Turning ReAct from Demo to Production: Handling Failures, Loops, and Token Budgets

This article explains how to upgrade a ReAct agent from a proof‑of‑concept to a production‑ready system by classifying tool failures, detecting repeated search loops, managing token budgets, and adding structured logging, complete with Python implementations and practical interview guidance.

LLMLoop DetectionToken Budgeting

0 likes · 24 min read

Turning ReAct from Demo to Production: Handling Failures, Loops, and Token Budgets

Architecture and Beyond

Oct 12, 2025 · Artificial Intelligence

How Do AI Agents Know When to Stop? Strategies and Real-World Implementations

This article explores the essential stop‑condition designs for AI agents, detailing hard limits, task‑completion checks, explicit termination tools, loop detection, error accumulation, and user interruption, and then examines concrete implementations in OpenManus and Gemini CLI with code examples and multi‑layer safeguards.

AI AgentGemini CLILLM

0 likes · 17 min read

How Do AI Agents Know When to Stop? Strategies and Real-World Implementations

DataFunSummit

Aug 2, 2023 · Big Data

Loop Detection in Risk Control: Challenges, Distributed Graph Computing Optimizations, and ArcNeural Engine Case Studies

This article discusses the challenges of loop detection in financial risk control, presents distributed graph computing optimization techniques—including pruning, multi‑graph handling, and memory‑efficient algorithms—shows experimental results, and shares real‑world ArcNeural engine case studies and future directions.

ArcNeuralBig DataLoop Detection

0 likes · 13 min read

Loop Detection in Risk Control: Challenges, Distributed Graph Computing Optimizations, and ArcNeural Engine Case Studies

DataFunSummit

Jun 18, 2023 · Artificial Intelligence

Intelligent Risk Control Forum – Sessions on Graph Algorithms, Pre‑trained GNN, Loop Detection, Active Learning, and Unstructured Data

The Intelligent Risk Control Forum gathers experts from Tencent, Huawei, Ant Group and academia to present the latest research on graph‑based algorithms, loop detection, pre‑trained graph neural networks, active learning and unstructured‑data risk models, addressing challenges such as data sparsity, adversarial behavior and model robustness.

Loop Detectiongraph algorithmsmachine learning

0 likes · 8 min read

Intelligent Risk Control Forum – Sessions on Graph Algorithms, Pre‑trained GNN, Loop Detection, Active Learning, and Unstructured Data