11-12, August 2026 Seoul, South Korea View More Details & Registration Note: The schedule is subject to change.
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AI agents have no memory between sessions. Every conversation starts from zero. Git becomes the only persistent memory an AI agent can rely on. GitAIOps is the pattern built on this principle: Git is the memory, and a 4-layer architecture defines what goes into that memory.
I applied this to a production migration: 15 Helm releases, Kafka ZooKeeper-to-KRaft, Redis-to-Valkey, full observability stack rebuild. The question: what does Git need to contain so any AI session picks up where the last one left off?
The answer is a 4-layer Git structure, each layer born from a production failure. Layer 1: Human plans in Git (36 files, 23,854 lines). Too verbose for AI. Layer 2: Distilled AI context in Git (6 files, 1,254 lines). 19:1 compression as a project state dashboard. Layer 3: Command Guardrails in Git (117 files). Enforced ordering, no AI-generated commands. Layer 4: Locked values in Git (30 files). Zero interpretation, reviewed like code.
Every AI action reads from Git, executes, and commits back. The loop is closed.
DEV: 2 weeks → 2 days. PROD: 1 week → 1 day. The session covers the architecture, each layer's failure, and real production artifacts.
