This AI Learns Your Brain.

Frustration mounts quickly when interacting with today's ubiquitous AI chatbots. Each new session feels like a blank slate, forcing users to re-explain context, re-upload files, and re-establish preferences that were clear just moments before. This fundamental 'amnesia problem' transforms potentially powerful assistants into tedious, stateless tools, hindering any genuine long-term collaboration.

Nous Research, an American company, now presents Hermes, an open-source AI agent poised to definitively solve this pervasive issue. Positioned as The Self-Improving Agent That Gets Smarter Every Day-Improving Agent That Gets Smarter Every Day, Hermes fundamentally redefines human-AI interaction by discarding the session-based limitations of its predecessors. It moves beyond simple task execution, aiming to become a true digital partner.

Hermes achieves this through robust persistent memory. Unlike mainstream AI assistants that discard conversation history, Hermes remembers every interaction. It stores memory in external files, like a `memory.md` file, or integrates with external processors such as Supermemory, Mem0, or OpenViking for enhanced recall. While sessions are preloaded with a compacted version (roughly 3,500 characters or 700 tokens), all past dialogues reside in an SQLite database, leveraging FTS5 for efficient full-text search, allowing it to retrieve forgotten details from days or weeks prior.

This memory fuels a continuous learning loop. Hermes reflects, learns, and evolves autonomously, extracting reusable patterns and building a running model of user preferences, decision history, and task patterns that persists across sessions. It even creates its own skills automatically from experience, a capability most agents lack out of the box, refining them with every subsequent use.

The agent actively manages its context, compressing sessions above 50% of the context window by removing old tool call outputs while retaining crucial head and tail information. Hermes also nudges itself every 10 turns to save important information to memory and write new skills when necessary. This radically different approach transforms AI from a fleeting utility into a long-term, self-improving agent that truly understands and adapts to its user over time.

Emerging from the open-source AI lab Nous Research, Hermes represents a significant leap in artificial intelligence agents. Billed as "The Self-Improving Agent That Gets Smarter Every Day-Improving Agent That Gets Smarter Every Day," Hermes redefines the relationship between user and AI, moving beyond a simple command-response mechanism. It acts as a digital apprentice, meticulously learning and growing with its user by observing patterns, feedback, and preferences across every interaction. This agent isn't merely responding; it's actively building a persistent model of the user, their decision history, and task patterns that evolves across sessions.

The name Hermes, drawn from the Greek messenger god, aptly describes its role as a swift, intelligent conduit for information and action. Unlike conventional chatbots plagued by session amnesia, Hermes boasts persistent memory, remembering every past conversation. It stores this context in external files—like `memory.md`, Supermemory, Mem0, or OpenViking—and indexes all sessions in an SQLite database using FTS5 for full-text search. Crucially, Hermes autonomously creates and refines reusable skills from successful task completions, nudging itself every ~10 turns to save important information or write a new skill. This makes it uniquely adaptive: the more you use Hermes, the more proficient and tailored it becomes to your specific workflows.

Hermes’s open-source foundation empowers a vibrant community, fostering transparency and collaborative development via its GitHub repository. This approach allows users remarkable flexibility in deployment, whether locally, on a $5 VPS, in Docker, over SSH, or via serverless backends like Modal and Daytona. Users can connect Hermes to various AI models, including: - Over 200 options through OpenRouter (like Gemma 4) - Specific endpoints such as Nous Portal, z.ai/GLM, Kimi/Moonshot, MiniMax, and OpenAI Furthermore, Hermes integrates with platforms like Telegram, Discord, Slack, WhatsApp, Signal, Email, and CLI, offering interaction across diverse devices. It arrives with over 40 built-in tools, encompassing web search, browser automation, vision, and scheduled automations, all while operating with zero telemetry and in sandboxed environments for enhanced privacy and security.

Hermes employs a sophisticated hybrid memory system to overcome the pervasive AI amnesia problem. It preloads key facts and current session data from a compacted `memory.md` file, limited to approximately 3,500 characters or roughly 700 tokens. This pre-fetching ensures immediate access to crucial context for any new interaction.

