AI Agents Explained: What Is a ReAct Loop and How Does It Work?
The article discusses the concept of a ReAct loop in AI agents, which allows them to reason, act, and observe their way to a final answer. A ReAct loop is a sequence of three steps: reason, act, and observe, which are repeated until the model has enough information to provide a correct response. The loop enables AI agents to handle tasks that cannot be solved in a single call, such as tasks with conditional dependencies.
- ▪A ReAct loop is a sequence of three steps: reason, act, and observe, which are repeated until the model has enough information to provide a correct response.
- ▪The loop enables AI agents to handle tasks that cannot be solved in a single call, such as tasks with conditional dependencies.
- ▪The ReAct loop is different from a single tool call in that the conversation remains open, and the model can change its plan based on what it just learned.
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| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/ai-agents-explained-what-is-a-react-loop-and-how-does-it-work/ |
| Publication time | Fri, 03 Jul 2026 16:30:00 +0000 |
| Retrieval time | 2026-07-04T13:15:44.112Z |
| Last seen | 2026-07-04T13:15:44.112Z |
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| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 8snoXlEcxyRU |
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| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Artificial Intelligence AI Agents Explained: What Is a ReAct Loop and How Does It Work? How agents reason, act, and observe their way to a final answer, one step at a time Maria Mouschoutzi Jul 3, 2026 12 min read Share Image created by the author using ChatGPT Images 2.0 In my last post, we talked about Tool Calling. Tool Calling is the mechanism that allows an AI model to decide which function needs to be used and with what arguments, instead of just generating text as output. By the end of that post, we had a setup that could decide to get_current_weather or convert_currency, or do both at once by calling them in parallel, or neither of them, and just generate text.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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