One user measured around $5 per day just from heartbeat loops and scheduled checks. That alone adds up to more than $150 per month, even before any real work happens.

Why Costs Grow So Fast

There are three main reasons costs escalate quickly:

1. Always-on reasoning
   The agent keeps thinking, even when nothing is happening.
2. Weak guardrails
   When a tool fails or config is wrong, the model tries to reason its way out instead of stopping.
3. Expensive models doing simple checks
   Claude Opus is great at reasoning, but using it to repeatedly ask “is there anything to do?” is costly.

When something breaks, the agent often enters long retry loops. Each retry burns more tokens, even if no progress is made.

When an Agent Makes Financial Sense

At $500–$5,000 per month, a full-time Opus agent is no longer cheap automation. It competes directly with human labor.

It only makes sense when:

• The agent replaces real engineering time
• Tasks run frequently and without supervision
• Human context switching is expensive

If the agent is mostly exploring, experimenting, or generating filler output, the cost is hard to justify.

The Bottom Line

Running a full-time AI agent is not about cheap answers. It is about paying for continuous reasoning.

Right now, that kind of intelligence is impressive, but expensive. Without strict limits on steps, tools, and token budgets, costs are not just high, they are unpredictable.

For most users, the real challenge is not making agents work.
It is making them worth the money.

Source https://www.glbgpt.com/hub/clawdbot-full-review/?gad_campaignid=23430588165