Even with rapid top-line growth, this level is deemed "catastrophic," indicating many new AI products struggle with defensibility and long-term customer value, making them risky investments despite the hype.

The rapid pace of AI innovation means today's cutting-edge research is irrelevant in three months. This creates a core challenge for founders: establishing a stable, long-term company vision when the underlying technology is in constant, rapid flux. The solution is to anchor on the macro trend, not the specific implementation.

The dot-com era saw ~2,000 companies go public, but only a dozen survived meaningfully. The current AI wave will likely follow a similar pattern, with most companies failing or being acquired despite the hype. Founders should prepare for this reality by considering their exit strategy early.