How do you keep up with Python and decide whether to adopt a new version or tool?

Answer with a filter rather than a reading list.

How you learn: the release notes for each version — Python's are unusually readable — plus PEPs for anything that changes semantics, and building something small with a new feature rather than only reading about it.

How you filter a new version:

• Does it fix a problem you actually have? Structural pattern matching, better error messages, and per-version speed improvements are all real, but none of them justify an upgrade on their own.
• Do your dependencies support it? This is usually the binding constraint, especially for anything with C extensions.
• Can you run the test suite against it in CI before committing?

A sensible policy to state: stay one minor version behind the latest in production, upgrade on a schedule rather than on impulse, and never let the runtime reach end-of-life, because that turns into a security problem rather than a convenience one.

Note: Naming a tool you evaluated and rejected is more convincing than listing ten you like.