Nous Research Launches Hermes Agent - An Open Source Agent That Remembers Everything

Nous Research just shipped something that most AI agent frameworks have been promising but failing to deliver: an autonomous agent that actually gets better over time. Hermes Agent is an open-source (MIT License) CLI tool that lives on your server, builds persistent memory across sessions, auto-generates reusable skills when it solves hard problems, and reaches you through Telegram, WhatsApp, Slack, Discord, or your terminal.

How It Compares

The AI agent landscape has no shortage of options. Here is where Hermes Agent sits relative to the current field:

The Memory System

This is Hermes Agent's core differentiator. Most AI agents have some form of context persistence - conversation history, config files, project-level instructions. Hermes Agent goes further with a multi-level memory architecture:

1. Session memory - standard conversation context within a single interaction
2. Persistent memory - facts, preferences, and project details retained across sessions
3. Skill memory - when the agent solves a complex problem, it automatically writes a reusable skill document describing the approach. These skill documents are indexed, searchable, and shareable

You can query past sessions by keyword ("How did we fix that Docker networking issue?"), and the agent loads relevant skills automatically when similar tasks come up. It is basically building its own procedural knowledge base as you use it.

Skills Ecosystem

Hermes Agent ships with 40+ bundled skills covering MLOps, GitHub workflows, diagramming, note-taking, and more. The skills use the Agent Skills open format - portable SKILL.md files that any compatible agent framework can consume.

You can browse and install additional skills from agentskills.io, GitHub repos, ClawHub, LobeHub, and the Claude Code Marketplace. The format has already been adopted by Microsoft in VS Code and GitHub, as well as tools like Cursor, Goose, and Amp.

The skills are sandboxed with quarantine and audit systems - new skills don't get full access until reviewed.

Cross-Platform Gateway

The gateway mode is what makes Hermes Agent feel less like a developer tool and more like a personal assistant. Run hermes gateway and it launches as a systemd service, listening on all configured messaging platforms simultaneously. Start a conversation on Telegram during your commute, continue it in your terminal at work, pick it up on Discord at night. The context carries across.

Voice memo transcription works across all channels - send an audio message on WhatsApp and the agent processes it the same as text.

The Tool Arsenal

Hermes Agent comes loaded with over 40 built-in tools:

• Web: search, browser automation with clicking/typing/screenshots
• System: terminal execution, filesystem operations, code execution
• AI: vision analysis, image generation, text-to-speech, multi-model reasoning
• Planning: task planning, cron job scheduling, memory management
• Delegation: subagent spawning with independent conversations and terminals, RPC tool calls from Python scripts

The five sandboxing backends (local, Docker, SSH, Singularity, Modal) provide real flexibility for security-conscious deployments. Docker containers get read-only root filesystems, dropped Linux capabilities, PID limits, and namespace isolation.

Research and Training Features

Nous Research built this for more than just end users. The agent can create thousands of tool-calling trajectories in parallel with automatic checkpointing, export conversations in ShareGPT format for model fine-tuning, and integrate with Atropos for reinforcement learning on agent behaviors. This is a research tool wrapped in a user-friendly shell.

What It Does Not Tell You

The pitch is compelling, but several questions remain unanswered.

First, memory quality over time. Persistent memory that grows indefinitely will build up noise. The skill generation system writes documents automatically, but there is no indication of how it handles contradictory skills, outdated procedures, or memory pruning at scale. After six months of heavy use, does the memory remain useful or become a liability?

Second, model flexibility comes with tradeoffs. Hermes Agent works with Nous Portal, OpenRouter, or custom endpoints - but tool-calling reliability varies wildly across models. An agent with 40+ tools is only as good as the model's ability to select and invoke them correctly. The documentation doesn't specify which models have been tested beyond Nous's own Hermes models.

Third, security in gateway mode. Running an autonomous agent as a persistent systemd service that accepts commands from five messaging platforms is a significant attack surface. The sandbox options are strong, but the messaging gateway itself needs to be locked down carefully. A compromised Telegram account becomes a root shell if the agent has elevated permissions.

Finally, community size matters. The skills ecosystem is promising but young. With 44 GitHub stars at launch, Hermes Agent needs critical mass to make its community skill sharing truly useful. The Agent Skills format has broader adoption, which helps, but the Hermes-specific skill library is thin for now.

Hermes Agent is the most ambitious open-source agent launch of 2026 so far. The persistent memory, auto-skill generation, and cross-platform gateway are features that the commercial AI agent frameworks have been talking about but not shipping. Whether Nous Research can build the community and ecosystem to make those features sing at scale is the open question. But for developers who want an agent that learns and grows without vendor lock-in, this is the first serious option.

Sources:

• Hermes Agent - Nous Research
• Agent Skills Specification - agentskills.io
• Agent Skills GitHub - GitHub
• NousResearch GitHub - GitHub