agent workflow
30 articles about agent workflow in AI news
/loop in Claude Code: How to Build Multi-Agent Workflows Without Leaving
The /loop command in Claude Code enables autonomous multi-agent workflows, cycling through coding tasks until completion. Developers should use it to automate iterative processes like TDD cycles.
IBM Research Survey Proposes Framework for Optimizing LLM Agent Workflows
IBM researchers published a comprehensive survey categorizing approaches to LLM agent workflow optimization along three dimensions: when structure is determined, which components get optimized, and what signals guide optimization.
Anthropic Disables Claude Max for 24/7 Autonomous Agent Workflows
Anthropic has disabled the 'Claude Max' feature that allowed for 24/7 autonomous agent operation, a move affecting developers running persistent coding and automation tasks on the platform.
Claude Adds Dynamic Loop Scheduling to AI Agent Workflows
Anthropic has added dynamic loop scheduling to Claude, allowing the AI to intelligently schedule repeated tasks without a fixed interval. This is a foundational capability for creating more autonomous and efficient AI agents.
agtx: The Self-Managing Kanban Board That Automates Your Multi-Agent Workflow
Install agtx to automate task delegation between Claude, Gemini, and Codex agents via a terminal-native kanban board managed by its own orchestrator agent.
Building Sequential AI Workflows with Microsoft Agent Framework and Azure AI Foundry
A technical walkthrough of implementing a sequential agent workflow for security incident triage using Microsoft's Agent Framework and Azure AI Foundry. Demonstrates how to structure multi-stage AI processes where each agent builds on previous outputs with full conversation history.
Sim Platform Democratizes AI Agent Creation with No-Code Workflow Builder
Sim introduces an open-source, drag-and-drop platform enabling anyone to build and deploy AI agent workflows without coding. The tool connects to popular messaging channels and includes an AI copilot for assistance.
Production Deployment Patterns for AI Agent Systems: From Prototype to Scale
The article presents CI/CD, monitoring, rollback, and scaling patterns for AI agent production deployments from a SaaS practitioner. It emphasizes treating multi-agent workflows as atomic units, using OpenTelemetry tracing, and implementing circuit breakers for resilience.
Google DeepMind adds async agents, MCP support to Gemini API
Google DeepMind added background execution and MCP support to Gemini API Managed Agents. Four new features target developers building long-running, stateful agent workflows.
Tiny Fish Improves Live Web Usability for AI Coding Agents
Tiny Fish has released a tool that makes the live web significantly more usable for AI coding agents. This addresses a critical failure point where agent workflows often break down during real-world web interactions.
EkyBot Lets Claude Code Talk to Other AI Agents via @mentions
Claude Code users can now @mention other AI agents for specialized tasks, creating multi-agent workflows from a single interface.
OpenAgents Workspace Enables Real-Time, Multi-Agent AI Collaboration
OpenAgents Workspace allows multiple AI agents to communicate and collaborate in real time. This moves beyond single-agent tools toward a coordinated, multi-agent workflow system.
How to Build a Multi-Agent Dev System: One Developer's 40-Commit Field Report
A developer's two-week field report reveals how CLAUDE.md, knowledge graph corrections, and multi-agent workflows create compounding productivity gains.
LangGraph vs Temporal for AI Agents: Durable Execution Architecture Beyond For Loops
A technical comparison of LangGraph and Temporal for orchestrating durable, long-running AI agent workflows. This matters for retail AI teams building reliable, complex automation pipelines.
MASFactory: A Graph-Centric Framework for Orchestrating LLM-Based Multi-Agent Systems
Researchers introduce MASFactory, a framework that uses 'Vibe Graphing' to compile natural-language intent into executable multi-agent workflows. This addresses implementation complexity and reuse challenges in LLM-based agent systems.
Sim Emerges as Open-Source Challenger to AI Workflow Automation Giants
Sim introduces a drag-and-drop interface for building AI agent workflows, positioning itself as a 100% open-source alternative to established platforms like n8n. Released under Apache 2.0 license, this tool promises greater accessibility and customization for developers creating automated AI systems.
OpenAI's WebSocket Breakthrough: The Infrastructure Shift Making AI Agents 40% Faster
OpenAI has launched WebSocket Mode for its Responses API, enabling persistent connections that reduce redundant data transmission in AI agent workflows. This architectural change cuts latency by up to 40% for complex tool-calling operations, marking a significant infrastructure evolution for production AI systems.
Claude Code Digest — Jun 20–Jun 23
Claude Code is shifting from a chat box into governed infrastructure: the teams pulling ahead are wiring policies, auth, and agent workflows now, not later.
Claude Code Digest — Jun 17–Jun 20
Claude Code is no longer a chat tool: teams are turning it into governed infrastructure, and the winners are the ones wiring policies, MCP auth, and multi-agent workflows before the rest of the market catches up.
Anthropic Releases Claude Mythos Publicly as 'Fable' at 2x Opus Price
Anthropic released Claude Mythos publicly as 'Fable' at 2x Opus pricing, targeting agent workflows with strong safety limits.
OpenAI Rebrands Mac Codex App as Unified AI 'Superapp' Platform
OpenAI is transforming its Mac Codex app into a unified AI platform dubbed a 'Superapp,' integrating chat, agent workflows, and multimodal capabilities into a single interface. This move signals a shift from a specialized coding tool to a broader, user-facing desktop AI application.
Inside Balyasny's AI Research Engine: How Hedge Funds Are Deploying Next-Gen AI for Alpha Generation
Balyasny Asset Management has built a sophisticated AI research system using OpenAI's GPT-5.3 models, implementing rigorous evaluation frameworks and agent workflows to transform investment analysis. This represents a significant leap in how quantitative finance leverages artificial intelligence for competitive advantage.
social.plus Vise: Workflow Governance for AI Coding Agents Building SDK
social.plus launched Vise, a workflow governance platform for AI coding agents building SDK integrations, enforcing policy controls and audit trails.
i10X Launches Supera Agent That Executes Full Workflows from Prompt
i10X launched Supera, an AI agent that autonomously executes multi-step workflows from a single prompt with user approval and cost transparency.
Dynamic Workflows: A New Agent Primitive Emerges
Dynamic workflows generate harnesses on the fly for agent orchestrators, enabling branching and verified tasks across coding agents like Claude Code and Codex.
Claude Opus 4.8 Launches Dynamic Workflows for Agentic Code
Claude Opus 4.8 launched with dynamic workflows for Claude Code, enabling multi-step agentic coding. The release addresses quality issues after a ~25% instruction miss rate post-4.6.
Distilled Agentic Workflow Runs at 100x Lower Inference Cost
A new paper shows agentic workflow distillation achieving 100x lower inference cost, but lacks benchmark details.
Show HN: Spec-Driven Dev Workflow Cuts Claude Code Agent Confusion
SDDW introduces a spec-driven workflow for Claude Code that decomposes complex tasks into specs and subtasks, clearing context between steps to reduce agent confusion and costs.
OpenClaw Creator: Agentic Workflows Fail Without Human Taste in Loop
Peter Steinberger, creator of the OpenClaw AI agent framework, argues that the core failure in agentic workflows is removing human judgment too soon. He asserts that strong output requires continuous human vision, steering, and questioning.
Anthropic's Agentic Workflows Launch: A Deep Dive on Cost & Capabilities
Anthropic launched Agentic Workflows, a managed service for running persistent AI agents. While marketed from $0.08/hr, real-world costs are higher due to compute, memory, and network fees.