AI coding tools upend the 'buy versus build' software equation and threaten the SaaS business model

AI coding tools like Bolt are lowering the barrier to entry for custom software development, challenging the traditional SaaS model as companies find it increasingly viable to build internal tools. This shift is driven by the emergence of "AI-native developers" who can leverage AI to generate functional code, potentially reducing costs and increasing control for businesses. While concerns remain about maintenance and reliability, the trend could significantly impact SaaS vendors, particularly those offering customizable functionality, as companies explore building alternatives in-house; Salesforce is responding by developing its own AI agents.

Analysis

The enterprise software sector is undergoing a significant transformation driven by AI coding tools like Bolt, Replit, and Cursor, which are fundamentally altering the traditional build-versus-buy decision for software. These tools lower the barrier to custom software development, enabling non-traditional developers, termed "AI-native developers" or "software composers," to create functional applications using natural language prompts, a process requiring significantly less time and formal training than traditional development. Netlify CEO Mathias Biilmann reports approximately 10,000 new websites, many being internal tools, are created daily via such AI services on their platform, indicating rapid adoption. This trend primarily impacts areas like HR and training, revenue operations (including CPQ and business dashboards), and marketing tools, where custom solutions can be built atop existing company data.

Netlify itself has exemplified this shift by internally developing an employee survey tool, a pricing calculator, and an interview training app—tasks typically outsourced to SaaS providers like Qualtrics, Momentive, or CPQ software vendors. Even venture capitalists, such as Andreessen Horowitz's Martin Casado, are building bespoke tools like AI-powered CRMs, challenging incumbents like Salesforce. However, concerns persist regarding the enterprise-readiness, maintenance, and reliability of AI-generated software, as highlighted by Globant CEO Martín Migoya. To address this, infrastructure solutions like Netlify's "opinionated platforms" are emerging, aiming to standardize and manage AI-generated code, potentially enabling production-grade internal applications without extensive support teams.

The strategic implications for the SaaS industry are considerable. The traditional per-seat pricing model faces pressure as companies find it potentially more cost-effective to build tailored solutions in-house. While core systems of record may remain entrenched, custom functionalities layered on top are vulnerable. Salesforce (CRM), for instance, faces a specific threat to its custom add-ons, though it is proactively developing its own AI agents (Agentforce) as a countermeasure; this is reflected in a negative sentiment score of -0.4 for CRM despite an overall moderately positive sentiment (0.35) for the AI trend itself. AlixPartners has warned that over 100 midmarket software companies are particularly exposed to this disruption. This new wave of AI-assisted software development is poised to create a substantial new layer of applications on top of existing systems, offering companies enhanced control, reduced costs, and faster innovation.

Key Decisions for Investors

• Investors should critically evaluate SaaS companies, particularly those deriving significant revenue from customizable tools in HR, revenue operations, and marketing, as these segments are most susceptible to in-house development using AI coding tools.
• Monitor the adoption trajectory of AI coding platforms and the development of supporting infrastructure like 'opinionated platforms,' as their maturation will influence the pace and scale of SaaS disruption.
• Assess the defensive and offensive AI strategies of incumbent SaaS providers, such as Salesforce's (CRM) 'Agentforce' initiative, to gauge their ability to adapt and potentially capitalize on these technological shifts.
• Consider the potential negative impact on traditional SaaS vendors who are slow to adapt, especially mid-market firms, as the build-versus-buy equation increasingly favors building with AI assistance for certain applications.