Beyond this initial preload, all past sessions are meticulously stored within an SQLite database, leveraging FTS5 for robust, full-text search capabilities. This powerful backend allows Hermes to search and retrieve any previous dialogue, action, or learned insight, providing comprehensive historical context that persists across individual sessions. Hermes can precisely pinpoint and retrieve information from weeks ago.

To manage token usage and maintain efficiency with long conversations, Hermes implements intelligent context compression. Unlike other agents, Hermes begins compression at 50% of the context window. It strategically removes output from old tool calls and compresses middle sections of the dialogue while meticulously preserving the crucial head and tail. This ensures core conversational flow and recent context remain intact, saving valuable tokens.

This self-improving agent also features a proactive 'self-nudging' mechanism. Approximately every 10 turns, the AI agent internally prompts itself to perform two critical actions: save important gleaned information to long-term memory or suggest creating a new, reusable skill based on recurring tasks or successful completions. This continuous internal reflection allows Hermes to autonomously identify patterns and codify them into actionable capabilities.

All these intricate learning and memory management processes unfold seamlessly in the background, making Hermes's evolution appear effortless and organic to the user. This constant, unprompted self-improvement builds a persistent model of user preferences, decision history, and task patterns, ensuring the agent genuinely gets smarter and more aligned with its user with every interaction. For a deeper dive into its innovative architecture, explore Hermes Agent — An Agent That Grows With You | Nous Research.

The Better Stack video, "Hermes: The Self-Improving Agent That Gets Smarter Every Day-Improving Agent That Gets Smarter Every Day," opens with a practical demonstration: generating promotional tweets from YouTube video scripts. The user aimed to test if Hermes could truly remember their specific writing style and incorporate iterative feedback without constant re-instruction.

User initiated a new chat, instructing Hermes to analyze scripts stored in an `@scripts` folder to understand their voice. Hermes quickly processed the text, identifying the user's style as "pragmatic and skeptical," "developer-centric," and "transparent and relatable." It then proposed a tweet strategy for a target audience of mid-senior level developers, initially aiming for tweets under 210 characters.

The iterative feedback loop quickly began. The user altered the desired tweet length mid-session, extending it to 400 characters, and even switched the underlying model to GLM 5 Turbo for faster responses. When Hermes generated a tweet using the word "incredible" and a phrase like "breaking a sweat," the user provided explicit negative feedback: "don't use the word incredible," preferring "really good" instead.

Hermes immediately incorporated this nuanced feedback, producing a tweet that perfectly matched the user's specific linguistic preferences. Crucially, the agent saved these stylistic adjustments directly to its memory. It then proactively generated a reusable skill for tweet creation, streamlining future content generation and showcasing its ability to automate tasks based on learned experience.

The true test came with a brand new Hermes session. Without any files re-uploaded or preferences re-stated, the agent flawlessly recalled the user's preferred tweet style. It remembered specific word choices, tone, and even the type of emojis the user liked, demonstrating the power of its persistent memory system powered by the compacted `memory.md` file and the SQLite database with FTS5.

This persistent, cross-session learning radically transforms repetitive creative workflows. Hermes eliminates the need for users to repeatedly articulate their specific stylistic requirements, freeing up valuable time. The agent genuinely functions as a self-improving digital apprentice, getting smarter and more efficient with every interaction.

Hermes transcends simple factual recall. It observes workflows, abstracts them, and automates entire processes, fundamentally changing how users interact with AI. This capability transforms it into a true digital apprentice, not merely a conversational interface.

Following the iterative process of generating tweets from YouTube scripts—refining tone, length (from 210 to 400 characters), and specific phrasing ("really good" instead of "incredible")—the user prompts Hermes. This explicit instruction, "create a skill so it's easier for me to write tweets in the future," activates its unique ability.

