AI agents fail in production not because of model quality but because of infrastructure failures in the context layer. Four specific failure modes are identified: fragmentation (agents see only partial data and return confident wrong answers), opacity (data exists but agents can't navigate or retrieve it correctly), speed degradation (latency compounds across multi-step reasoning loops), and non-accumulation (agents never improve because they lack persistent memory). Each failure mode has a corresponding fix: fresh context via change data capture, navigable context via a semantic layer with access controls, fast context via memory-first architecture and semantic caching, and compounding context via two-tier agent memory. Redis Iris is presented as a managed platform addressing all four pillars through Context Retriever, LangCache, Data Integration, and Agent Memory services.
