A CTO Called It "God Mode" — Garry Tan Just Open-Sourced How He Ships 10,000 Lines of Code Per Week as a CEO

Y Combinator's CEO just dropped his entire Claude Code setup on GitHub. 20,000 stars in days. One install command. Thirteen AI roles. And the internet is losing its mind.

The Tweet That Broke Dev Twitter

On March 12, 2026, Garry Tan — the man running the most powerful startup accelerator on the planet — posted a tweet that would rack up millions of impressions:

"I just open-sourced my entire Claude Code setup I used to average 10K LOC and 100 PRs per week in the last 50 days."

Within 48 hours, the GitHub repo had crossed 10,000 stars. By the time you're reading this, it's past 20,000. A CTO who tried it DM'd Tan directly: "Your gstack is crazy. This is like god mode."

That CTO predicted 90% of new repos would adopt it. Bold? Maybe. But when the CEO of YC drops his exact engineering workflow as a free, MIT-licensed toolkit, people pay attention.

Garry Tan — Y Combinator CEO, builder, and now apparently a 10,000-LOC-per-week machine. (Photo: Y Combinator)

So What Exactly Is gstack?

Here's the core insight: most people use Claude Code like a really smart intern — they tell it what to do, one thing at a time.

Garry Tan uses it like a full engineering team.

gstack is a collection of 13 specialized "skills" (slash commands) that turn Claude Code into distinct engineering roles. Each command triggers a different persona with different expertise, different priorities, and different failure modes to watch for.

Think of it this way: at a well-run startup, the CEO doesn't do code review. The QA engineer doesn't make product decisions. The release manager doesn't debate architecture. gstack encodes this separation of concerns into AI behavior.

One install command. Pure Markdown files. No dependencies beyond Claude Code itself (and Bun for the browser features). Nothing touches your PATH. Nothing runs in the background.

git clone https://github.com/garrytan/gstack.git ~/.claude/skills/gstack \
  && cd ~/.claude/skills/gstack && ./setup

That's it. You now have access to 13 engineering roles.

The 13 Roles: Your AI Engineering Team

Here's what you get:

Command	Role	What It Actually Does
/plan-ceo-review	CEO / Founder	Challenges your assumptions. Asks "what's the 10-star version of this?" before you write a single line
/plan-eng-review	Engineering Manager	Locks architecture, data flows, edge cases. Generates diagrams.
/plan-design-review	Senior Designer	Runs an 80-item design audit. Catches "AI slop" — those generic, soulless UI patterns
/design-consultation	Design Partner	Builds design systems from scratch
/review	Staff Engineer	Finds production bugs. Auto-fixes obvious issues. Found an XSS vulnerability that an entire human team missed
/ship	Release Engineer	Syncs main, runs tests, opens PRs. One command to ship
/browse	QA Engineer	Launches a real Chromium browser. 200ms response time. Sees your app the way users do
/qa	QA Lead	Tests your app, finds bugs, generates regression tests, verifies fixes
/qa-only	QA Reporter	Reports bugs without touching code
/qa-design-review	Designer + Coder	Design audit → implementation → before/after screenshots
/setup-browser-cookies	Session Manager	Imports real browser cookies for authenticated testing
/retro	Eng Manager	Analyzes your commit history. Tracks what you planned vs. what you actually shipped
/document-release	Technical Writer	Auto-updates stale documentation

The Browser Skill: This Is the Real Magic

Everyone talks about the slash commands. But the most technically impressive part of gstack is /browse.

Most AI coding tools that "see" your app launch a fresh browser instance every time, wait 3-5 seconds for it to spin up, then grab a screenshot. It's slow, it bloats your context window, and it's painful at scale.

Tan built something different: a persistent headless Chromium daemon that communicates over localhost HTTP. Cold start is 3-5 seconds. But after that? Every subsequent call runs in ~200ms.

That's 20x faster than the default Chrome MCP approach, with zero context bloat.

This is what unlocked /qa — Tan's self-described "massive unlock." Before the browser skill, AI code review was blind. After it? "Claude Code saying 'I SEE THE ISSUE' and then actually fixing it, generating a regression test, and verifying the fix — that changed how I work. The agent has eyes now."

