Holden Spaht

"Nobody is vibe coding Dayforce... It needs to be audited. It needs to be checked. It needs to be correct... high cost of error." The market is indiscriminately selling software stocks on the fear that AI agents will replace SaaS seats. Spaht argues that highly regulated, complex "systems of record" (like Payroll/HR) have a moat built on compliance and data ontology that LLMs cannot replicate. Therefore, the sell-off in these specific names represents a value disconnect. LONG "High-Consequence" Vertical SaaS. AI agents eventually becoming capable of handling complex, multi-jurisdictional compliance tasks without hallucination.

"We view them [Anthropic/OpenAI]... as a great route to market for them because they don't understand these domains... We started with Claude's MCP embedded into all of our software tools." The relationship between Big Tech AI (Hyperscalers/Model Builders) and Vertical SaaS is symbiotic, not adversarial. The Model Builders (Amazon/Anthropic, Microsoft/OpenAI, Google) provide the engine, while the SaaS companies provide the distribution and domain context. This confirms the "AI Infrastructure" long thesis remains intact as the enterprise layer adopts their models. LONG AI Model Providers. Regulatory crackdowns on AI model dominance or commoditization of the model layer itself.

"We view them [Anthropic/OpenAI]... as a great route to market for them because they don't understand these domains... We started with Claude's MCP embedded into all of our software tools." The relationship between Big Tech AI (Hyperscalers/Model Builders) and Vertical SaaS is symbiotic, not adversarial. The Model Builders (Amazon/Anthropic, Microsoft/OpenAI, Google) provide the engine, while the SaaS companies provide the distribution and domain context. This confirms the "AI Infrastructure" long thesis remains intact as the enterprise layer adopts their models. LONG AI Model Providers. Regulatory crackdowns on AI model dominance or commoditization of the model layer itself.

"We view them [Anthropic/OpenAI]... as a great route to market for them because they don't understand these domains... We started with Claude's MCP embedded into all of our software tools." The relationship between Big Tech AI (Hyperscalers/Model Builders) and Vertical SaaS is symbiotic, not adversarial. The Model Builders (Amazon/Anthropic, Microsoft/OpenAI, Google) provide the engine, while the SaaS companies provide the distribution and domain context. This confirms the "AI Infrastructure" long thesis remains intact as the enterprise layer adopts their models. LONG AI Model Providers. Regulatory crackdowns on AI model dominance or commoditization of the model layer itself.

"Nobody is vibe coding Dayforce... It needs to be audited. It needs to be checked. It needs to be correct... high cost of error." The market is indiscriminately selling software stocks on the fear that AI agents will replace SaaS seats. Spaht argues that highly regulated, complex "systems of record" (like Payroll/HR) have a moat built on compliance and data ontology that LLMs cannot replicate. Therefore, the sell-off in these specific names represents a value disconnect. LONG "High-Consequence" Vertical SaaS. AI agents eventually becoming capable of handling complex, multi-jurisdictional compliance tasks without hallucination.