The current tech landscape is not a universally rising tide. While investor enthusiasm buoys AI-native companies, the disruptive threat of large language models is simultaneously depressing valuations and venture capital interest for traditional software companies whose business models are now at risk.

For the first time, the high-multiple software industry faces a potential existential threat from AI. Even the possibility of disruption is enough to compress valuations, causing massive dispersion where indices look calm but underlying sectors are experiencing extreme rotation.

The recent software stock drawdown is not about poor current performance; many companies are still beating earnings. Instead, the market is pricing in a massive "terminal value risk" from AI, valuing companies as if they will decline in perpetuity, creating a historic disconnect between current fundamentals and long-term valuation.

A large concentration of private credit lending is in the software sector, particularly SaaS businesses. The rise of powerful AI tools that can replicate software services cheaply poses a direct threat to the viability of these companies, creating a hidden risk concentration within private credit portfolios where there are few hard assets to recover.

The primary threat of AI to software isn't rendering it obsolete, but rather challenging its growth model. AI will make it harder for SaaS companies to implement annual price increases and will compress valuation multiples, creating stress for over-leveraged firms from the zero-interest-rate era.

AI is making core software functionality nearly free, creating an existential crisis for traditional SaaS companies. The old model of 90%+ gross margins is disappearing. The future will be dominated by a few large AI players with lower margins, alongside a strategic shift towards monetizing high-value services.

Unlike previous tech shifts like cloud, AI is so disruptive that it creates a viable narrative for how incumbents could either massively win or be completely displaced. This complicates investment decisions across the software sector, as both optimistic and pessimistic outcomes are highly plausible.

The traditional software buyout playbook relies on a stable terminal value multiple for exits. However, AI's ability to make existing code obsolete means long-term free cash flow projections are no longer reliable, rendering the leverage-based PE model fundamentally flawed.

The AI productivity boom is not lifting all tech stocks. Instead, it's negatively impacting traditional software companies. The market is pricing this in, with software ETFs like IGV breaking down technically even before earnings reports reflect the anticipated decline in business.