‘It allows workers to experiment with the same logic their employers have been applying to them’ — developers reportedly lost their jobs to an ‘AI Transformation’, so they built an AI that can replace the CEO | Daily Reports Online
A group of developers reportedly lost their jobs during what their employer called an “AI Transformation.” Their response was unusually literal. They built OpenExecutive, an open-source system designed to perform work associated with a CEO and the rest of the executive suite.
The employer and CEO have not been named in the online discussion, and OpenExecutive’s own materials don’t present it as revenge for a particular firing. That said, it’s hard not to see some specific grievances in both the project and the response online, with lots of comments gleefully welcoming senior management to the automation discussion.
The appeal is easy to understand after several years of executives explaining that AI will make organizations leaner, usually while standing a comfortable distance from the part being trimmed.
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OpenExecutive presents one AI executive to the user, but that voice is backed by eight specialist agents. The virtual management team includes equivalents of everything from a chief strategy officer and chief operating officer to general counsel and a board communications director. It can draw on company documents, remember previous decisions, and surface follow-up actions later.
Org chart forked
OpenExecutive uses Anthropic’s Claude models by default, with an executive agent routing requests to whichever specialists seem relevant. The developers pitch it as a C-suite group chat in which everyone responds promptly. The project is distributed under the permissive Apache 2.0 license. Anyone can inspect it, modify it, run it internally or build a commercial product around it.
That open-source element gives the project more weight than a chatbot sold as a digital chief executive might usually represent. It also allows workers to experiment with the same logic their employers have been applying to them. If a company can divide software development into tasks, feed those tasks to models, and keep a few people around for supervision, it can do so.
The comparison is not entirely frivolous. Executive work involves processing information, preparing scenarios, comparing trade-offs, and producing documents for other executives. Those are all activities developers think AI models can handle. It makes OpenExecutive both a product and a satire of AI products.
AI replacement has often been discussed as something that moves upward from the bottom of an organization, consuming routine work before eventually reaching management. The developers have turned the telescope around and discovered that a surprising amount of executive labor also looks like information moving between boxes.
Human accountability
OpenExecutive is still an executive adviser, not a legal chief executive. It cannot accept responsibility or sign documents on behalf of a company. A human must decide whether to act on its recommendations and remain accountable if those recommendations fail.
That’s where human leadership can’t really be replaced. Analysis is part of the job, but it also involves making choices under uncertainty and accepting responsibility for the consequences. A model can recommend closing an office or cutting a team without feeling the weight of the people affected, while the humans deploying it may find the machine’s apparent neutrality rather convenient.
The project therefore reveals one of the stranger assumptions behind AI-driven layoffs. Companies often judge workers by how much of their output software can reproduce. Executives are more often judged on relationships and judgment.
AI does not erase that distinction, but it makes the special exemption harder to defend. If a developer must prove that their work contains something beyond the code an AI can generate, senior leaders should be expected to prove that their value exceeds AI recommendations. A large salary should buy more than the ability to schedule another meeting about efficiency.
Recent corporate experiments also suggest that replacing people can be easier to announce than to sustain. For instance, Duolingo’s CEO softened an “AI-first” memo after backlash over plans to phase out contractors where automation could handle their work.
Automation keeps happening, but there should be more questioning of its benefits. AI can help a small group start a company without immediately assembling a miniature court of consultants and executives. It can also give existing leaders a new justification for concentrating control while reducing the workforce beneath them.
OpenExecutive will not make CEOs obsolete, at least today. Its recommendations require scrutiny and auditing. But it shows the rhetoric of AI efficiency goes both ways in corporations. Once leaders decide that every job should be broken into tasks and measured against a machine, their own work becomes fair material for the same experiment. The resulting AI CEO may never fire its human counterpart, but it has already made the performance review considerably more awkward.
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