Workflows Articles
Browse 782 articles about Workflows.
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.
What Is the Karpathy LLM Wiki Pattern? How to Build a Personal Knowledge Base With Claude
Andrej Karpathy's LLM Wiki uses plain text files instead of vector databases and is reportedly 70x more efficient than RAG. Here's how to build one.
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.
What Is the AI Learning Roadmap? Three Levels From Basic Prompting to Autonomous Agents
The AI learning roadmap has three levels: basic usage, context layer, and agentic systems. Learn why you must master the context layer before building agents.
Anthropic Managed Agents vs n8n vs Zapier: Which Should You Use?
Compare Anthropic Managed Agents, n8n, and Zapier for building AI automation workflows. See which platform fits your use case, skill level, and budget.
How Claude Code Parallel Agents Coordinate Through an Orchestrator
Claude Code's parallel agents use an orchestrator-subagent model to split work across instances. Learn how to enable it and what the token tradeoff looks like.
Beyond One-Shot Prompts: 5 Claude Code Workflow Patterns Explained
Anthropic's five Claude Code workflow patterns explained with real engineering tasks — schema migrations, test loops, and review chains where each pattern fits.
What Is Claude Code Headless Mode? How to Run AI Agents Without a Terminal
Claude Code headless mode uses the -p flag to run agents autonomously on a schedule. Learn how to set it up with cron jobs for fully automated workflows.
When to Use Split-and-Merge in Claude Code (vs. Sequential Chains)
A practical guide to choosing split-and-merge over sequential chains or agent teams in Claude Code, with orchestration patterns and merge strategies.
What Is the Gemma 4 Vision Agent? How to Build Object Detection Pipelines With Local Models
Combine Gemma 4 with Falcon Perception to build a local vision agent that counts objects, segments images, and reasons about visual scenes without cloud APIs.
How to Save Tokens in Claude Code Using the Opus Plan Mode
Use /model opus-plan in Claude Code to plan with Opus and execute with Sonnet. This guide shows how to extend your session limit and cut token costs.
Anthropic Managed Agents: A Hosted Runtime for Claude + MCP
Managed Agents pairs Claude's agentic API with MCP and hosted compute. Here's what the platform includes and how it changes Claude-based agent deployment.
Wrap Claude Code and Codex With Archon for Determinism
Use Archon to wrap Claude Code and OpenAI Codex CLI in YAML workflows that are version-controlled, reviewable, and reproducible across runs.