DoorDash Is Testing Lunch By Text. It's A Clue To How You'll Buy Software In 2027.
AI agents are fundamentally shifting the value proposition of software, moving revenue generation away from traditional SaaS interfaces and toward the underlying data, application, and agentic layers. The ability to integrate and process data via a custom agent (the 'agentic layer') is becoming the primary differentiator. Companies must now position themselves not just as tools, but as trusted data custodians and workflow orchestrators to survive the agent disruption. For builders, this means focusing on creating highly structured, interoperable data schemas that can be consumed by multiple agents.
Key takeaways
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Agent disruption makes old SaaS tools less sticky.
As agents handle information processing (e.g., reading contracts, writing kickoff plans), the need to open and use a dedicated, single-purpose tool diminishes, making the tool itself less valuable.
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The agent trained on proprietary knowledge is hard to replace.
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The true value lies in the 'lessons learned'—the unique context and workflow knowledge taught to a custom agent. This knowledge, if housed in a custom harness, creates a significant competitive moat.
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The competitive set for software is broadening.
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Major players (Meta, Salesforce, Microsoft) are all positioning themselves as control planes, leveraging their existing data distribution to manage and govern agents, rather than just selling the application.
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Value must be demonstrated across multiple layers.
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To sell software in the age of agents, vendors must move beyond simple value demonstrations and prove how their solution impacts the data layer, the application layer, and the agentic layer simultaneously.
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The core value remains in structured workflows.
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While interfaces may shift, highly compliant, structured workflows (like payroll) and the underlying data structure remain critical applications that cannot be easily replaced.