The field of AI agent development is shifting from prompt engineering to 'harness engineering,' which focuses on execution systems that manage models, tools, memory, and retries for autonomous workflows. While these harnesses improve agent performance and continuity, they do not inherently enforce architectural boundaries or governance rules. This creates a 'governance gap' where agents may bypass established decisions, reintroduce forbidden dependencies, or violate layering contracts, as harnesses prioritize execution and throughput over adherence to architectural intent. AI
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IMPACT Highlights a critical gap in AI agent development, suggesting a need for new governance infrastructure beyond current execution systems.
RANK_REASON The article discusses a conceptual shift in AI development and identifies a gap in current approaches, rather than announcing a new product or research finding.