DejaVu: AI incident agent uses long-term memory to recall past outage fixes

An engineer describes building DejaVu, an AI on-call agent designed to remember every outage a team has resolved. The author argues that most incidents are recurring failure patterns that appear under different service names and error messages, and that general chatbots lack the context to recognize them. DejaVu works through a recall, reason, and retain loop, using the Hindsight open-source memory system to retrieve semantically similar past incidents and feed them to an LLM. In a side-by-side test, the same model reported 20% confidence without memory versus 98% with memory for a simulated cache bug. The author notes that a keyword search would miss many of the 6 cache-related incidents in a 20-incident dataset, which semantic recall can surface.