ReAct Agent Pattern/ ReAct

Definition

ReAct Agent Pattern is reasoning-and-acting pattern where an AI alternates between thought, tool call, observation, and next action. In defense applications, it makes tool-using agents more transparent than opaque single-pass completions. The hard part is verbose loops, tool overuse, and unverified intermediate reasoning, especially when systems are deployed across contested links, coalition boundaries, and mixed human-machine teams. KhanBMS treats it as a useful pattern when every action is logged and bounded by mission policy, tying the concept back to modular command, edge execution, and auditable authority.

Reference attributes

Layer

agent control loop

Operational value

Makes tool-using agents more transparent than opaque single-pass completions

Primary risk

Verbose loops, tool overuse, and unverified intermediate reasoning

KhanBMS role

A useful pattern when every action is logged and bounded by mission policy

Related terms

• Tool-Use Agents
  Agents that call external APIs, databases, simulators, sensors, or effectors to accomplish tasks.
• Agentic AI
  AI systems that pursue goals through planning, tool use, memory, and feedback loops rather than single-shot inference.
• LLM Orchestration Layer
  Middleware that routes models, prompts, tools, memory, retrieval, policy, and telemetry across AI workflows.
• Prompt Injection Defense
  Controls that prevent untrusted text or content from overriding a model agent’s system instructions or tools.