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AI agents could make it harder for some software companies to charge a premium or keep customers loyal, Microsoft executive Charles Lamanna warned at a Seattle technology summit. In GeekWire’s account of his remarks, the risk is that when an agent chooses and operates a service for someone, the agent—not the person using it—becomes the practical customer. Lamanna described agents as “very harsh customers.” That is a forecast, not proof that business software broadly has already lost pricing power.
How an AI agent could change who chooses software
In a direct-use model, a person opens an application, learns its interface and may stick with it because of habit, training or the work already organized there. In the model Lamanna described, an agent handles a task and interacts with software services behind the scenes. The user may care about the completed task, while the agent can select a service based on price, speed and reliability.
That shift could make some services easier to substitute. If the agent can switch between providers without asking the user to learn a new interface, a company may have less leverage from brand familiarity or user loyalty. The service would still need to work well, but Lamanna’s point is that it may have to earn its place through the qualities the agent evaluates.
GeekWire reported that Lamanna made the argument in a keynote conversation with Madrona Managing Director Matt McIlwain at Madrona’s annual IA40 Summit in Seattle on September 30, 2026. He said: “If my agent interacts with your app exclusively, the agent’s your customer, not the end user,” followed by, “And agents are very harsh customers.”
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What “thick” and “thin” apps mean in Lamanna’s framework
Lamanna’s distinction is about how deeply people use an application, not a measured industry classification. The report offers qualitative examples and does not set a time threshold for either category.
| Type | How it is used | Examples in GeekWire’s report | Implication in Lamanna’s forecast |
|---|---|---|---|
| Thick app | A place where a person spends a substantial part of the workweek. | CAD programs, contact-center software, and Excel for a full-time financial modeler. | Deep, direct use may make the application harder to reduce to an interchangeable back-end service. |
| Thin app | A service a person enters briefly and then leaves; much business software, Lamanna argued, fits this pattern. | No specific vendor is identified as a thin app in the report. | It may be used headlessly behind an assistant such as Copilot or ChatGPT, leaving the agent to select among services. |
The labels are a way to reason about exposure, not a verdict on any particular product. The report does not establish that a named vendor’s application will become headless, or measure which apps are most vulnerable. The useful question for a software company is whether users depend on its distinctive interface and workflows, or whether an agent can request a result from it much like it could from another provider.
Microsoft’s own apps could be mediated by Copilot
Lamanna’s scenario includes Microsoft products rather than exempting them. As GeekWire reported it, he expects Word, Excel and PowerPoint to remain, while many people may use their capabilities from inside Copilot instead of moving between separate applications. He described a possible standard office setup as Copilot for AI and Teams for communication, “and that’s maybe it.” This is his prediction about how people may work, not a statement that the Office apps are going away.
The report also says Lamanna described Copilot using connectors to draw on information from services such as Salesforce and ServiceNow, so a person could work without leaving the assistant. That illustrates the distinction between the interface a person sees and the services an agent or assistant coordinates with. It does not establish the technical details, availability or commercial terms of every connector.
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Lamanna reportedly compared a software service operating behind an agent to a business selling only through Amazon. A seller can reach customers there, but if buyers see similar options—“your pencils or those pencils,” as he put it—the seller may face pressure to compete on price. He contrasted that with a brand such as Nike, which he described as having more leverage.
The analogy is about differentiation: a company whose value is visible and distinctive to users may retain more influence than one the agent treats as a replaceable supplier. It is not evidence that every headless service will become a commodity, nor does the example establish an outcome for any software vendor.
Platform access can limit what agents are able to do
Agent-mediated work depends not only on software providers but also on the platforms controlling access. GeekWire reported several examples involving Amazon: the company blocked Meta’s Muse agent from shopping on its site, saying Meta had not requested permission and that Muse did not identify itself and appeared to store customer credentials. Meta disputed the credentials concern, saying Muse could not see users’ passwords or payment methods.
GeekWire also reported that Amazon opened seller tools to Anthropic’s Claude, enabling merchants to manage inventory, prices and listings without entering Seller Central, and that Amazon was in a legal dispute with Perplexity over Comet. These are examples reported by GeekWire, not proof that platforms will treat all agents alike. They show that an agent’s ability to act can depend on a platform’s access rules as well as on the underlying service.
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Lamanna’s argument identifies a plausible pressure on some business-software companies: if an agent can choose among comparable services, the services may compete more directly on price, speed and reliability, with less protection from end-user habit. The distinction between deep, direct workflows and brief, agent-mediated tasks helps explain why the effect might vary across applications.
But GeekWire’s report describes a forecast and examples, not a measured market-wide shift. It supplies no adoption, pricing or performance statistics, and it does not establish that most apps will lose pricing power. Nor does the framework alone predict which companies will remain differentiated: that depends on how users and agents value the work each service performs, and on whether platforms allow agents to reach it.
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