Reason-and-Act Agent Loop
Version: 1.0.0
Last updated: 2026-07-16
Purpose
Build bounded tool-use loops that alternate model proposals with deterministic execution and observation.
Why
ReAct demonstrated benefits from interleaving reasoning and actions on evaluated tasks [1]. In production, the useful abstraction is proposal → authorize → execute → observe, not exposure of private reasoning.
How
Set maximum steps, wall-clock deadline, cost budget, permitted tools, termination criteria, and repeated-action detection. Treat tool output as untrusted content.
When
Use only when the task requires adaptive tool selection. Prefer a deterministic workflow when the sequence is known.
Tradeoffs
| Benefit | Cost |
|---|---|
| Adaptive information gathering | Variable latency and cost |
| Recoverable observations | Larger attack surface |
| Better task coverage | Harder testing |
Anti-Patterns
- Unlimited loops or retries.
- A model both proposes and authorizes an action.
- Write-capable tools for a read-only task.
- Logging hidden chain-of-thought as state.
Enterprise Considerations
Use scoped service identities, per-tool policy, network isolation, approval tiers, idempotency keys, and replayable audit events. Define incident kill switches.
Checklist
- Loop has step, time, and cost limits
- Each action is authorized immediately before execution
- Tool outputs are isolated as untrusted
- Repeated non-progress is detected
- Completion is independently verified
References
- Yao et al., “ReAct: Synergizing Reasoning and Acting in Language Models,” ICLR 2023, https://arxiv.org/abs/2210.03629
Changelog
- 1.0.0 (2026-07-16): Defined bounded proposal-and-execution loops.