CLAUDE CODE

One dev, one CLI, 24 subdomains, and a lot of parallel agents. The playbook for shipping an AI app portfolio.

Four agents, same tasks. Honest trade-offs from a developer shipping production apps with all of them.

CLAUDE.md is the highest-leverage file in any Claude Code project. Here's what goes in one, what doesn't, and the patterns that actually ship.

Skills are how you stop copy-pasting the same workflow into Claude Code every session. What they are, how to write one, and where to find hundreds ready to use. Fact-checked against Anthropic's docs.

Autocomplete wrote the line. Agents write the pull request. The shift from Copilot to Claude Code, Cursor Agent, and Devin - explained with links to the docs that prove every claim.

MCP is the USB-C of AI agents. What the Model Context Protocol is, why Anthropic built it, and how to install your first server in Claude Code or Cursor. Fact-checked against the official MCP spec.

Updated 2026 comparison of Aider and Claude Code using official docs and current workflow patterns: architecture, control surfaces, cost behavior, and where each fits best.

A practical operational guide to Claude Code usage limits in 2026: plan behavior, API key pitfalls, routing choices, and team controls using hooks and subagents.

A deep comparison of Claude Code and OpenAI Codex app based on official docs and product updates: execution model, security controls, pricing, workflows, and when each wins.

Hacker News keeps arguing about Claude Code, Codex, skills, MCP, and orchestration. Under the noise, the same four truths keep surfacing: workflows matter more than demos, verification is the bottleneck, skills beat prompts, and orchestration matters more than raw autonomy.

The coding-agent workflow is maturing past giant hand-written prompts. The winning pattern in 2026 is a control stack: project rules, reusable skills, bounded sub-agents, and deterministic tools around the model.

AI-native development is not about using AI tools. It is about restructuring how you plan, build, review, and ship code around agent capabilities. The five-layer stack that defines how the most productive developers work in 2026.

How to use Claude Code's Task tool, custom sub-agents, and worktrees to run parallel development workflows. Real prompt examples, agent configurations, and workflow patterns from daily use.

How to use AI agents to plan, scaffold, build, test, and deploy a SaaS product. Parallel development patterns, real workflow examples, and the operational details that determine whether your AI-assisted build succeeds or fails.

Context engineering is the practice of designing the persistent information that surrounds every AI interaction. CLAUDE.md files, system prompts, skill libraries, and memory systems. It is the single highest-leverage skill for developers working with AI agents in 2026.

An opinionated guide to the MCP server ecosystem in 2026. Curated picks by category, real configuration examples, installation commands, and honest assessments of what works and what does not.

Deep comparison of the top AI agent frameworks - LangGraph, CrewAI, Mastra, CopilotKit, AutoGen, and Claude Code.

How to go from idea to deployed SaaS product using Claude Code as your primary development tool. Project setup, feature building, deployment, and iteration.

How a single developer shipped 100+ features in one day using Claude Code, parallel agents, and the never-ending todo system.

AI agents fail in ways traditional debugging cannot catch. Here are the tools and patterns for finding and fixing broken agent loops, tool failures, and context issues.