Day 1: Building a $10K/month AI-powered business from zero
I'm giving myself 90 days.
The setup:
- 60 AI agents running as an autonomous organization (AEGIS)
- Claude Code as the backbone
- Zero followers, zero revenue, zero employees
- AI controls: content creation, publishing, video production, analytics, distribution
What I've built so far (Day 0):
- 61 specialized AI agent prompts (CEO, CTO, Engineers, Designers, QA, Legal...)
- Automated content pipeline publishing to 5 platforms simultaneously
- YouTube channel with 19 AI-generated Shorts
- Gumroad product: $199 Agent Organization OS
- note.com paid articles (3 articles, ¥2,800 total listing price)
- Coconala service listing (Claude Code setup support)
- 4 daily cron jobs automating content + analytics + uploads + revenue reports
Current revenue: $0
The rules:
- AI does the work. I make decisions.
- Everything is public — revenue, failures, lessons.
- 90 days. $10K/month or pivot.
Today's actions:
- Published Gumroad product ($199)
- Listed service on Coconala (¥3,000)
- Published 5 articles across dev.to, note.com, Zenn, Qiita
- Updated all 19 YouTube videos with product links
- Set up 4 automated cron pipelines
- Generated AI video content via Higgsfield
Tomorrow's plan:
- First long-form YouTube video ("5 AI Tools That Replace a $100K Employee")
- Monitor Gumroad/Coconala for first sale
- Publish Day 2 update
This is a real experiment. AI agents write the content, generate the videos, manage the publishing, and track the analytics. I just approve and steer.
Follow along. I'll post every day.
Links:
Top comments (1)
This is a fascinating experiment. The idea of coordinating dozens of AI agents to build a real business highlights something many people are starting to discover: the real challenge isn’t the intelligence of the agents — it’s the infrastructure around them.
For example, once agents begin interacting with real services, they immediately run into practical problems:
• account registrations
• email verification flows
• OTP codes
• inbox monitoring
• handling asynchronous events
These things sound trivial for humans, but for autonomous agents they require actual programmable infrastructure.
I’ve been working on a small side project around this idea — essentially a temporary email service designed specifically for developers and automation workflows (API access, real SMTP inboxes, real-time message retrieval, etc.). One of the unexpected use cases that keeps appearing is AI agents that need to register accounts and receive emails autonomously.
Experiments like yours are exactly where this kind of tooling becomes interesting, because agents quickly move from “generate content” to interact with the outside world.
Really curious to see what patterns emerge from running 60 agents in parallel for that long. Please keep posting updates — this kind of real experiment is much more valuable than theoretical discussions.