# How to track AI API deprecations

AI API deprecations are easy to miss until they become urgent. A model retirement, endpoint change, SDK migration, or deadline can create support work, broken automations, and rushed engineering decisions.

The goal is to catch deprecations when they appear in source material, not after they break a workflow.

## Sources to monitor

For every provider your product depends on, track:

- API changelogs
- Model lifecycle pages
- Migration guides
- SDK release notes
- Developer newsletters
- Status or incident pages
- Docs pages for endpoints you use

Deprecations often appear in docs before they become widely discussed.

## What to extract

Each deprecation brief should answer:

1. What is being deprecated or changed?
2. What is the deadline or migration window?
3. Which model, endpoint, SDK, or parameter is affected?
4. What should engineering, product, or support do next?

This makes the update actionable instead of another link to read later.

## How Skimless helps

Skimless can follow provider docs, changelogs, feeds, newsletters, and videos, then turn deprecation signals into a daily or weekly brief. Teams can notice migration work early instead of discovering it during a release.

Related: [track AI API changes](/resources/how-to-track-ai-api-changes), [track AI model releases](/resources/track-model-releases), and [monitor AI vendor updates](/resources/monitor-ai-vendor-updates).