6 ms·
Show HN: AI agents run my one-person company on Gemini's free tier – $0/month
I'm a solo dev in Taiwan. I built 4 AI agents that handle content, sales leads, security scanning, and ops for my tech agency — all on Gemini 2.5 Flash free tier (1,500 req/day). I use ~105. Monthly LLM cost: $0.
Architecture: 4 agents on OpenClaw (open source), running on WSL2 at home with 25 systemd timers.
What they do every day:
- Generate 8 social posts across platforms (quality-gated: generate → self-review → rewrite if score < 7/10)
- Engage with community posts and auto-reply to comments (context-aware, max 2 rounds)
- Research via RSS + HN API + Jina Reader → feed intelligence back into content
- Run UltraProbe (AI security scanner) for lead generation
- Monitor 7 endpoints, flag stale leads, sync customer data
- Auto-post blog articles to Discord when I git push (0 LLM tokens — uses commit message directly)
The token optimization trick: agents never have long conversations. Every request is (1) read pre-computed intelligence files (local markdown, 0 tokens), (2) one focused prompt with all context injected, (3) one response → parse → act → done. The research pipeline (RSS, HN, web scraping) costs 0 LLM tokens — it's pure HTTP + Jina Reader. The LLM only touches creative/analytical work.
Real numbers:
- 27 automated Threads accounts, 12K+ followers, 3.3M+ views
- 25 systemd timers, 62 scripts, 19 intelligence files
- RPD utilization: 7% (105/1,500) — 93% headroom left
- Monthly cost: $0 LLM + ~$5 infra (Vercel hobby + Firebase free)
What went wrong:
- $127 Gemini bill in 7 days. Created an API key from a billing-enabled GCP project instead of AI Studio. Thinking tokens ($3.50/1M) with no rate cap. Lesson: always create keys from AI Studio directly.
- Engagement loop bug: iterated ALL posts instead of top N. Burned 800 RPD in one day and starved everything else.
- Telegram health check called getUpdates, conflicting with the gateway's long-polling. 18 duplicate messages in 3 minutes.
The site (https://ultralab.tw https://ultralab.tw) is fully bilingual (zh-TW/en) with 21 blog posts, and yes — the i18n, blog publishing, and Discord notifications are all part of the automated pipeline.
Live agent dashboard: https://ultralab.tw/agent https://ultralab.tw/agent
Stack: OpenClaw, Gemini 2.5 Flash (free), WSL2/systemd, React/TypeScript/Vite, Vercel, Firebase, Telegram Bot, Resend, Jina Reader.
GitHub (playbook): https://github.com/UltraLabTW/free-tier-agent-fleet https://github.com/UltraLabTW/free-tier-agent-fleet
Happy to answer questions about the architecture, token budgeting, or what it's actually like running AI agents 24/7 as a one-person company.
- r0fl 7mo agoThe GitHub link in the post is 404
- sheepscreek 7mo agoThis is a bit funny - I hope the repo is private and not hallucinated.
- ppcvote 7mo agoHa! Not hallucinated, just a typo in the org name. Correct link: https://github.com/ppcvote/free-tier-agent-fleet https://github.com/ppcvote/free-tier-agent-fleet
- ppcvote 7mo agoThanks for catching that! The correct repo link is https://github.com/ppcvote/free-tier-agent-fleet https://github.com/ppcvote/free-tier-agent-fleet — I used the wrong org name in the post. Everything's there: scripts, timers, config, and docs.
- CubsFan1060 7mo agoThis feels like we're still on the march to the dead internet. What percentage of your interaction do you want/think is actually real people, and not just agents talking to other agents?
- deleted 7mo ago[deleted]
- hk1337 7mo agoI’d be okay with it generating the posts and the reports of the financials and such but you need some human interaction in there. Generate the posts with AI so it can free up your time to interact with people replying to the post. Or write the bigger, longer, more content posts yourself with maybe some AI assistance in places here and there then use AI to create smaller posts from your larger posts. Still keeping with the human interaction with those that reply to the posts.