Workflows Articles
Browse 1006 articles about Workflows.
Is Your Tech Stack Agent-Ready? The 5-Question Diagnostic for Evaluating Any Tool as Agent Infrastructure
Not every tool can serve as an agent control plane. Here's the 5-question diagnostic — state machines, ownership, audit history
Vibe Coding vs Agentic Engineering — Karpathy's Framework for Knowing Which One You're Actually Doing
Karpathy draws a hard line: vibe coding raises the floor for beginners; agentic engineering raises the ceiling for professionals.
What Is the Agent Handoff Pattern? How to Design AI Outputs for Downstream Use
The handoff pattern ensures your agent's output can be consumed by other agents or tools. Learn why portable formats like HTML, JSON, and Markdown matter.
What Is the Self-QA Loop? How AI Agents Critique Their Own Output Before You See It
A self-QA loop has an AI agent render, screenshot, and critique its own output before handing it to you. Here's how to implement it in your vertical agent.
What Is Structured Memory in AI Agents? How to Build Persistent Context
Structured memory lets AI agents reuse context across sessions without bloating the window. Learn how to build portable memory artifacts for your agents.
How to Build an Agent-Native Product: Lessons from OpenClaw, Hermes, and Codex
Agent-native products use outcome-based prompts instead of step-by-step instructions. Learn the design patterns behind the best agentic tools available today.
How to Build an Agentic Coding Workflow with Claude Code and Jira: A Full Walkthrough
Learn the complete agentic coding workflow: ideation, PRD creation, Jira ticket generation, PIV loop implementation, and system evolution using Claude Code.
What Is Agentic Context Grounding? The Pattern Behind Claude Design and Vertical AI Apps
Agentic context grounding reads a source of truth before generating anything. Learn the six patterns behind Claude Design that apply to any vertical AI agent.
What Is an AI Memory System? How to Build Persistent Context for Your Agents
AI models are stateless but your work isn't. Learn how to build a durable memory layer using SQLite, Postgres, embeddings, and MCP servers for your AI agents.
How to Build an AI Orchestrator That Delegates to Cheaper Sub-Agent Models
Use a frontier model as orchestrator and cheaper open-weight models for heavy lifting. This hybrid approach cuts costs while maintaining output quality.
How to Use AI Voice Agents for Customer Support: Low-Latency Models Explained
Low-latency voice models like Grok Voice ThinkFast enable real-time AI phone agents. Learn how to build and deploy voice agents for customer support.
How to Run Claude Code with Cheaper Models: OpenRouter, NVIDIA NIM, and Ollama
Use Claude Code's interface with DeepSeek, Gemma, and other affordable models via proxy. Get 80–90% of Opus quality at 2–5% of the cost.
What Is Gemini File Generation? How to Create PDFs, Excel, and Docs with AI
Gemini can now generate PDFs, Word docs, Excel sheets, Google Slides, and more directly in chat. Here's how to use this feature to speed up document workflows.
How to Use the Google Workspace MCP Server with Claude Code and Codex
Connect Gmail, Drive, Calendar, and Chat to your AI coding agents using the Google Workspace MCP server. Here's how to set it up and what you can automate.
Local AI vs Cloud AI: How to Decide What to Own and What to Rent
Not all AI work belongs in the cloud. Learn how to route tasks between local models and cloud APIs based on privacy, cost, and context requirements.
How to Use Ollama to Run AI Models Locally: A Beginner's Setup Guide
Ollama lets you run open-weight models like Gemma 4 and Llama locally on your own hardware. Here's how to get started with local AI inference in minutes.
How to Use OpenAI Codex for Everyday Work: 10 Use Cases Beyond Coding
OpenAI Codex isn't just for developers. Discover 10 practical use cases for knowledge workers including workflow audits, form creation, and slide deck drafting.
OpenAI Codex vs Claude Code: Which AI Coding Agent Wins for Non-Technical Users?
OpenAI Codex and Claude Code are both moving toward non-technical users. Compare their browser control, UX, integrations, and real-world coding performance.
What Is the PIV Loop? The Core Methodology for AI-Assisted Software Development
The PIV loop—Plan, Implement, Validate—is the repeatable process for handling individual coding tickets with AI agents. Here's how to apply it to any project.
Software 1.0 vs 2.0 vs 3.0: How AI Is Rewriting the Rules of Programming
Andre Karpathy's framework explains how AI shifts programming from writing code to prompting models. Here's what Software 3.0 means for builders and developers.