Building AI agent harnesses that improve across 6 editable control dimensions
MaryamMiradi · x · 2026-09-23
Maryam Miradi distills the MemoHarness paper into a 6-step roadmap for adaptive agent harnesses. Core argument: most harnesses are static — prompt, tools, memory, workflow and output handling are configured once and reused, yet different tasks fail for different reasons. MemoHarness decomposes the harness into six editable control dimensions (context, tools, generation, orchestration, memory, output processing), learns from previous executions, and adapts the configuration for each new case.
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