Why over-automation kills debugging skills

Modern AI tools can generate working code extremely quickly. The problem starts when engineers stop reading what gets generated.

Sustainable software development still depends on understanding:

• control flow
• state transitions
• network boundaries
• failure conditions

If nobody on the team can explain the system manually, the system is already operationally fragile.

Small systems survive longer

A small static site deployed with Caddy can outlive a fashionable microservice stack held together by autogenerated glue.

Simplicity scales surprisingly far.

Suggested workflow

Use AI for:

• drafts
• boilerplate
• refactoring ideas
• documentation generation

But keep architecture, debugging and operational decisions human.