Dan Ives argues the current selloff in software is overdone and emotionally driven by fear that each new OpenAI/Anthropic model upgrade will keep crushing software multiples. His core view is that the durable winners are the incumbent software and data-stack players, not the models themselves.
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The transcript is a focused bullish case on software stocks after a sharp selloff. The speaker says the market is reacting to an 'AI alarmism' narrative that software companies will be permanently disrupted every time OpenAI or Anthropic releases a stronger model. He calls this the most disconnected narrative he has seen in tech since the late 1990s, arguing that the actual advantage sits with companies that already own the install base, years of code, and real customer workflows. He specifically points to enterprise software and infrastructure names such as Salesforce, ServiceNow, CrowdStrike, and Palo Alto Networks as examples of businesses whose value comes from embedded data and deep usage rather than from the frontier models themselves. …
Tactically, the software trade looks sentiment-heavy and could stay volatile on every major model release from OpenAI or Anthropic; near-term weakness may persist even if the fundamental thesis is intact.
Over the next few months, the likely path is a rotation toward software names that can prove durable workflow and data advantages. Confirmation would come from resilient enterprise demand and no real evidence that model upgrades are breaking incumbent products.
The structural thesis is that AI does not erase enterprise software moats; it shifts value toward companies that own the data, the workflow, and the installed base. If correct, model companies may generate the headlines, but platform companies capture the durable economics.
The current software selloff is being driven by the fear that every new OpenAI or Anthropic model upgrade will hit software stocks again and again.
The opening question frames repeated model upgrades as the key concern weighing on software names.
This is the most disconnected narrative he has seen in tech since the late 1990s.
He directly compares the current software narrative with late-90s excess.
AI-native stacks will not be the long-term winners because the data sits in the installed base and decades of code built into existing use cases.
He argues the moat is in incumbent data and code rather than in new model-native stacks.
Are we going to keep seeing software get hit every time OpenAI or Anthropic releases a new model upgrade, or does that stop?
The answer is that the selloff is driven by an exaggerated AI-disruption narrative; incumbent stack players own the data, install base, and code, so they should remain winners over time.
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