Interleaved Thinking

Interleaved thinking is the agentic-model ability to reason, act, observe, and then reason again after receiving tool or environment feedback. In 当我们在讨论 Harness 的时候，我们在讨论什么 | 深度对谈: MiniMax × Hermes Agent, the MiniMax guests distinguish this from chatbot behavior: a chatbot can answer the present prompt, while an agentic model must explore, correct paths, and update plans as the environment changes.

Key Claims

• Agentic models need to revise plans after tool calls rather than simply execute the first plan.
• Benchmarks that require cross-source search and multi-condition answers test this behavior better than one-shot chat tasks.
• Agent Harness matters because the model can only interleave thought and action when it has tools, observable state, and feedback.
• The concept is a model-side complement to Agentic Workflow and Model Harness Co-Evolution.

Connections

• MiniMax — company context for the term in the source.
• Agent Harness — runtime environment that exposes observations and feedback.
• Agentic Workflow — task pattern enabled by interleaved reasoning and action.
• Multi-Agent Collaboration — peer checking can help when a single agent’s interleaved path drifts.
• AI Coding Verification — software tasks require agents to observe tests, errors, diffs, and reviews before deciding next steps.