Recursive Experiential–Working Memory Evolution for Long-Horizon Agent Harnesses
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Updated
Aug 30, 2026 - Python
Agent harnesses are the runtime scaffolding around AI agents. They usually combine context delivery, tool interfaces, planning state, memory, sandboxes, permissions, evaluation, and observability so agents can complete longer tasks reliably. Agent harnesses are especially common in coding agents, research agents, and multi-agent workflows where repeatability, safety, and traceability matter.
Recursive Experiential–Working Memory Evolution for Long-Horizon Agent Harnesses
Open-source Python agent harness for auditable, cost-controlled LLM workflows with YAML playbooks and MCP server support.
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Self-updating intelligence dashboard tracking the AI model and tooling landscape — frontier models, agent harnesses, self-hosting, strategy.