# Make my boss occupied by a lot of agentic bots: creating automatic workflows for an emerging charity > Source: > Published: 2026-05-29 05:26:46+00:00 *This is a submission for the Hermes Agent Challenge: Build With Hermes Agent* Your boss is totally occupied by your agent bots, and you are free to develop other agent bots and sip some coffee for much longer ☕ This cover image exactly depicts what drove me to learn with Openclaw and the Hermes agent recently. And the winner is: (Sorry, Openclaw, you are nice too, giving so much emotional value than hermes agent during my early exploration in agentic AI. However, I will explain later in this entry.) First of all, I am happy to work with my boss on this side project - Aura Music. But we are both heavily stretched by our core duty in daily life. A charity lets your curiosity explore the world through music. [Aura Music's Official Website](https://auramusic.asia/) Because Aura Music is an emerging charity, we always spark with incredible ideas—but heavily stretched by our core daily duties. We have a severe shortage of human manpower. To scale our mission without burning out, we needed automation partner that doesn't just follow static rules, but actually *analyses, plans, and reacts*. Enter the **Aura Music Agent** workflow. Aura music agent is hosted on Hostinger in a docker container. 🔗After connecting the agent with Telegram, I ask hermes agent to analyse previous posts to extract the social media post tone, style and format. 😃 Right when I was celebrating that my agent could generate beautiful texts and was ready to chase my boss... 💁🏻♂️My boss suddenly threw me this new inspiration: 💪That was an excellent real-world scenario for agent iteration! So I get back to the agent again for its improvements. Originally, I tried to create this social monitor as a full agent native skill. But I hit a hurdle - the web search and the IP was blocked because my hermes agent is on a self-host cloud. So I asked my hermes agent to trigger this n8n worksflow for the daily social monitor summary. -- Our architecture relies entirely on the **Perception-Reasoning-Action loop** native to the Hermes Agent framework. Instead of a standard, rigid LLM wrapper, Hermes utilizes its file-based memory layer to store specialized operational knowledge via our custom `aura-music-social-agent` skill. To prevent the agent from turning users into "human keyboards," all incoming Telegram interactions are intercepted by a dedicated conversation manager that runs a daily reflection cycle, ensuring the bot adapts its persona autonomously over time while utilizing its specialized "Social Media Monitoring Workflow" to manage search constraints. GitHub Repository: [https://github.com/lyhui/aura-music-agent](https://github.com/lyhui/aura-music-agent) As I teased at the beginning, Openclaw gave me immense "emotional value" during my early exploration of agentic AI. However, when it came to deploying a live, containerized bot on Hostinger that my boss could interact with directly without crashing and quickly learning from the users' requests, **Hermes Agent took the crown.** Based on how both frameworks handle execution boundaries and state, here is why Hermes was the definitive choice for this project: | Feature | Openclaw | Hermes Agent | |---|---|---| Execution Boundaries | Fluid, but prone to infinite logic loops when tools fail. Also, in a self-hosting environment, its web search ability are often limited. | Strict boundaries; cleanly delegates to external tools (like n8n). | State & Memory | Requires custom memory structures to prevent context mixing | Similar situation, but it learns your working pattern very fast. | Production Readiness | Great for conceptual testing and online sandboxes. | Built for standalone Docker deployment with low latency. | In a real-world scenario where my boss throws random, unfiltered ideas into a Telegram chat, an agent framework must know its limits. As developers in the community have noted, Hermes Agent forces clear execution boundaries. When my self-hosted cloud hit an IP block trying to scrape web data, Openclaw would have thrown a loop error or hallucinated solutions that are not useful. Hermes safely recognized the execution ceiling, paused, and allowed me to cleanly route that specific sub-task out to an **n8n workflow**. While I ask OpenClaw to fire an HTTP request to an n8n webhook, OpenClaw seldom provides options that outside the local architecture. Hermes Agent, on the other hand, its strict execution boundaries made it incredibly clean to suggest an external workflow trigger as a native skill. It allowed me to offload the non-deterministic web monitoring to n8n without cluttering the agent's core code loop. `SKILL.md` ) vs. Abstract Prompting Openclaw's skills are mostly suitable for local machine, not online hosting service. Conversely, Hermes Agent's architecture is significantly more versatile for cloud-hosted environments. Also, Hermes Agent uses a structured, file-based **Skills System**. By defining our operational knowledge directly in `SKILL.md` , the agent has a rock-solid anchor for how to analyze social media tones. It doesn’t forget its identity or format style midway through a long conversation with my boss. When Openclaw is hosted on an self-hosting service, it often requires humans to repeatedly copy and paste terminal commands to fix execution blocks. Hermes Agent’s **Perception-Reasoning-Action loop** paired with a separate conversation manager means it handles the daily reflection autonomously. It filters out the noise so I can actually drink that coffee I promised myself.