Inside Claude Code’s 5‑Agent Playbook: How One Developer Turns Coding Into a Real‑Time Strategy Game

Introduction

In the past week, a Twitter thread by Anthropic’s chief coder, Boris Cherny, has gone viral. The thread doesn’t just describe a new tool – it lays out a workflow that turns a single developer into a multitasking command‑center, orchestrating five AI agents to write, test, and ship code faster than a traditional engineering department.

The 5‑Agents Command Center

Cherny’s method is simple, yet elegant. He keeps five tabs open in iTerm2, each running a Claude instance. Using system notifications, he knows when a Claude needs input and can shift his focus instantly:

* Test runner – runs full test suites * Refactor bot – cleans up legacy modules * Doc writer – drafts documentation * Bug fixer – handles issue triage * IDE helper – suggests code snippets

This multitasking approach mirrors a real‑time strategy game more than classic coding, where the developer is a fleet commander, not a lone coder.

The Counterintuitive Power of the Slowest Model

While many in the industry chase low latency, Cherny prefers the heavy‑weight Opus 4.5. It may be slower, but its superior tool‑use and fewer corrections mean that the human time saved outweighs the compute cost. In a world where correcting AI mistakes costs more than generating code, the “compute tax” is a worthwhile trade‑off.

Learning from Mistakes: A Shared Knowledge Base

To tame AI amnesia, the team maintains a single CLAUDE.md file in the repo. Every error is recorded as a rule, turning the codebase into a self‑correcting organism. When a pull‑request review spotlights a flaw, the developer adds it to the file, ensuring the next run of Claude never repeats that mistake.

Automation with Slash Commands and Subagents

Cherny leverages custom slash commands (e.g., /commit-push-pr) and subagents that specialize in particular phases of development. These agents handle boilerplate Git operations, run end‑to‑end tests, or simplify architecture, allowing the developer to focus on higher‑level logic.

Verification Loops: The Real Unlock for AI‑Generated Code

The key to Claude Code’s success is its built‑in verification loop. Each change is automatically tested through browser automation, test suites, or shell scripts. By iterating until the UI feels right, the AI boosts code quality by 2‑3×, making manual QA largely obsolete.

The Future of Software Engineering

Cherny’s approach signals a paradigm shift: AI is no longer a passive autocomplete but an active workforce. Developers who adopt this mindset can multiply their output fivefold and play a different game—one where typing is a relic.

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