Agentic workflows are useful. The problem is how fast tokens pile up.
A single do this can turn into dozens of model calls. Context grows every turn. Retries get more expensive late in the session. Even simple search and re-read loops show up on the bill.
That is token addiction: wrapping deterministic work in an LLM every time.
Why agentic cost escalates
What token addiction looks like
Agent greps the same repo on every run
LLM summarizes JSON that a Set node or script could map
Full HTML dumped into context instead of structured fields
No max steps on tool loops
You are paying for judgment on work that never needed judgment.
A simple control plane
With a clear process, n8n helps you decide when AI should run:
Use AI for judgment. Use workflows for everything else. Autonomy without routing is just an expensive loop.