Investors' obsession with companies growing "from zero to 100 in a year" has led them to neglect fundamentally strong enterprise software businesses. This creates an arbitrage opportunity for those willing to back solid companies with great, albeit not exponential, growth in large markets.
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.
Instead of selling software to traditional industries, a more defensible approach is to build vertically integrated companies. This involves acquiring or starting a business in a non-sexy industry (e.g., a law firm, hospital) and rebuilding its entire operational stack with AI at its core, something a pure software vendor cannot do.
The current fundraising environment is the most binary in recent memory. Startups with the "right" narrative—AI-native, elite incubator pedigree, explosive growth—get funded easily. Companies with solid but non-hype metrics, like classic SaaS growers, are finding it nearly impossible to raise capital. The middle market has vanished.
An alternative to chasing hyper-growth AI is to invest in categories where AI adoption is slower. This provides founders with a crucial time advantage to build durable businesses, but it necessitates a more capital-efficient model that can't sustain a hyper-frequent fundraising pace.
The focus on AI among institutional investors is so absolute that promising non-AI companies risk "dying of neglect" and being unable to secure follow-on funding. This creates a potential opportunity gap for angel investors to fund valuable businesses in overlooked sectors.
Investor uncertainty about the long-term viability of software business models due to AI is causing a fundamental shift in valuation. Instead of paying a premium for future growth, investors are now demanding immediate returns like dividends, effectively treating established software firms as value stocks rather than growth stocks.
The market has shifted beyond a simple AI vs. non-AI debate. The only metric that matters for private companies is extreme growth velocity. Startups demonstrating anything less are considered unfundable, creating a stark divide in the venture landscape.
Thrive Capital invested in an AI-powered accounting firm, not an accounting AI software tool. Their thesis is that in some industries, the service provider who uses AI to become hyper-efficient will capture more value than software vendors selling tools to a fragmented customer base. This is a bet on the business model, not just the technology.
Many engineers at large companies are cynical about AI's hype, hindering internal product development. This forces enterprises to seek external startups that can deliver functional AI solutions, creating an unprecedented opportunity for new ventures to win large customers.
In the current AI hype cycle, a common mistake is valuing startups as if they've already achieved massive growth, rather than basing valuation on actual, demonstrated traction. This "paying ahead of growth" leads to inflated valuations and high risk, a lesson from previous tech booms and busts.