Hermes then leverages its skill manager skill to encapsulate that entire workflow. It analyzes the conversation history, identifying the steps, preferences, and feedback provided, then compiles these into a single, executable command. This move is crucial for long-term efficiency.

This transformation proves dramatic. What once required a multi-turn dialogue—defining style, audience, length, and making several linguistic tweaks—now collapses into a single, concise command. Executing this new skill instantly produces polished tweet options, even generating full threads, tailored precisely to the user's learned preferences.

This autonomous skill creation stands as Hermes's most compelling superpower. It actively learns from every interaction, building a personalized toolkit that evolves with the user. This differentiates Nous Research's agent, allowing it to progressively automate complex, bespoke tasks without requiring manual coding or constant re-prompting.

Users acquire a custom-built suite of commands, each reflecting their specific needs and workflows. Hermes becomes an increasingly intelligent, self-optimizing partner, radically streamlining repetitive tasks and freeing up cognitive load. This persistent, adaptive intelligence makes it a formidable tool for any content creator.

The burgeoning AI agent landscape presents a stark choice: depth versus breadth. On one side stands Hermes, The Self-Improving Agent That Gets Smarter Every Day-improving agent from Nous Research, engineered for profound personalization and long-term, cumulative intelligence. Its design prioritizes a single agent's evolving capabilities, making it a digital apprentice that genuinely gets smarter with every interaction.

Hermes excels at building a persistent model of its user, remembering past conversations, preferences, and even autonomously generating new skills based on observed workflows. This focus cultivates a highly tailored experience, allowing the agent to anticipate needs and refine processes over extended periods. Users benefit from an AI that learns their unique style and automates complex, multi-step tasks with increasing efficiency.

Conversely, OpenClaw champions a strategy of expansive integration and orchestration. It provides a robust framework for managing diverse agents across numerous channels and tools, making it ideal for large-scale deployments requiring broad operational reach. OpenClaw prioritizes the ability to coordinate teams of agents, connect to a vast array of external services, and handle complex multi-channel communication workflows.

Where Hermes aims to become an indispensable, deeply knowledgeable personal assistant, OpenClaw serves as a powerful command center for distributed AI operations. OpenClaw’s strength lies in its ability to integrate with virtually any API or platform, enabling comprehensive tool utilization and multi-agent collaboration. Hermes, meanwhile, dedicates its resources to refining its internal model and skill set, creating a unique, continuously improving intelligence for individual users.

This philosophical divergence underscores why many users are now evaluating their needs. Recognizing Hermes's distinct value proposition, OpenClaw even offers an official migration wizard, simplifying the transition for those seeking a more personalized, self-improving AI companion. For a deeper dive into the innovative work behind Hermes and other open-source AI initiatives, explore NOUS RESEARCH - Open Source AI.

Hermes prioritizes user privacy and data sovereignty. It operates with zero telemetry by default, ensuring your interactions remain private. Users self-host the agent on their own infrastructure, whether a local machine, a Virtual Private Server (VPS), or a Docker container, granting complete control over sensitive data.

This open-source agent radically expands model choice, sidestepping vendor lock-in. Hermes connects seamlessly to various AI models, including: - OpenRouter, offering access to over 200 different models. - OpenAI's robust APIs. - Local endpoints for on-device inference. Users retain the flexibility to switch models mid-session, optimizing for cost or performance as needed.

Accessibility defines Hermes's deployment philosophy. It runs effectively on a cheap $5 VPS, democratizing powerful AI for a wider audience. This low barrier to entry allows individuals and small teams to leverage advanced agent capabilities without significant infrastructure investment.

Interacting with Hermes is intuitive and versatile. A robust Command Line Interface (CLI) with a Text-User Interface (TUI) provides a powerful control panel. Beyond the terminal, Hermes integrates with popular messaging platforms, extending its reach to: - Discord - Slack - Telegram This multi-platform support ensures users can manage their digital apprentice from virtually anywhere.

