New survey maps the path to long-horizon AI agents
jiqizhixin · x · 2026-07-24
A survey titled Towards Long-Horizon Agents argues that the next frontier for AI agents is moving beyond one-shot tasks to systems that can plan over long time spans, interact with real environments, recover from failure, and adapt strategies while executing.
- The paper proposes a unified framework based on the co-evolution of two parts:
- Externalized harness
- Internalized optimization
- It organizes the field into six perspectives: Foundation, Evolution, Harness, Optimization, Application and Frontier.
- The authors position the survey as a roadmap for building more capable, reliable, and truly autonomous long-horizon agents.
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