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What the SaaSpocalypse promises—and what it can miss
The term describes the possibility that AI-assisted development, including “vibe coding,” could make it economical for companies to replace SaaS subscriptions with software built for their own needs. Anderson’s caution is that a working substitute can still carry forward the old system’s assumptions and workflow. Recreating its screens and handoffs may reproduce its limitations rather than take advantage of what agents can do.
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That is a leadership argument, not a measured comparison showing that custom software is better or worse than SaaS. Anderson’s interview does not quantify potential savings or establish that organizations broadly can replace their SaaS tools. Its useful question is narrower: if a company builds something itself, has it changed the work—or merely rebuilt the old process?
Redesign the work before building
Anderson recommends starting with the desired outcome, then working backward to decide how the process should operate. As he told CIO: “Before you put any fingers on keyboards, get a small cross-functional team together, look at reimagining the process and start from the outcome. Then work back”.
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That means involving people who understand the work and the systems around it before development begins. The team should identify which steps need to happen, what result counts as success, and where an agent could perform work instead of navigating a human-oriented sequence of dashboards, forms, and handoffs. In Anderson’s view, agents may need direct access to data, APIs, and other agents rather than interfaces designed primarily for people.
Check whether the work can be delegated predictably
Not every task is a good candidate for agent execution. Before building, leaders should ask whether the work can be delegated in a predictable way: are the inputs and intended outcome clear enough, and can the process be designed so the agent’s role is understandable? If the answer is unclear, automating the existing steps may simply encode their ambiguity.
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A practical comparison should examine the current SaaS workflow and a proposed agent-enabled process across the same questions:
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- Delegation: Can the work be assigned to an agent predictably?
- Identity and access: How will users, agents, data, and APIs be managed?
- Operations: What observability, technical standards, and documentation will support the system?
- Ownership: Who will maintain and support it after launch?
- Experience: How will the change affect employees and customers who depend on the process?
Building is only the start of production ownership
Generated code is not the whole operating model. A custom tool also needs consistent user management, observability, technical standards, documentation, and a named owner responsible for keeping it running. These are ongoing responsibilities, not features that appear automatically when a prototype works.
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Anderson frames this as a shift in accountability: “Someone has to keep it running. We didn’t have that responsibility in SaaS. Now we do,” he told CIO. Replacing a vendor transfers some continuing work to the organization. A decision to build should therefore account for who handles maintenance and production support, not just who can create the first version.
Employee trust is part of implementation
Employees may wonder whether AI will replace them or what their future looks like in an AI-first workplace. Anderson argues that unanswered fears can turn into resistance, whether active or quiet. “We’ve always said building the technology is easy. Getting people to use it is hard,” he told CIO.
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His advice is to bring the CHRO into AI leadership discussions alongside the CISO. Security leadership addresses risks such as access and protection; human-resources leadership can help leaders explain how work and roles may change, what is known and what remains uncertain, and where employees fit. Anderson warns that without psychological safety, “on one extreme you get AI sabotage. On the softer end you get passive resistance, where people just resist using the AI.” These are his observations in an opinion interview, not quantified findings.
Use a build decision that includes the people and the operating work
Before committing to a custom replacement, leaders can use Anderson’s recommendations as a set of decision gates:
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- Define the outcome. Describe the result the work should produce before choosing a tool or asking anyone to build.
- Redesign the process. Map which steps should change and whether agents need a different path to data, APIs, or other agents than the current user interface provides.
- Assess predictable delegation. Decide which parts of the work can be delegated clearly and where human judgment or a different process remains necessary.
- Plan production operations. Assign responsibility for identity management, observability, standards, documentation, maintenance, and support.
- Plan for adoption. Involve security and HR leadership, explain what is known and unknown, and address how the change affects employees.
- Compare the full experience. Judge the proposed process against the SaaS workflow by its outcome, reliability, operating ownership, and effect on employees and customers—not by whether a prototype can be built.
The case Anderson makes is not that every SaaS product should be replaced or that AI-generated custom tools will necessarily fail. It is that the apparent ease of producing code can obscure the harder work: changing a process, operating the result, and earning the trust of the people expected to use it.
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