AI agents eliminate the physical work of typing and coding, but introduce a new form of burnout. The constraint on output is no longer time spent "doing," but the limited human capacity for high-stakes decision-making, context switching, and verification, which drains mental energy much faster.

Managing AI agents is a demanding job. Since agents operate on weekends, holidays, and overnight, the human manager must constantly review outputs and correct mistakes. This creates a relentless workload and is not a suitable role for those who are not prepared for constant oversight.

The problem with AI agents isn't getting them to work; it's managing their success. Once deployed, they operate 24/7, generating a high volume of responses and meetings. Your biggest challenge will shift from outreach capacity to your human team's ability to keep up with the AI's constant activity and output.

AI is not a 'set and forget' solution. An agent's effectiveness directly correlates with the amount of time humans invest in training, iteration, and providing fresh context. Performance will ebb and flow with human oversight, with the best results coming from consistent, hands-on management.

The work of managing AI agents isn't less, it's different. It trades the emotional exhaustion of managing people for a more intense, sustained cognitive load, as you're constantly problem-solving and optimizing systems rather than dealing with interpersonal issues.

To maintain the high velocity enabled by AI agents, you must be available to unblock them constantly. This means making critical decisions and even landing pull requests from your phone is no longer a novelty but a competitive necessity. Delaying until you're at a desk is a major disadvantage.

While AI agents don't argue or take unexpected vacations, they operate 24/7 and generate ideas at a relentless pace. This constant output creates a higher cognitive load and can be more tiring for managers than supervising a human team.

While AI increases output, it also intensifies the mental load. Engineers managing multiple AI agents in parallel report feeling 'wiped out' by mid-morning. The cognitive effort required to context-switch and manage numerous complex tasks simultaneously creates a new and potent form of professional burnout.

Treat custom AI agents like junior employees, not finished software. They require daily check-ins to monitor for bugs, performance issues, and regressions. There is no "set and forget"—a human must actively manage the agent every day for it to succeed.