Production AI agents often fail because they receive either too little operational context to act reliably or too much sensitive context to operate safely. This talk presents Secure Context Cache, an open-source framework and runtime gateway that measures, selects, reuses, and verifies identity- and policy-scoped context before a model call. In a deterministic prototype benchmark of 24 developer-agent tasks, the approach reduced average context tokens by 75.3% relative to full-context release while preserving 95.8% task success; infrastructure-review and incident-response examples will show how freshness checks, provenance, audit evidence, and human approval limit stale-context and prompt-injection risk. Attendees will leave with an architecture pattern, failure-mode checklist, and rollout metrics for operating AI agents with SRE discipline.
Krishna Reddy is an experienced Cloud and Data Platform Engineer serving as Senior Platform Engineer at HedgeServ. With a deep background in the financial, insurance, and retail industries, he specializes in building resilient cloud ecosystems using AWS, Python, Kubernetes, Spark, and serverless architectures. Krishna holds an M.S. in Computer Science from Wright State University.
