Beyond Investigation Agents: Building Operational Memory That Compounds

Why the future of production operations belongs to agents that remember: a technical deep-dive into memory architectures for AI SREs.

Willem Pienaar

Co-Founder, CTO | Cleric

Shahram Anver

Co-Founder, CEO | Cleric

The Problem

AI investigation agents typically start from zero on every alert. The cache issue from Tuesday gets rediscovered Friday. The rate limit context your principal engineer debugged at 2 AM? Gone. Your platform team’s two years of tribal knowledge? The agent doesn’t have it.

If an agent performs the same on incident #100 as incident #1, it won’t scale.

What We’ll Cover

Why Investigation Logic Will Commoditize: Foundation models will make querying Prometheus and parsing logs trivial. The lasting advantage is exclusive access to your incident history and architectural context.

The Three Types of Operational Memory: Semantic (infrastructure topology), Episodic (past incident outcomes), Procedural (investigation strategies that improve) - and how they work together.

The Multiplayer Collision Problem: How memory lets agents connect related incidents across services, turning five simultaneous alerts into one root cause.

[Live Demo] Cold Start vs Warm Start: Watch the same alert investigated with zero context versus 99 incidents of learned history.

Why Operational Memory Creates Lasting Value: How these three memory types compound and get measurably smarter with each incident.

Live Attendees Get

Technical Q&A with Willem and Shahram
Real production investigations (anonymized)
Architecture brief: “Designing Memory-Enabled Investigation Agents”

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Beyond Investigation Agents: Building Operational Memory That Compounds

The Problem

What We’ll Cover

Live Attendees Get

Register Now

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