What Is a Version Number? What v1.0, Beta, and "Deprecated" Actually Mean.
You have been using tools and libraries built with Claude, ChatGPT, Cursor, or Bolt and version numbers are everywhere. Python 3.11. React 18. requests 2.31.0…
You have been using tools and libraries built with Claude, ChatGPT, Cursor, or Bolt and version numbers are everywhere. Python 3.11. React 18. requests 2.31.0. Your AI tells you to install a specific version. A tool you like shows a warning that a feature is “deprecated.” Something else says it is in “beta.” These words appear constantly in the world of software and nobody stops to explain what they actually mean.
Here they are, explained simply.
What a Version Number Actually Tells You
Most software uses a three-part version number in the format X.Y.Z, for example 2.31.0. Each number means something different.
The first number (2 in this case) is the major version. A change here means something significant changed, often in a way that breaks compatibility with the previous version. When Python went from version 2 to version 3, code written for Python 2 stopped working in Python 3. That was a major version change.
The second number (31) is the minor version. New features were added but existing things still work. If you are using version 2.28 of a library and it updates to 2.31, your code will almost certainly still work and you now have access to new capabilities.
The third number (0) is the patch version. Small fixes and bug corrections. Nothing changes about how you use the software. It just works better. Updating from 2.31.0 to 2.31.4 is safe and usually recommended.
This system is called Semantic Versioning, often shortened to SemVer, and it is used by the vast majority of software tools and libraries you will encounter.
What Beta, Alpha, and Release Candidate Mean
Software goes through stages before it is considered stable and ready for everyone to use.
Alpha is the earliest stage. The software exists and works in limited ways but is incomplete, likely to have bugs, and not recommended for anything you depend on. Alpha software is for testing and feedback, not production use.
Beta means the software is mostly complete and working but still being tested for bugs and issues. Beta versions are more stable than alpha but may still have problems. Using a beta version of a library in your app is a calculated risk. It might work perfectly or it might have a bug that nobody has found yet.
Release Candidate (RC) is one step before the final release. The developers believe it is ready but want one last round of testing before calling it final. Release candidates are generally stable enough for careful use.
Stable or General Availability (GA) is the final, fully tested version that the developers recommend for production use. This is what you want for anything important.
When your AI installs a library for you, it typically installs the latest stable version. If you see a beta or release candidate in your requirements, it usually means the AI chose a specific version for a reason, such as a feature that only exists in the newer version.
What “Deprecated” Means
Deprecated means “this still works for now but we are planning to remove it in a future version. Stop using it.”
When a library or framework deprecates a feature, it usually means they found a better way to do the same thing and want everyone to switch to the new approach. The old approach keeps working for a period, often years, to give developers time to update their code. But eventually it gets removed entirely.
If your AI-written code uses a deprecated feature and you see a deprecation warning, your code still works today. But at some point in the future, when the library releases a major version that removes the deprecated feature, your code will break.
What to do: paste the deprecation warning into your AI and ask: “My code is using a deprecated feature. Can you update it to use the recommended alternative?”
Why Your AI Specifies Exact Versions
When your AI tells you to install requests==2.31.0 with a specific version number, it is being precise about which version it knows works for your use case. Different versions of libraries sometimes behave differently or have different APIs. By specifying an exact version, the AI ensures you are using the same version it knows works.
This is also why requirements.txt files list specific version numbers. They create a reproducible environment where everyone working on the same project uses the same versions of every dependency.
The One Thing to Remember
Version numbers tell you how much changed. Major versions can break things. Minor versions add features safely. Patch versions fix bugs. Beta means almost ready but not quite. Deprecated means it works now but will be removed eventually. When you see a deprecation warning, paste it to your AI and ask it to update your code to the recommended alternative before the future version removes the feature entirely.
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New here? These might help: What does “install Python” mean and do I even need to? → Why does my Python script keep asking for libraries I never installed? →