Your next 'coworker' is actually a digital intern

The industry is rebranding AI programs to suggest they are autonomous workers capable of handling complicated "coworker" duties. For instance, new tools are being designed to write code or monitor business data, with apps now allowing you to check in on their progress from your phone. These companies want you to believe these agents are active participants in your daily workflow, moving beyond just typing out text answers to actually performing the work itself.

To understand an agent, think of a regular AI chatbot like a librarian who can answer any question you ask. An "agent," by contrast, is like an apprentice who has the librarian's knowledge but is also given a set of specific tools—like a calculator, a web browser, or a file manager—and a checklist of steps to perform. When you give the agent a task, it doesn't just think of an answer; it creates a plan to use those tools in order. It keeps loop-testing its own progress: "Did I get the data I needed? Does this code run? If not, what do I try next?" It isn't thinking for itself; it is simply iterating through a loop until the result matches the goal you set.

The danger of calling these tools "agents" is that it leads us to treat them like human colleagues who have their own judgment. If your computer system is labeled a "coworker," you might be tempted to trust its decisions rather than double-checking them. In reality, these systems are "brittle"—they are highly efficient at following a specific script, but they fail in unpredictable ways the moment they face a situation that isn't on their checklist. By framing them as autonomous agents, companies are shifting the burden of failure onto you. The more we treat software as a teammate, the less likely we are to hold it to the standard of a tool, which is all it actually is.