Agent Systems and Architectures
Key Questions
What does research show about progressive disclosure in agent design?
A systematic study finds progressive disclosure does not scale and is harness-dependent, challenging a common agent design pattern.
How does MSCE improve agent memory handling?
MSCE converts agent memory into executable skills rather than relying on passive retrieval, enabling more effective self-improvement.
Why is agent architecture emerging as a key focus area?
Insights on harnesses and memory conversion signal a shift from scaling model size toward architectural innovations for capability and safety gains.
A systematic study shows progressive disclosure in agents doesn't scale and is harness-dependent, challenging a common design pattern. MSCE converts agent memory into executable skills, moving beyond passive retrieval. These complement earlier insights on harnesses as compositional generalizers. Together, they signal a shift from model size to agent architecture as a key frontier for capability and safety.