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 ) 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 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 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.
Discussion Highlights (9 comments)
r0fl
The GitHub link in the post is 404
CubsFan1060
This 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?
OsrsNeedsf2P
What's your MRR?
TutleCpt
It sounds like a business that produces no valuable product and no real use. This is what the internet has become.
rappatic
I guess it shouldn’t be surprising for this post to be LLM-written when the author’s point is that they use LLMs to write a bunch of social media posts, but it still makes me a little sad.
soared
Has this generated any revenue? What’s the point of having 27 threads accounts, rather than 1 high quality one? Do none of these places care if they’re botted? So you made 4 agents, a website for a company that says the make agents - but what’s the product/service? Agent making? Website is AI slip - there is a specific style that Ai Studio uses and it’s exactly your website.
brunohaid
OK, the whats the endgame for flooding the zone with agent outputs question aside: The visualization of what the agents are up to in the "office" on the dashboard is incredibly cute.
Western0
Why not local models? W H Y ?
ppcvote
A bit of context on why I built this: 3 months ago I had zero experience with any of this — no AI development, no automation, no open source. I'm a solo founder in Taiwan where smartphone penetration is nearly universal but AI adoption in daily work is still very early. As I started building, I realized these tools can genuinely change how people work and live — not just for developers, but for small businesses and solo operators who don't have engineering teams. So I packaged what I learned into services and open-sourced the playbook. This is also my first time posting on HN. My English isn't strong enough to write essays natively, so I use AI to help with the writing — but the ideas and intent are mine. Seemed fitting given what I'm building. I'm not trying to sell anything here. I just want to show that you can run real operations with AI agents on zero budget, and I want to make these tools more accessible in my country.