拒絕被大廠 AI 綁架！hermes-agent 讓你用 5 美元 VPS 跑自己的進化型 AI
GitCovery · 2026-07-03 · 6 min
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這集不是走馬看花，我們將帶你深入剖析一個會「自我進化」的 AI 代理程式 hermes-agent！它最大的特色就是能建立長期記憶，從你的每一次互動中學習，變成真正懂你的數位夥伴。 🔥 本集專案： 🤖 NousResearch/hermes-agent：一個會跟你一起「長大」的 AI 代理人！它能從經驗中學習，自己創造並優化技能，愈用愈聰明。 🎯 深度解析重點： • 獨特的「封閉式學習循環」架構設計 • AI 如何自主學習、創建並優化「技能」 • 持久性記憶的建立與運作機制 • 低資源需求的部署潛力與應用場景 ⏱️ 時間戳：
✨ Episode Outline — click any point to jump to it in the episode
Problem solved
Stateless AI assistants forget everything each session; hermes-agent gives AI long-term memory and self-evolution.
Benefits
- Long-term memory spanning weeks to months
- Self-evolving via closed learning loops
- Autonomous skill creation from successful tasks
- Low-cost 24/7 cloud agent on a $5 VPS
- Model-independent, MIT-licensed, data sovereignty
Use cases
KPIs / results
- Over 200,000 GitHub stars, hundreds added daily
- Runs on a $5 VPS
Tools / build
- Hermes Agent
- FTS5 full-text search + LLM hybrid memory
- AgentSkills.io autonomous skill system
- Modal/Daytona serverless persistence
📑 Chapters — tap a time to jump there
00:00
Opening
- GitCovery intro to GitHub Trending open-source projects
00:10
節目介紹
- Framing hermes-agent as AI that grows with you
00:26
NousResearch/hermes-agent
- NousResearch hermes-agent: long-term memory, self-evolution
- Closed learning loop, skill creation, serverless persistence
- MIT-licensed, model-independent; setup threshold and security risks noted
🌐 This transcript was automatically translated to English from the original.
Hello fellow developers, welcome to GitCovery. Today we will take you to quickly master the most popular open source projects on GitHub Trending so that you will not miss any technical trends worthy of attention. Today we will give an in-depth analysis of a popular project on GitHub, Hermes-agent, an AI agent that claims to grow with you. Its biggest breakthrough is that it can establish long-term memory and evolve itself. It turns an AI assistant that can only have a single conversation into a digital partner that truly understands you and becomes more powerful the more you use it. Your AI Is the assistant like a goldfish? The memory is only 7 seconds, and every conversation is a new beginning. There is no way to become a true productivity partner. What if there is an open source project now that can allow AI to have long-term memory for weeks or even months, and it can also learn and evolve on its own from experience. What kind of changes will this bring to our collaboration with AI? The Hermes-agent we are going to analyze in depth today is officially challenging this problem. Hermes-agent was developed by the well-known AI research institution NOS Research. It focuses on a core concept. This is an AI agent that will grow with you. Its goal is very clear, which is to solve the biggest pain point of current AI assistants: no state and short memory. How popular is this project on GitHub? It has accumulated more than 200,000 stars and is still increasing by hundreds of stars every day. The popularity of the developer community is evident. But please note that Hermes-agent is not just a chatbot. It is a complete framework designed to run for a long time, have cross-platform access, and also has the ability to self-improve. The most troublesome thing about most AI assistants on the market is its statelessness. It sounds very professional, but to put it bluntly, every conversation is an independent event. You must take the trouble to do it. Repeatedly providing the same background information is really inefficient when dealing with complex or long-term tasks. In the past, developers were accustomed to treating AI as a Korean-style library that can be used as taught and thrown away after use. However, the price of this model is that AI can never truly understand your personal preferences, workflow or your long-term goals. Hermes-agent has chosen a completely different path. It does not pursue 100 points in a single task, but focuses on building a persistent agent. This design concept allows AI to transform from a short-term tool. Have the opportunity to transform into a digital partner who can build a long-term relationship with you and grow together. The core of Hermes-agent's technology is a unique set of closed learning loops. This mechanism gives it the superpower of self-evolution. The first is its autonomous skill creation system. When the agent successfully completes a complex multi-step task, the matter is not over yet. It will use a large language model LLM to abstract this successful workflow into a skill that can be reused and follow the open standards of AgentSkills.io It's like a great chef who invents a new dish. He will take the initiative to write down the recipe, and