Block's AI agent, Goose, has an accessible UI that allows non-technical employees in roles like sales and finance to build their own software dashboards and tools. This democratizes software creation within the enterprise, turning domain experts into citizen developers.

Modern AI coding agents allow non-technical and technical users alike to rapidly translate business problems into functional software. This shift means the primary question is no longer 'What tool can I use?' but 'Can I build a custom solution for this right now?' This dramatically shortens the cycle from idea to execution for everyone.

"Vibe coding" platforms, which allow users to create apps from natural language, pose a direct threat to the B2B SaaS market. For simple workflows, it is becoming faster for a team to build its own personalized app than to navigate the sales, procurement, and integration process for an existing SaaS product.

The barrier to creating software is collapsing. Non-coders can now build sophisticated, personalized applications for specific workflows in under an hour. This points to a future where individuals and teams create their own disposable, custom tools, replacing subscriptions to numerous niche SaaS products.

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

The true advantage of AI coding tools like Claude Code is not just task automation, but the ability for non-engineers to build a suite of personal, custom applications. This "personal software" is the ultimate unlock for scaling a marketer's unique craft and workflows.

The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.

Instead of integrating with existing SaaS tools, AI agents can be instructed on a high-level goal (e.g., 'track my relationships'). The agent can then determine the need for a CRM, write the code for it, and deploy it itself.

Nimble small and medium-sized businesses will increasingly use AI to build custom internal tools, especially for CRM. They will opt to create the 20% of features they actually need, rather than pay for complex, expensive enterprise software where they ignore 80% of the functionality.