Claude Code — the terminal-native AI coding agent that gstack builds on top of. (Image: Anthropic)

The Workflow: One Feature Request, Full Pipeline

Here's what happens when you use gstack on a single feature request:

1. /plan-ceo-review — Rethinks the product angle. "You asked for a settings page. What if it's actually an onboarding flow?"
2. /plan-design-review — 80-item design audit catches AI-generated UI patterns before they ship
3. /plan-eng-review — Architecture locked. Data flows mapped. Edge cases documented. Diagrams generated.
4. Coding happens — Claude Code writes ~2,400 lines across 11 files
5. /review — Staff-engineer-level code review. Catches a race condition. Auto-fixes it.
6. /qa — Opens a real browser. Clicks through the feature. Finds a preview rendering bug. Fixes it. Generates 9 regression tests.
7. /ship — Syncs with main, runs full test suite, opens a clean PR

From idea to pull request. One person. One AI. Multiple specialized roles.

The Numbers That Made People Lose Their Minds

Using this exact setup, over a 50-day period:

• 10,000+ lines of code per week (some days hitting 20,000)
• 100 pull requests per week
• 1,237 GitHub contributions in 2026 alone
• All while running Y Combinator full-time

The before-and-after is striking. Here's Garry Tan's GitHub contribution graph from 2013 — when he was a full-time engineer:

2013: 772 contributions as a full-time engineer at Initialized Capital.

And here's 2026 — as a part-time coder running YC:

2026: 1,237 contributions and counting — while serving as CEO of Y Combinator. The dark green blocks in Jan-Mar tell the story.

Let that sink in. The CEO of the world's most famous startup accelerator is out-shipping most engineering teams — as a side activity. And he's coding more now, as a CEO, than he did as a full-time engineer 13 years ago.

The Controversy: "It's Just a Bunch of Prompts"

Not everyone was impressed.

YouTuber Mo Bitar released a video titled "AI is making CEOs delusional," calling gstack "essentially a bunch of prompts in a text file."

On Product Hunt, one commenter wrote: "Garry, let's be clear and honest: if you weren't the CEO of YC, this wouldn't be on PH."

The critics aren't entirely wrong. gstack is Markdown files. There's no proprietary technology. Any experienced Claude Code user has probably built some version of this workflow.

But that's exactly the point.

The value of gstack isn't that it contains secret sauce. It's that it represents an opinionated, battle-tested workflow from someone who has actually shipped thousands of PRs with it. Instead of every developer spending weeks assembling their own prompts from tweets and blog posts, you get a working baseline in one command.

It's the difference between "everyone can build a web framework" and Rails. The opinion is the product.

Why This Actually Matters

Here's the bigger picture that most people are missing:

As AI coding tools mature, the models are converging. Claude, GPT, Gemini — they'll all write decent code. The differentiation is shifting from the models themselves to the workflows built on top of them.

Claude Code's skill system. Cursor's rules. Copilot's instructions. These are all mechanisms for encoding human expertise into AI behavior. And gstack is the first viral example of an opinionated skill pack — a pre-built engineering philosophy you install in one command.

The question isn't whether gstack's specific prompts are good. It's whether "skill packs" become the standard way developers configure AI tools. Instead of every team reinventing their own prompts from scratch, you'd install a "stack" that reflects a particular engineering philosophy — like choosing Rails vs. Django vs. Express.

We might be watching the birth of a new ecosystem.

The gstack repo on GitHub — one of the fastest-growing developer tools of 2026. (Image: GitHub)

How to Get Started (5 Minutes)

Requirements: Claude Code installed, Git, Bun v1.0+ (for browser features only)

Step 1: Install gstack

git clone https://github.com/garrytan/gstack.git ~/.claude/skills/gstack \
  && cd ~/.claude/skills/gstack && ./setup

Step 2: Add to your CLAUDE.md

The setup script will guide you through adding the gstack configuration to your project's CLAUDE.md file.

Step 3: Start using commands

• Start with /plan-ceo-review on your next feature
• Try /review on your latest changes
• Use /qa to let AI actually see and test your app
• Ship with /ship when you're ready

Pro tip: You don't have to use all 13 commands. Pick the 3-4 that match your workflow and build from there. /review, /qa, and /ship are the power trio.

The Bottom Line

Whether you love it or hate it, gstack is a signal of where software development is heading. The future isn't about whether AI can write code — it obviously can. It's about how we organize AI to write code well.

Garry Tan's answer: treat it like a team, not a tool.

20,000 GitHub stars suggest a lot of people agree.