you can follow it directly in the future without having to start over. What's more, Hermes-agent has a powerful cross-painting memory search capability. It combines FTS5 full-text search and LLM planting capabilities. You can think of FTS5 as a super-fast library indexing system that can find all relevant records from a huge conversation history in an instant. But it does not just throw a bunch of original materials to you, it will also invite LLM again. This smart librarian condenses these scattered records into a concise and highly relevant summary of the current problem. This hybrid search architecture can be said to take into account both search efficiency and contextual accuracy. Finally, its server-less persistence design integrates platforms such as Model and Daytona. This agent will automatically enter a dormant state when there is no task, and can be awakened instantly upon receiving new messages. This means that users can maintain a 24-hour personal assistant in the cloud at very low cost. It has completely gotten rid of the past limitation of having to keep the program open on the local computer. So where can Hermes-agent be used in practical applications? Its application scenarios are actually quite wide. Developers can deploy it on a cloud host as an all-weather programming partner. You can assign tasks to it through Telegram or Discord at any time, such as automatically running a script or helping to manage the context of the project. AI researchers can use its autonomous learning capabilities to perform long-term automated data collection and analysis work. Even if you are not a developer, for smart home enthusiasts, you can use its message channel to integrate Home Assistant and no matter where you are, you can use natural language to control various devices in your home through communication software. However, although the project provides a one-click installation script, which greatly reduces the difficulty of getting started, to truly use its full functions, you still need to have a certain degree of understanding of Docker API, drug management and other technologies. Therefore, its target users are still more inclined to developers and technology enthusiasts with technical backgrounds. The response from the Hermes-agent community is generally cautious and optimistic. The points of appreciation are mainly focused on its innovative long-term memory and self-learning mechanism. Many people believe that this is the future direction of personalized AI agents. Moreover, it adopts MIT authorization and has a model-independent design, which also makes developers who pay attention to data sovereignty feel at ease. However, there are many voices of complaints. Many people report that its setting threshold is high, especially when integrating multiple platforms and tools. The setting process is a bit cumbersome. In addition, the project is still in the early development stage, and long-term operation stability And whether the API will change frequently are the focus of the community. Although the future of Hermis Agent is promising, its strong autonomy actually also brings potential risks. The first is the unpredictability of behavior. Although an agent that can modify its own skills is very powerful, it may also produce unexpected wrong behavior after a certain optimization. And it may be very difficult to find out where the problem is. Secondly, there are serious security concerns when you give an agent permissions to execute native instructions and operate external APIs. This undoubtedly expands the attack surface. If you encounter a malicious prompt injection attack, it is very likely to bypass the existing security mechanism, leading to out-of-control cloud costs and even data outsourcing. This also means that before deploying Hermes-agent to the production environment, a more stringent full-line control and monitoring mechanism must be established. In summary, the greatest value of Hermes-agent does not lie in how fast it performs tasks, but in that it is the first open source AI agent that truly introduces the two concepts of growth and companionship. It uses closed learning loops and persistent memory. There are also autonomous skill creations that paint a picture of what a future personal AI assistant may look like. For all developers and researchers who care about how AI evolves from a mere tool to a long-term partner, Hermes-agent is definitely a milestone worthy of close attention. Projects The above is today's Gitcovery. I hope these GitHub Trending projects can bring inspiration to your development work. Please enter the information column below for the above GitHub Report. If you like this show, don't forget to subscribe to our channel. We will see you at the same time tomorrow.