NEWS · CODING · #2122
InfoQ webinar panel highlights silent failures and governance for AI agents
An InfoQ webinar titled “AI in Production: What Breaks, What Works, and Who Approves It?” gathered ThoughtWorks practitioners and security/privacy experts to discuss operational challenges of agentic systems, including semantic and embedding drift, RAG leakage, model memorization, and the scaling gap for human code review as coding agents produce more production code. Panelists recommended treating evals as persistent infrastructure, shifting checks left in the harness, using mutation testing and continuous tracing, enforcing agent identities and tiered access, red‑teaming, and isolating secrets to limit blast radius.
KEY POINTS
- An InfoQ webinar titled “AI in Production: What Breaks, What Works, and Who Approves It?” gathered ThoughtWorks practitioners and security/privacy experts to discuss operational challenges of agentic systems, including semantic and embedding drift, RAG leakage, model memorization, and the scaling gap for human code review as coding agents produce more production code.
- Panelists recommended treating evals as persistent infrastructure, shifting checks left in the harness, using mutation testing and continuous tracing, enforcing agent identities and tiered access, red‑teaming, and isolating secrets to limit blast radius.
- These practitioner-reported failure modes and governance gaps show that LLM-based systems can silently cause business, compliance, and security incidents unless engineering, evals, and access controls are redesigned for agentic workflows.
WHY IT MATTERS
These practitioner-reported failure modes and governance gaps show that LLM-based systems can silently cause business, compliance, and security incidents unless engineering, evals, and access controls are redesigned for agentic workflows.