AI Startups Need Net New Capabilities

🔑 Enhanced Key Takeaways

• •The 'net new capability' thesis aligns with the 2025-2026 shift in venture capital, where investors are pivoting away from 'wrapper' startups that rely solely on OpenAI or Anthropic APIs toward companies building proprietary vertical-specific data moats.
• •Recent industry analysis suggests that the commoditization of LLMs has reduced the barrier to entry for basic generative tasks to near zero, forcing startups to integrate deep-stack technical capabilities like custom fine-tuning on private datasets or specialized agentic workflows to maintain valuation.
• •The concept of 'net new' is increasingly being measured by 'workflow integration depth,' where the value is derived not from the AI model itself, but from the ability to replace legacy enterprise software stacks entirely rather than merely augmenting them.

🔮 Future ImplicationsAI analysis grounded in cited sources