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Off-the-shelf SaaS products often fail to accommodate a company's specific workflows. Building custom internal tools with AI allows teams to create solutions precisely matched to their culture and cadence (like design reviews), leading to higher adoption and impact.
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.
Alex Karp argues that the future of enterprise software is not about forcing companies into standardized SaaS workflows. Instead, AI's true power lies in creating custom systems that amplify a company's unique "tribal knowledge" and operational data, turning their specific processes into a competitive advantage that no other enterprise can replicate.
Standard SaaS platforms are one-size-fits-all. With AI coding assistants like Perplexity Computer, you can build a custom UI, such as a Kanban board for Slack messages, that perfectly matches your personal workflow and adds missing features like bulk-archiving specific message types.
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.
Vercel builds internal AI agents and tools, like an Open Graph image generator, to automate tasks that were previously bottlenecks. This not only increases efficiency but also serves as a critical dogfooding process, allowing them to innovate on their core platform by building the tools their own teams need.
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.
The primary value of AI app builders isn't just for MVPs, but for creating disposable, single-purpose internal tools. For example, automatically generating personalized client summary decks from intake forms, replacing the need for a full-time employee.
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.
Developing internal tools, like a project management system, evolves a company's environment and workflows much faster than rolling out new policies, which require extensive communication and buy-in for adoption.
Anthropic has seen a proliferation of personalized work apps created by employees in roles like sales. Tools like Claude Code lower the barrier to building software, allowing teams to create tailored solutions for repetitive tasks instead of using generic tools.