56% Salary Increase

The race today is for frameworks, APIs, and tutorials on autonomous agents. What rarely shows up in this conversation are the most useful questions: when an agent actually makes sense, when a simple script solves it better, and how to audit a decision the agent made without you in the loop. This distinction is what separates those who can charge more from those who merely execute faster.

The reasoning I apply before writing a single line of code:

1. Does the problem require iterative reasoning?
If not (predictable inputs, deterministic logic), an agent is over-engineering. Write a function and move on.

2. Is the error reversible?
Autonomous agents make mistakes. If the failure is catastrophic (deleting data, sending emails, processing payments), you need human checkpoints in the middle of the flow, not full automation.

3. Can you audit the decision?
If the agent took an action and you can't explain why, you're not in control. Logs, traces, and periodic evaluations are not a technical detail: they are the product itself.

Those who will reach the 56% are not necessarily the ones with the most tools installed, but the ones with clarity about when not to use any of them.

Have you ever stopped to think about when NOT to use an AI agent in your project? Tell me in the comments, I'm curious to see how other devs are structuring this reasoning.