AI is useful in a starred library. It is also uniquely good at making confident mistakes.
A wrong auto-tag on one repository is annoying. A wrong auto-tag applied to two hundred repositories is a cleanup project. That is why Starcat treats AI as an advisor, not an author of record.
The rule
AI may suggest. Only you confirm writes.
In practice that means:
- Tag recommendations appear as proposals you accept or dismiss
- Summaries are generated for review, not silently overwritten into your notes
- Nothing in your personal taxonomy changes because a model "felt sure"
This is slower than full automation. It is also how you keep trust in a tool you open every day.
Why confirmation is a feature
Your tags are a language. infra/observability and learn/later mean something specific to you. A model trained on the public web does not share that dialect.
Confirmation creates a feedback loop humans actually use:
- AI proposes a short list
- You keep what fits
- The library stays coherent
Without that step, the library slowly becomes someone else's ontology.
Conservative by design
Starcat unlocks AI behind Pro and BYOK-style provider settings. Even then, the product stance does not change: capability is gated; consent is not optional.
If you want a system that quietly rewrites your tags overnight, Starcat is the wrong app. If you want a second set of eyes that still asks before it writes — that is the point.