Nicheloom

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AI agents run my one-person company on Gemini's free tier

$0/month

Details

External ID
47296664
Source
HN
Company
—
Product
—
Website domain
—
Launched
March 8, 2026
Cohort
—
Upvotes
16
Upvotes percentile
0.6968019680196802
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

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/agentStack: 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-fleetHappy to answer questions about the architecture, token budgeting, or what it's actually like running AI agents 24/7 as a one-person company.

Enrichment

Theme
Vertical
Horizontal
Function
Agent / copilot
Audience
B2C
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
ai agents to automate solo business operations
Manually corrected
False

Could you build this?

Yes This is a collection of scripted prompt workflows and cron jobs orchestrating Gemini's free API tier on local machines.

Discussion

20 comments analyzed.

Competitors mentioned: Telegram bot with GPT-4o-mini for RSS filtering, Traditional scheduling tools with poor UX, AI courses and prompt-engineering services, Other social media automation/posting tools

Concerns raised: Dashboard visuals are CSS animations without live data backing (acknowledged as incomplete), Content generated by LLM with agent-written comments creates endless feedback loop of generated garbage, ROI unclear: 12k followers may be dead weight if they don't convert to revenue, Only one paying subscriber in Taiwan; early and small MindThread subscription revenue, Suspicious rapid posting pattern (10 comments in 6 minutes, ~800 words) raises authenticity questions

Feature requests: Live systemd logs piped into dashboard with clean architecture, Real-time monitoring data visualization for multi-agent setups, Customizable agent dashboards for other teams, Better dashboard integration with actual server-side inference metrics

Competitors

Other products that read as similar to this one — 518 launches clear the similarity bar, closest 8 shown.

Attention rank: #211 of 519 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 129 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.