Nous Research Releases ‘Hermes Agent’ to Fix AI Forgetfulness with Multi-Level Memory and Dedicated Support for Remote Terminal Access

In the current state of AI, we have become accustomed to the ‘ephemeral agent’—a smart but forgetful assistant that restarts its cognitive clock with every new conversation. While LLMs may be major coders, they are not coders persistent condition required to work as true teammates.

Nous Research the team is released Agent of Hermesan independent open source system designed to solve two major problems in agent workflows: memory corruption and environmental fragmentation.

It is built on top management Hermes-3 model family, Hermes Agent is billed as an assistant who ‘grows with you.’

The Memory Hierarchy: Learning about Skilled Texts

For an agent to ‘grow,’ it needs more than just a large content window. Hermes Agent uses ia multi-level memory system which simulates process learning. While it handles short-term operations using a standard index, its long-term use is driven by Skills Documents.

When a Hermes Agent completes a complex task—such as debugging a specific microservice or optimizing a data pipeline—it can compile that experience into a permanent record. These records are stored as subsequent check mark files agentkills.io open standard.

• Process Memory: The next time you ask the agent to do the same job, you don’t start from scratch. It queries its library of Skill scripts to ‘remember’ successful actions it has taken in the past.
• Content Persistence: Unlike traditional RAG (Retrieval-Augmented Generation), which often pulls in different snippets, this system allows an agent to maintain an integrated understanding of your specific codebase and preferences over weeks or months.

Persistent Machine Access: Beyond the Sandbox

A major point of contention for AI devs is the ‘implementation gap.’ Most agents write code but cannot interact with the real world without heavy manual intervention. Hermes Agent fills this gap by providing continuous dedicated machine access.

The agent is designed to live within an active environment, supporting five different backends:

1. Location: Direct interaction with the host machine.
2. Docker: Isolated, reproducible containers for safe code generation.
3. SSH: Ability to log into remote servers or cloud environments.
4. Singularity: Support for high-performance computing (HPC) containers.
5. Model: Serverless implementation of heavy workload scaling.

This persistence is important for AI devs. You can run a long-running EDA (Exploratory Data Analysis) on a remote server via SSH, log out, and come back later. The agent maintains terminal state, manages background processes, and tracks file system changes independently. It’s not just about simulating a conversation; manages the workplace.

Gateway: An Agent In Your Pocket

While most technical agents are confined to a CLI or proprietary web dashboard, Nous Research has prioritized accessibility through Hermes Gateway.

The system integrates directly with existing communication stacks, including Telegram, Discord, Slack, and WhatsApp. This allows for a continuous feedback loop: a developer can start a task at his workstation and receive a ‘task completed’ notification via Telegram. Through the gateway, you can send follow-up instructions or even voice memos that the agent processes and implements within its ongoing environment.

Under the Hood: React Loop and Durability

For AI devs in this regard, the architecture is a refined implementation of React Loop (Consultation and Execution).. The agent follows a programmed cycle:

• Viewing: Reading terminal output or file contents.
• Consultation: Analyzing the current situation against the goal.
• Action: To execute a command or call a tool.

This is powered by Hermes-3 (based on Llama 3.1)which was trained using a special learning framework called Atropos. This training specifically targets instrument piloting accuracy and long-range planning, ensuring that the agent does not get ‘lost’ during multi-step deployments.

Key Takeaways

• Persistent Machine Access: Unlike stateless chatbots, it works on real endpoints (Docker, SSH, Local, etc.), which allows it to run long-term operations and preserve the state of the file across sessions.
• Automatic ‘Skills Documents’: It uses a multi-level memory system to record efficient workflows as searchable markup files (with agentkills.io), which means it gets smarter the more you use it.
• Precision ‘Hermes-3’ Thinking: Powered by Llama 3.1-based Hermes-3 model, well configured Atropos RL advanced guidance and reliable tool calling within complex logic loops.
• The Ubiquitous Gateway: You can contact your agent via Telegram, Discord, or Slackallowing you to manage heavy engineering tasks or receive status updates from your phone.

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