# ReAct Pattern (Reasoning + Acting) 2026: Deep Turkish Technical Guide — From Academia to Production

> Source: https://sukruyusufkaya.com/en/blog/react-pattern-dusun-eylem-prompt
> Updated: 2026-05-13T19:53:49.218Z
> Type: blog
> Category: yapay-zeka
**TLDR:** Most comprehensive Turkish technical guide for ReAct Pattern (Reasoning + Acting): academic foundation (Yao et al. 2022 ICLR paper), CoT vs ReAct difference, Thought-Action-Observation loop, 5 ReAct variants (Vanilla, MRKL, Self-Ask, ReWOO, Plan-and-Execute), LangChain + LangGraph + LlamaIndex implementations, agentic tool use integration, 25+ Turkish practical examples, error handling, production deployment, observability, cost optimization, model comparison.

<tldr data-summary="[&#34;ReAct Pattern (Reasoning + Acting) — paradigm where LLMs generate THOUGHTS, take ACTIONS (tool calls), receive OBSERVATIONS, and iterate. Yao et al. 2022 paper, foundation of modern agentic AI.&#34;,&#34;CoT vs ReAct: CoT pure internal reasoning, ReAct adds external world interaction (search, DB, API). Result: less hallucination, current info, multi-step capability.&#34;,&#34;T-A-O loop: Thought → Action → Observation → Thought → ... → Answer.&#34;,&#34;5 ReAct variants: Vanilla ReAct, MRKL, Self-Ask, ReWOO, Plan-and-Execute.&#34;,&#34;Production 2024-2026: LangChain AgentExecutor, LangGraph state machines, Anthropic SDK, OpenAI Function Calling — all built on ReAct.&#34;,&#34;Token cost 3-10x CoT due to iterative LLM calls. ReWOO optimization saves 50-70%.&#34;,&#34;25+ Turkish practical examples: web research, KVKK queries, financial analysis, multi-API workflow, customer support, code debug.&#34;]" data-one-line="ReAct Pattern is the foundational technique for modern agentic AI — Yao 2022, T-A-O loop, 5 variants, production via LangChain/LangGraph."></tldr>

## 1. Introduction

ReAct Pattern - LLMs generate Thoughts, take Actions (tool calls), receive Observations. Yao et al. 2022 ICLR paper. Foundation of modern agentic AI.

## 2. CoT vs ReAct

CoT - internal reasoning only. ReAct - reasoning + external world interaction.

## 3. T-A-O Loop

Thought - Action - Observation iterative cycle until final answer.

## 4. 5 Variants

Vanilla ReAct, MRKL, Self-Ask, ReWOO, Plan-and-Execute.

## 5. Modern Implementation

LangChain AgentExecutor, LangGraph state machines, OpenAI Function Calling.

## 6. Tool Design

8 principles - atomic, descriptive, strict schema, deterministic, error handling, idempotent, bounded, auditable.

## 7. Cost Optimization

3-10x CoT - use ReWOO, prompt caching, smaller models for simple tasks.

## 8. Conclusion

ReAct foundational for agentic AI. LangGraph state machine modern best practice.