I spent 3 weeks building a rulebook for my AI coding agent. Week 1 after launch: 20 stars, 8 forks, and one distribution lesson I didn't see
I'm an engineer, not a marketer. So naturally, I spent 95% of my time on the product and 5% on distribution. Week 1 taught me that ratio is exactly backwards.
Here's what happened — and more importantly, what I built and why it might matter to you.
The problem I was trying to solve
If you've spent serious time with Claude Code or Google Antigravity, you've hit this: the agent does something you didn't ask for. It creates a file. It refactors something adjacent. It makes an assumption and runs with it.
It's not the model's fault. You didn't give it a rulebook.
I spent three weeks building that rulebook. The result is Full Stack HQ — a CLAUDE.md + agent stack that installs in 30 seconds and turns your AI from an unpredictable collaborator into something closer to a disciplined senior engineer.
The core idea is permission-first:
You: "Add JWT authentication"
Agent: Here's my plan:
Phase 1 — Create auth module
Phase 2 — Add guards to protected routes
Phase 3 — Implement refresh token rotation
[APPROVAL NEEDED] Proceed with Phase 1?
You: PLAN APPROVED
Agent: [implements Phase 1 only, then stops]
The agent never acts without your explicit sign-off. It sounds simple. The difference in practice is significant.
What's in the box
10 specialist agents — frontend, backend, database, architect, security, DevOps, and more. Each triggered by name, each with deep context for its domain.
28 skill modules — Next.js, NestJS, Prisma, TypeScript, auth patterns, Docker, GitHub Actions. The agent knows your stack before you explain it.
10 slash command workflows — /plan, /debug, /preview, /orchestrate, /ui-ux-pro-max. Repeatable processes, not one-off prompts.
One install command — works with Claude Code and Google Antigravity IDE out of the box.
curl -fsSL https://raw.githubusercontent.com/sabahattink/antigravity-fullstack-hq/main/install.sh | bash
Week 1 numbers
I launched quietly. No existing audience. No newsletter. No Twitter following worth mentioning.
Metric Value
GitHub stars 20
Forks 8
Clones (14 days) 37
Unique cloners (48h) 22
Dev.to readers 21
Hacker News 6 points
Not viral. But not zero — and the trajectory matters more than the snapshot.
The distribution lesson I didn't expect
I assumed the technical audience would be the easiest to reach. Developers already use Claude Code. They already feel the pain. Just show them the solution, right?
Wrong. Two things surprised me:
- The framing mattered more than the feature set.
"Permission-first workflow" didn't land immediately. People had to think about what it meant. But "your AI asks before it acts" — that clicked in one sentence. Same concept. Different words. Completely different conversion.
- Karma gates are real.
Reddit was my primary distribution plan. Turns out r/ClaudeAI and r/webdev both have karma thresholds that blocked me from posting links on day one. I was sitting on a finished product with nowhere to put it.
The fix: spend the week before launch commenting genuinely in technical threads. Build the number first. It feels backward but it's the actual sequence.
What I'd do differently
Start distribution 3 weeks before launch, not after. The GitHub stars, the Reddit karma, the IH presence — all of it compounds. Trying to build it in parallel with the product means you're always behind.
Pick one audience and go deep before going wide. I tried to reach Claude Code users, Antigravity users, enterprise IT leaders, and vibe coders simultaneously. Spreading that thin meant none of them felt like I was talking specifically to them.
The product page is permanent. The launch day isn't. Product Hunt taught me this — the page lives forever and keeps accumulating traffic. Treating launch day as the only moment is the wrong mental model. Every good comment, every honest update, every genuine reply is still working six months from now.
What's next
Reddit r/ClaudeAI launch post (waiting on karma)
Submit to more awesome-claude lists
v1.1 with a web installer for non-technical users
Enterprise CLAUDE.md template variant
If you're using Claude Code or Antigravity and want to stop being surprised by your agent — give it a look.
And if you've launched a dev tool with no audience before: what was the one channel that actually moved the needle for you?
The strongest insight here is that you’re not really selling a “CLAUDE.md stack.” You’re selling control over agent behavior. That is a much sharper frame because every serious developer using AI agents eventually hits the same fear: the agent starts acting beyond the boundary they had in mind.
“Your AI asks before it acts” is the line I’d build around. It is clearer than permission-first workflow because it immediately describes the pain and the fix. The enterprise angle also becomes more believable from there, because teams do not just need faster coding agents. They need predictable, auditable, approval-based execution.
One thing I’d watch is the Full Stack HQ name. It explains the developer scope, but it may feel too broad and tutorial-like if this becomes a governed agent workflow layer. For a harder AI-devtool/security direction, Davoq.com would carry the product with more infrastructure weight.
This reframe landed. "Control over agent behavior" is more precise than anything I've written so far — it names the actual fear, not the mechanism.
The auditable/approval-based angle for enterprise is something I've been circling but not stating directly. Teams don't just want speed, they want to be able to explain to a manager exactly what the agent did and why. That's a different sale than "better CLAUDE.md."
On the name: you're right that Full Stack HQ skews tutorial. It made sense for the initial positioning (broad config kit for full-stack devs) but if this moves toward governed agent workflows, that name creates the wrong expectation. Davoq is interesting — curious what made that one come to mind specifically. Infrastructure weight is real but it also needs to hint at the control layer, not just the tooling layer.
What would you build first if you were going harder on the enterprise/security direction — the audit log, the approval workflow, or the policy layer?
Sabahattin, I’d build the approval workflow first.
Audit logs are important, but they are after-the-fact. Enterprise trust starts before the agent acts.
The real control moment is whether the agent can pause, explain intent, request approval, and stay inside a defined boundary before making a risky change.
That is the wedge.
Policy and audit become stronger after that, but approval is the first thing that makes the system feel safe enough for serious teams.
That is also why Davoq.com came to mind.
Full Stack HQ works for the current version, but it sets the wrong expectation if you are moving toward governed agent workflows. It sounds like templates, tutorials, or general dev tooling.
Davoq feels more like infrastructure: short, serious, controlled, and not tied to Claude, prompts, or one stack. It can carry governed agent execution much better.
My honest view: if this direction is real, the name should not wait too long. Once developers attach the product to a tutorial-style brand, it becomes harder to reposition it later as enterprise control infrastructure.
I own Davoq.com, so if this direction feels serious, I can keep the acquisition simple and founder-friendly.
I would not rename just for aesthetics. But if you already see Full Stack HQ creating the wrong expectation, Davoq is exactly the kind of name worth securing before the category gets more fixed.
Happy to answer questions about the permission-first architecture or the CLAUDE.md structure if anyone's curious. What's your current AI coding setup look like?