VCs are shifting investment away from traditional SaaS because AI-powered 'cloud code' can easily replicate software features, eroding moats. Capital is now flowing to less replicable, technology-risk businesses like robotics, AI-driven hedge funds, and biotech. This marks a strategic return to underwriting deep technical innovation over predictable financial metrics.

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.

A significant market disconnect exists where public SaaS companies are selling off on fears of AI disruption, while venture capitalists are aggressively funding new AI-native SaaS startups at a record pace, suggesting two completely different outlooks on the future of software.

A partner at Google's AI-focused fund, Gradient Ventures, has adopted a "short SaaS" investment thesis. The rationale is that AI makes building software so easy that most traditional SaaS companies no longer have a defensible moat. This puts the entire business model in jeopardy, making it an unattractive area for new venture investment.

As large AI models absorb functions of traditional SaaS products, investors and entrepreneurs are shifting focus back to tech-enabled services. Integrating AI deeply into physical services and workflows is now seen as creating more defensible, lasting value than pure software, reversing a years-long trend.

Unlike SaaS, deep tech companies have a unique valuation trajectory: a sharp seed-to-Series A increase, a long plateau during R&D, and then massive step-ups post-production. This requires a bimodal investment strategy focusing on early stage and the final private round before inflection.

Unlike prior tech cycles with a clear direction, the AI wave has a deep divide. SaaS vendors see AI enhancing existing applications, while venture capitalists bet that AI models will subsume and replace the entire SaaS application layer, creating massive disruption.

Unlike SaaS startups focused on finding product-market fit (market risk), deep tech ventures tackle immense technical challenges. If they succeed, they enter massive, pre-existing trillion-dollar markets like energy or shipping where demand is virtually guaranteed, eliminating market risk entirely.

Deep tech is highly varied (space, robotics, bio). VCs accustomed to the homogenous SaaS playbook lack the expertise to underwrite these diverse areas, so they default to chasing a few consensus 'winners,' causing unhealthy capital concentration.