Agent reliability is being engineered around the model

Two projects treat the model as only one component of a dependable agent system. Harness Engineering proposes encoding local requirements, authority, prior failures, and proof checks in repositories so later runs inherit organizational judgment. SafeAI scans agent code offline for prompt injection, exposed tools, Model Context Protocol (MCP) misconfigurations, and missing governance before runtime testing. Together they extend the previous days’ evidence-gating theme into repository design and continuous integration, although neither project reports an independent comparative benchmark.

Operational reliability is also appearing as core product work. Cofounder’s agent-platform role makes execution reliability, traces, metrics, tests, cost, and integration quality explicit engineering responsibilities for end-to-end workflows. Separately, Codex Resets records 35 usage-limit resets over 26 weeks, with an average interval of 8.9 days; preserved announcements connect resets to rapid traffic growth, outages, and unexpectedly fast quota consumption. The dashboard is not a controlled service-quality study, but it shows why capacity and metering belong in the agent reliability stack.