“Employees who don’t really understand the goal they’re after will spin in circles not knowing when they should just call it done or step away,” Farmer says. “The enemy of good is perfect, and LLMs make us feel like if we just tweak that last prompt a little bit, we’ll get there.”
Agents of doom
Observers see two versions of doomprompting, with one example being an individual’s interactions with an LLM or another AI tool. This scenario can play out in a nonwork situation, but it can also happen during office hours, with an employee repeatedly tweaking the outputs on, for example, an AI-generated email, line of code, or research query.
The second type of doom prompting is emerging as organizations adopt AI agents, says Jayesh Govindarajan, executive vice president of AI at Salesforce. In this scenario, an IT team continuously tweaks an agent to find minor improvements in its output.
