Making ACE Work in Production: Two Lessons from the Real World

The article examines Agentic Context Engineering (ACE) implementation in real enterprise environments, identifying two critical success factors: detailed LLM self-eval as a strong alternative to human-labeled ground truth, and providing agents with prior context about their purpose to improve learning efficiency during cold-start scenarios. These findings show that feedback quality and initial context shape whether ACE enhances or diminishes agent performance in production.