Project dossier

In-house LLM Inference on Kubernetes: A Production Runbook

OpenAI reports that users increasingly delegate long-horizon work and run agents in parallel. Runtime and output volume are easy to measure, but neither tells us whether the result was safe to use. For consequential tasks, the real cost includes evidence collection, human review, regression testing, rollback preparation, and correcting downstream effects. A fast agent can look cheap until verification consumes the time it supposedly saved. What is your preferred unit for agent ROI: accepted outc