The Deprecation Tracker: Why It Exists

The deprecation tracker exists because AI tool recommendations have a shorter shelf life than recommendations in almost any other product category.

When Derek reviews a monitor arm, the Ergotron LX he evaluated in 2022 is still available and still performs the same way. The review is evergreen for three to five years. When I review an AI tool, the model it runs on may be replaced within six months, the interface may change substantially, and competing tools may close the capability gap that made the recommendation compelling in the first place.

What the Tracker Tracks

Changes that affect the substance of previous recommendations: model updates that change performance, pricing changes that affect the cost-benefit analysis, capability additions that change my category recommendations, and deprecations where tools have been discontinued or superseded.

I do not track minor UI updates or feature additions that don't change the recommendation. The signal-to-noise ratio matters. The tracker is for changes that should cause you to reconsider your current stack, not for every update log.

How to Use It

If you subscribed to a tool based on a recommendation from more than six months ago: check the tracker. If the tool has been updated or a better alternative has emerged, the tracker will say so. If the recommendation stands, the tracker won't have a recent entry for that tool.

Chip did not have a deprecation tracker. Chip's recommendations from 2024 remain on his pages without update context. This is the gap the tracker fills. It is not a perfect solution to a genuinely hard problem — the landscape moves faster than any static documentation can track. It is better than the alternative.