The context-overload rule resonates — we kept hitting the same problem. Diagnosis is useful but we ended up just compressing the retrieved chunks to a token bud

The context-overload rule resonates — we kept hitting the same problem. Diagnosis is useful but we ended up just compressing the retrieved chunks to a token budget before they hit the LLM. Deterministic, keeps only the highest-signal passages. What's the most common finding people run into — context overload or low retrieval scores?