Tagged articles

multi-agent coordination

9 articles · Page 1 of 1

Jul 3, 2026 · Information Security

Evolving AI‑Native Security Operations: From Agent Risk Monitoring to Agentic SOC

Facing an explosion of enterprise agents, 360’s security team built a dual‑track AI‑native operation that first makes agent‑related threats visible through AI runtime telemetry and then amplifies incident analysis, response and multi‑agent coordination while keeping expert oversight, ultimately turning the SOC into a real‑time risk decision engine.

AI runtime telemetryAI securityAgentic SOC

0 likes · 23 min read

Evolving AI‑Native Security Operations: From Agent Risk Monitoring to Agentic SOC

Linyb Geek Road

Jun 26, 2026 · Artificial Intelligence

What Is AI Orchestration? Concepts, Tools, and Common Pitfalls Explained

The article breaks down AI orchestration as a management layer that routes tasks, maintains state, executes tools, handles retries, and coordinates multiple agents, comparing frameworks like LangGraph and CrewAI while highlighting practical pitfalls and best‑practice advice for building reliable multi‑step AI workflows.

AI orchestrationCrewAILangGraph

0 likes · 20 min read

What Is AI Orchestration? Concepts, Tools, and Common Pitfalls Explained

DataFunSummit

Jun 23, 2026 · Artificial Intelligence

How to Engineer Trustworthy AI Agents: Execution Control, Safety Boundaries, and Multi‑Agent Collaboration

In a 90‑minute live technical dialogue, experts from OPPO and Tencent Cloud dissect ten core challenges of moving AI agents from demo to production—covering sandbox vs. permission boundaries, checkpoint design, rollback strategies, tool‑call safety, human‑in‑the‑loop control, multi‑agent coordination, and observability—offering concrete engineering guidelines for building reliable, auditable agents.

AI Agent EngineeringCheckpoint DesignExecution Control

0 likes · 18 min read

How to Engineer Trustworthy AI Agents: Execution Control, Safety Boundaries, and Multi‑Agent Collaboration

macrozheng

Jun 14, 2026 · Artificial Intelligence

How to Keep AI‑Generated Code Reliable: Practical Vibe‑Coding Practices with Claude Opus 4.8

The article shares a step‑by‑step guide for safely using AI coding assistants like Claude Opus, covering Git preparation, narrow spec writing, rule and skill files, model cost management, verification through tests and diffs, context handling, multi‑agent coordination, and strict permission controls to avoid costly mistakes.

AI CodingClaude OpusGit workflow

0 likes · 20 min read

How to Keep AI‑Generated Code Reliable: Practical Vibe‑Coding Practices with Claude Opus 4.8

DataFunSummit

Jun 7, 2026 · Artificial Intelligence

Harness Engineering: Safety, Human‑Agent Collaboration, and Multi‑Agent Design

In a 90‑minute technical livestream, three experts dissect ten core challenges of bringing AI agents from demo to production, covering execution control, sandbox versus permission boundaries, checkpoint design, rollback strategies, tool‑call safety, human‑in‑the‑loop interaction, multi‑agent coordination, observability, and memory management.

CheckpointRollbackSafety Boundaries

0 likes · 17 min read

Harness Engineering: Safety, Human‑Agent Collaboration, and Multi‑Agent Design

DataFunSummit

Jun 5, 2026 · Artificial Intelligence

Harness Engineering: Making Multi‑Agent Systems Safe and Trustworthy from Demo to Production

In a 90‑minute live technical session, three experts dissect ten core challenges of Agent engineering—sandbox vs permission boundaries, checkpoints, rollback, tool‑call safety, human‑in‑the‑loop, multi‑agent coordination, observability, and memory—showing that moving agents from "usable" to "trustworthy" requires fine‑grained execution controls rather than broader permissions.

CheckpointRollbackSandbox

0 likes · 18 min read

Harness Engineering: Making Multi‑Agent Systems Safe and Trustworthy from Demo to Production

ShiZhen AI

Apr 8, 2026 · Artificial Intelligence

AI Agent Beginner’s Guide: A Clear, No‑Jargon Explanation

This guide explains what an AI Agent is, how it differs from a chatbot, the importance of tools and prompt design, common pitfalls, multi‑agent coordination, and practical steps to build, monitor, and deploy production‑grade agents.

AI AgentAgentic LoopError Handling

0 likes · 13 min read

AI Agent Beginner’s Guide: A Clear, No‑Jargon Explanation

Frontend AI Walk

Mar 25, 2026 · Artificial Intelligence

Slow Learning Agents: 7 Cognitive Shifts from Using ChatGPT to Truly Understanding Agents

The article outlines seven essential mindset transitions for building robust LLM agents—recognizing agents as autonomous decision loops, prioritizing harness over model size, layering context, designing tools for agent goals, structuring multi‑layer memory, coordinating multiple agents with isolation and protocols, and aligning evaluation with the real environment.

Context ManagementEvaluationHarness

0 likes · 16 min read

Slow Learning Agents: 7 Cognitive Shifts from Using ChatGPT to Truly Understanding Agents

AI Tech Publishing

Feb 2, 2026 · Artificial Intelligence

2025’s Hottest Agent Architecture Patterns: A Deep Technical Summary

The article surveys emerging 2025 agent architecture patterns—including giving agents a computer, multi‑layer action spaces, progressive disclosure, context offloading, caching, sub‑agent isolation, evolving context, and multi‑agent coordination—backed by citations from Meta, Anthropic, and open‑source projects.

AI agentsAgent ArchitectureContext Management

0 likes · 20 min read

2025’s Hottest Agent Architecture Patterns: A Deep Technical Summary