AI Services Market › Use cases › Research & Knowledge
Research & KnowledgeDone with Hermes Agent 2026-10-22
Run a 24/7 local agent that curates news digests
The author runs Hermes Agent on a Proxmox VM with a local Qwen model, monitoring RSS feeds, curating news digests, and reporting via Telegram.
- What They Did
- Hermes Agent runs on a small Proxmox VM (4 vCPU, 8 GB RAM, no GPU) and calls a Qwen 3.6 MoE llama-server on the author's RTX 5060 Ti. The author sent one Telegram message asking for a daily 8 AM cron job. Hermes created it, pulled RSS and MCP data, compared against its memory, and sent briefings to Telegram topics.
- How It Went
- The agent delivers daily briefings and a 9 AM startup/VC digest at no API cost. Memory builds up over weeks into trend-aware reports, and Hermes writes reusable skills. The post gives no formal quality measurements.
- Worth Knowing
- Don't over-prompt the cron job: a clear goal worked better than detailed steps. The fast MoE model beat the dense 27B, which was about 3x slower.
Try it yourself with Hermes Agent
Set up a news digest for me. Monitor these RSS feeds: [list of feed URLs], and every [morning at 7am / every 4 hours] pick the [5-10] most relevant stories on [topics I care about], skipping duplicates and clickbait. Send me a short digest on [Telegram / other channel] with a one-line summary and link for each story, and confirm by sending me a test digest now.
Do this with a skill.
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