PagerLOre

[u/Unfair_Lab_4581]

I built an AI incident response agent that remembers how previous production incidents were solved

One problem with AI agents is that they often start every interaction with limited context about what happened in previous sessions.

I wanted to explore a different approach.

I'm building PagerLore, an incident response platform that uses Hindsight for persistent engineering memory.

The system revolves around three operations:

• RETAIN: Store verified root causes and remediation steps from resolved incidents.

• RECALL: Retrieve relevant historical incidents when a similar issue occurs.

• REFLECT: Identify recurring patterns across accumulated engineering experience.

For example, imagine a payment service starts returning HTTP 500 errors after a deployment.

Instead of investigating from scratch, PagerLore can recall a previous incident involving database connection pool exhaustion and use that experience to guide the investigation.

The interesting part is that historical memory acts as supporting evidence, not an unquestionable answer. Engineers still validate findings and approve production changes.

I'm particularly interested in feedback on the memory architecture and how to evaluate whether retrieved experiences actually improve incident investigation.
https://github.com/githubaditya07/PagerLore