Before you adopt an AI tool, check how you would leave it
Most AI features get evaluated on what they do on day one. The harder question is what you can take with you if you ever need to switch. A recent BytePreview guide on data portability draws a useful line between three things: the data you put in, the outputs the tool generates, and whatever belongs
Posted on Oct 20 • Originally published at bytepreview.com
Most AI features get evaluated on what they do on day one. The harder question is what you can take with you if you ever need to switch.
A recent BytePreview guide on data portability draws a useful line between three things: the data you put in, the outputs the tool generates, and whatever belongs to the provider or depends on its infrastructure. An "Export" button doesn't tell you which of those you get back, or whether the result is usable anywhere else.
The guide suggests a simple matrix (export, format, retention, deletion, interfaces), writing down open questions instead of filling gaps with assumptions, and saving the version and date of every document you review. Anything critical that isn't documented belongs in the contract.
Full guide on BytePreview: https://www.bytepreview.com/en/articulos/data-portability-in-ai-software-a-guide-to-assessing-lock-in-risk?utm_source=dev&utm_medium=social&utm_campaign=bytepreview