VCs Cool on Generic AI SaaS Tools
Get the Tech newsletter
Daily tech — startups, AI labs, chips, the launches that shape the next decade. Free.
- Aaron Holiday (645 Ventures) told TechCrunch that thin workflow layers, generic horizontal tools, light product management, and surface-level analytics — 'basically, anything an AI agent can now do' — are now 'quite boring' to investors, while AI-native infrastructure, vertical SaaS with proprietary data, systems of action, and platforms embedded in mission-critical workflows are gaining favor.
- Igor Ryabenkiy (AltaIR Capital) said differentiation in UI and automation is 'no longer enough' because the barrier to entry has dropped, and argued that consumption-based pricing will be easier to defend than rigid per-seat models.
- Jake Saper (Emergence Capital) framed the split between Cursor and Claude Code as the 'canary in the coal mine' — 'one owns the developer's workflow, the other just executes the task' — saying developers increasingly choose execution over process as agents take over.
- Saper also said Anthropic's model context protocol (MCP) is turning integrations from a moat into a utility, since users can now connect AI models to external data and systems without building or downloading custom connections.
- Abdul Abdirahman (F-Prime) said generic vertical software without proprietary data moats is no longer popular, citing public SaaS companies whose stocks are down as AI-native startups with 'better, more efficient technology' rise.
- Ryabenkiy identified the SaaS companies struggling to raise right now as generic productivity tools, project management software, basic CRM clones, and thin AI wrappers built on top of existing APIs — 'products that can be copied without much effort.'
Why it matters: VCs are reallocating capital away from easily-replicated AI SaaS toward startups with proprietary data, workflow ownership, and deep domain expertise — meaning thin AI wrappers and generic productivity tools face an uphill funding battle, and public SaaS stocks in the firing line have already sold off as AI-native challengers emerge with sharper technology.
