LLM Evaluation Methods for Production Coding Agents
Measuring agent execution paths, not just final outputs, reveals production readiness.
10 stories
Measuring agent execution paths, not just final outputs, reveals production readiness.
Most organizations run multiple software factories at once, and the gaps between them kill speed.
AI coding agents overwhelm delivery pipelines built for human developers.
Control plane reconciliation and GitOps turn modular components into genuinely composable systems.
Separate compute, storage, and execution to fix agentic pipeline design.
Machine-speed version control breaks infrastructure built for human developers.
Enriched breach signals and sandboxed validation enable agents to remediate SLOs safely.
Structured signal schemas let AI agents act confidently on production data instead of guessing.
Composable infrastructure scales individual resources; HCI scales whole nodes together.
AI agents are overwhelming pipelines designed for human-paced development cycles.