Workflows Articles
Browse 1206 articles about Workflows.
Claude Code Split-and-Merge Pattern: How Sub-Agents Run in Parallel Within One Session
The split-and-merge pattern lets Claude fan out work to up to 10 sub-agents simultaneously and merge results—all within a single terminal session.
What Is the Anthropic Advisor Strategy? How to Cut AI Agent Costs by 12% Without Losing Quality
The Anthropic advisor strategy uses Opus as a senior adviser and Haiku or Sonnet as executor, reducing costs while improving benchmark performance.
What Is the Anthropic Advisor Strategy? How to Use Opus as an Adviser With Haiku or Sonnet
The Anthropic advisor strategy pairs Opus as a senior adviser with Haiku or Sonnet as executor, cutting costs by 12% while improving performance.
How to Build an AI Stock Trading Bot With OpenClaw: Strategy, Setup, and Lessons Learned
Learn how to build an autonomous stock trading agent with OpenClaw, including strategy design, cron job scheduling, and what not to do with options.
Inside Claude Code's Shared Task List: How Agents Avoid Conflicts
Claude Code's shared task list uses git worktrees and status flags to prevent file conflicts when multiple agents edit a codebase. Here's the mechanic in detail.
What Is the Claude Code Builder-Validator Chain? How to Build Quality Checks Into AI Workflows
The builder-validator chain uses one sub-agent to build and another to review, giving you automated quality checks without manual code review.
Run Multiple Claude Code Sessions in Parallel With Git Worktrees
Use the Claude Code -w flag to spin up isolated git worktrees and run several AI coding sessions in parallel — one per branch, with zero context bleed.
File-Based Signaling in Claude Code: Patterns for the Monitor Tool
Wire up the Claude Code monitor tool with file-based signals so background builds, tests, and watchers notify the agent on completion — no polling required.
What Is the Claude Code Operator Pattern? How to Run Multiple AI Agents in Parallel Terminals
The operator pattern lets you run multiple Claude Code sessions in isolated Git worktrees simultaneously, each with its own clean context window.
How to Save Tokens in Claude Code Using Opus Plan Mode
Using /model opus-plan in Claude Code switches to Opus for planning and Sonnet for execution, extending your session limit without sacrificing quality.
What Is the Claude Managed Agents Dashboard? How to Monitor Sessions, Environments, and Costs
Anthropic's Managed Agents dashboard gives you full visibility into agent sessions, token usage, environment permissions, and credential vaults.
What Is the Context Layer in AI? The Missing Step Between Basic Prompting and Agentic Workflows
Context is the most valuable asset on the internet. Learn how companies like Notion, Salesforce, and Snowflake own the context layer and why it matters.
What Is Cursor Remote Access? How to Control Your AI Coding Agent from Your Phone
Cursor now lets you run agents on your dev box and control them from anywhere, including your phone. Learn how to set it up and what it enables.
What Is the Gemini Notebooks Feature? How It Compares to Claude Projects and ChatGPT Memory
Gemini Notebooks organizes chats, files, and custom instructions in one space and syncs with NotebookLM. Here's how it stacks up against competitors.
LLM Wiki vs RAG: A Decision Framework for AI Knowledge Bases
Decide between an LLM Wiki and a RAG pipeline using accuracy, cost, and complexity. A side-by-side framework for picking the right knowledge architecture.
What Is the Middleware Trap in AI? Why Building on Models You Don't Own Is Risky
Most AI app builders are thin wrappers with no durable moat. Learn why the middleware trap is real and which structural layers are safe to build on.
How to Build a Transcript-to-ClickUp Agent With Anthropic Managed Agents
Learn how to build a sales call transcript processor that automatically creates ClickUp tasks using Anthropic Managed Agents and OAuth integrations.
Archon Explained: The Meta-Agent Framework for AI Coding Workflows
Archon is a meta-agent framework that orchestrates AI coding agents through YAML pipelines. Here's what a harness builder is and why teams are adopting one.
What Is GLM 5.1? The Open-Source Model That Matches GPT-5.4 on Coding
GLM 5.1 from ZAI is a 754B open-weight model under MIT license that rivals closed frontier models on SWE-bench. Here's what it can do.
Harness Engineering: Orchestrating AI Coding Agents
Harness engineering is the discipline of orchestrating multi-agent AI coding sessions into reliable pipelines. Here's how the practice is taking shape.