1 min read
In short
If AI development tools really do read each other’s instructions, personal settings become part of the overall context rather than a local note. Let’s explore what a cautious conclusion we can draw right now—even without knowing the details of how it works.
The main risk here isn’t that one AI client can read another’s files. The problem lies elsewhere: a developer’s personal instructions may suddenly begin to influence the behavior of a neighboring tool, even though the user didn’t expect it.
The practical takeaway is simple: instructions for AI clients should be treated as data that can cross the boundaries of a specific application. Don’t store secrets, unnecessary personal information, or rules there—especially ones whose consequences you’re not prepared to see in a different work context.
This also changes the approach to configuration itself. The more tools are working alongside a single project, the more important it is to separate project rules, personal preferences, and sensitive information. Otherwise, convenient automation turns into an implicit channel for transmitting context.
But there’s an important caveat: the source material provides only a title and a snippet of text unrelated to the mechanism’s description. Therefore, it’s impossible to say with certainty which specific clients are involved, exactly what they’re reading, or whether this is intended behavior, an integration, or a bug. For now, this is a reason to reevaluate the boundaries of trust, rather than proof of a specific vulnerability.
Have you already checked which instructions and files your AI tools can access outside the current client? Source: Hacker News - Newest: ""AI" "LLM""