Before You Blame the Model, Check What Your Compactor Deleted
A lot of production AI incidents look like intelligence failures.
- The assistant asks for data the user already gave.
- It violates a constraint that was clearly stated earlier.
- It makes a recommendation that ignores a prior commitment.
The default diagnosis is: the model hallucinated.
Sometimes that is true. But often, the model is doing exactly what we asked with the context it was given. The real bug is that the context was compacted badly before the model saw it.
This article is about that failure mode, and how to fix it with a lightweight probe harness.
What you will get from this:
- A clear mental model for why compression breaks decisions.
- One concrete, end-to-end example from failure to fix.
- A domain-agnostic pattern you can apply in support, healthcare, finance, legal ops, IT, or logistics.
- A practical CI approach that does not require live model calls in unit tests.
The Core...
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