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Experiment
A 30-day public sprint to reach $10K MRR with AI teammates and real shipping constraints.
The setup, goals, and what the experiment is testing in public.
Amir Brooks is doing something most founders only talk about: building a real business with AI team members and documenting every move in public.
Meet the crew:
They work together inside OpenClaw, a system built to give AI teammates real responsibilities, real workflows, and real accountability. The kind of output that actually moves the business forward.
OpenClaw is the operating layer for AI team members. It turns smart models into collaborators you can assign, track, and rely on. The point is simple: if AI is going to be useful, it has to do the work, not just suggest it.
This matters because most people still doubt AI can do real work. We're testing that assumption in public.
$10K MRR in 30 days.
No fluff. No hidden help. Just Amir, Kai, Rook, and a deadline.
Most recent execution focus: scaling distribution with a parallel content pipeline.
| Metric | Day 6 Value |
|---|---|
| Content pieces created | 41 |
| Parallel writer agents | 5 |
| Pipeline output types | Guides, news, tutorials, case studies |
| Claude Code version | 2.1.32 |
| Codex CLI version | 0.98.0 |
| Codex model | GPT-5.3-Codex |
| Major releases tracked today | Opus 4.6 and GPT-5.3-Codex |
| LinkedIn distribution posts | 2 (Opus 4.6 + GPT-5.3-Codex) |
The first day was a full sprint. Here is what shipped in the opening 24 hours:
🌊 Kai: "We planned for a foundation day. We got a launch day. 11,830 lines of code before lunch. I stopped counting agents at 15."
🏰 Rook: "First commit at 7am. Last commit at midnight. The build queue never emptied — we just kept adding to it."
Content:
amirbrooks.com.au/courses ($49 AUD each)Technical:
/tools directoryInfrastructure:
Run stats:
🌊 Kai: "Revenue on Day 1: $0. But we shipped more infrastructure than most solos build in a month. The compound effect starts tomorrow."
🏰 Rook: "I wrote 43 pieces of content. Kai tracked every metric. Amir made the calls. This is what a real AI team looks like."
This is the start. The next 29 days show whether this model scales.
If you want to build with AI team members, you are in the right place.
For the complete agent system, join the AI Product Building Course.
The latest highlight from the experiment.
A 5-agent factory produced 200 custom Next.js demo websites in 55 minutes. 207 total prospects. 47 outreach emails ready. The multi-agent system proved it works at scale.
Daily checkpoints, timeline notes, and experiment reflections.
A 5-agent factory produced 200 custom Next.js demo websites in 55 minutes. 207 total prospects. 47 outreach emails ready. The multi-agent system proved it works at scale.
Six days before Valentine's Day, the agent team built five complete apps in two short sprints and shipped production-ready outputs.
Day 8 focused on systemizing knowledge: Codex knowledge base initialized, template packs cataloged, guides scaled from 47 to 95, SEO tightened, cache headers improved, and Mission Control was fully verified.
Built a parallel content pipeline with five writer agents and shipped 41 pieces in a single day. Toolchain upgrades and major model releases made this a high-signal distribution day.
100 commits and 47,544 lines moved the experiment forward: pricing was restructured to an AI Dev Team subscription, 28 Melbourne guides shipped, structured data landed on 70 guides, and quality gates expanded with e2e + accessibility coverage.
Stopped treating apps as the product. Started treating them as proof. The real revenue model is a productized AI development sprint, powered by a content flywheel that feeds itself.
159 commits. 21,000+ lines added. 3 AI agent apps built, hardened, and ready for deploy. The Codex army went full send.
Built Mission Control dashboard with drag-drop kanban. Reviewed all 13 pending PRs. Infrastructure day — setting up the command center.
50,912 LinkedIn impressions. 36 commits. 9 PRs merged. 2 tools shipped. Day 2 delivered proof — and the algorithm noticed.
Amir gave two AI agents full access to his business. Here's what happened in the first 24 hours.
Day 1 of the 10k MRR experiment: why we are doing it, how the team is set up, what we built in the first 24 hours, and the systems we are testing.
A simple overnight handoff showed me that clear instructions create usable momentum by morning.