Previously, building bespoke software for niche internal problems was too expensive. AI agents dramatically lower this cost, allowing companies to create custom-fit solutions for 99% of their problems, ending the era of contorting workflows to fit generic, off-the-shelf tools.

Traditional SaaS switching costs were based on painful data migrations, which LLMs may now automate. The new moat for AI companies is creating deep, customized integrations into a customer's unique operational workflows. This is achieved through long, hands-on pilot periods that make the AI solution indispensable and hard to replace.

User stickiness for AI models is increasingly driven by the 'harness'—the custom prompts, workflows, and integrations built around a specific model. This ecosystem creates high switching costs, even when a competing model offers incrementally better performance.

As AI commoditizes user interfaces, enduring value will reside in the backend systems that are the authoritative source of data (e.g., payroll, financial records). These 'systems of record' are sticky due to regulation, business process integration, and high switching costs.

AI models are not an immediate threat to Excel because they are designed for approximation, not the precise computation required for financial and data analysis. Their 'black box' nature also contrasts with a spreadsheet's core value proposition: transparent, verifiable calculations that users can trust.

While replacing complex systems like Workday with AI is impractical, the real opportunity is in extensibility. AI allows users to build small, custom apps on top of existing platforms, solving specific needs and making the core SaaS product even stickier and more valuable.

The most durable moat for enterprise software is established user workflows. The current AI platform shift is powerful because it actively drives new behaviors, creating a rare opportunity to displace incumbents. The core disruption isn't just the tech, but its ability to change how people work.

AI doesn't kill all software; it bifurcates the market. Companies with strong moats like distribution, proprietary data, and enterprise lock-in will thrive by integrating AI. However, companies whose only advantage was their software code will be wiped out as AI makes the code itself a commodity. The moat is no longer the software.

In enterprise AI, competitive advantage comes less from the underlying model and more from the surrounding software. Features like versioning, analytics, integrations, and orchestration systems are critical for enterprise adoption and create stickiness that models alone cannot.