Hermes, The Self-Improving Agent That Gets Smarter Every Day-improving agent from Nous Research, has ignited a fervent community, evidenced by its explosive growth since launch. The project now commands over 64,000 GitHub stars, a staggering figure that underscores its immediate impact and widespread developer interest. This rapid adoption speaks volumes about the perceived value of a truly persistent, self-learning AI agent.

Nous Research maintains a blistering development pace, consistently rolling out significant enhancements. The recent v0.9.0 update introduced critical features, including a local web dashboard for intuitive agent management and a 'Fast Mode' that optimizes performance for certain tasks. These additions dramatically improve user experience and demonstrate a commitment to continuous iteration.

Beyond core development, Hermes thrives on a passionate open-source community actively extending its capabilities. Enthusiastic contributors have already delivered vital tools like a native Windows desktop application, significantly broadening accessibility for users outside the command-line interface. Such organic contributions are a hallmark of robust, user-driven projects.

This burgeoning ecosystem fundamentally elevates Hermes beyond a mere CLI agent. The web dashboard simplifies interaction for non-technical users, while community-developed tools like the native Windows desktop app eliminate barriers to entry, making the agent more accessible to a wider audience. These contributions don't just add features; they cultivate a robust, multi-faceted platform that leverages collective intelligence.

The expanding suite of interfaces and integrations enhances Hermes's utility, transforming it into a more versatile and broadly applicable tool. Users can now choose their preferred interaction method, from deep CLI customization to a graphical interface, fostering greater adoption across various professional and personal contexts. This collaborative growth ensures Hermes remains at the forefront of persistent AI development.

Nous Research's Hermes represents a radical shift in AI agent design, but is it ready to completely take over your digital life? While its recent launch and rapid 64,000+ GitHub stars signal immense potential, a balanced view acknowledges both its unparalleled strengths and its relative youth. Hermes excels in memory retention and autonomous skill creation, setting a new bar for personalized, self-improving agents.

Its hybrid memory system, combining a compacted `memory.md` for preloading and an SQLite database with FTS5 for deep session search, ensures it truly never forgets. This foundational capability allows Hermes to learn your specific workflows and preferences, automating repetitive tasks with a level of personalization previously unseen. It becomes a genuine digital apprentice, growing smarter with every interaction.

However, Hermes operates in a landscape populated by more mature platforms like OpenClaw. The ongoing "Depth vs. Breadth" debate highlights OpenClaw's broader channel support and sandboxing capabilities, contrasting with Hermes's focused depth in learning and self-improvement. Users considering a full transition should weigh this difference against their specific integration needs.

Despite its nascent stage, the project's real-world viability is already being validated. Better Stack's video creator, who demonstrated Hermes generating tweets from video scripts, committed to using it as their main personal assistant. This practical adoption underscores Hermes's immediate utility and the tangible benefits of its persistent memory and skill-building for daily tasks.

Hermes offers a compelling vision for a truly personal AI, one that adapts and evolves with you. Its zero-telemetry, self-hostable architecture further bolsters its appeal for privacy-conscious users. While it may require some initial setup, its long-term promise of an AI that genuinely learns and automates for *you* is undeniable. For more technical details and setup guides, consult the Hermes Agent Documentation.

Hermes signals a profound shift for AI assistants. No longer passive tools requiring constant supervision, these agents transform into proactive, self-improving partners. They learn from every interaction, build persistent memory, and autonomously craft skills, evolving alongside their users.

This radical evolution is deeply intertwined with advancements in underlying language models. Nous Research, the creators of Hermes, also develops powerful LLMs such as Hermes 4.3, boasting an unprecedented 512K context window. Such massive context allows the agent to process vast amounts of information, enabling deeper learning and more sophisticated reasoning across extended sessions.

Imagine a future where your digital assistant doesn't just complete tasks, but fundamentally alters your workflow. Developers could offload repetitive coding patterns, allowing the agent to automatically generate and refine boilerplate code or even suggest optimized algorithms based on learned project history.

Writers will find an AI that internalizes their unique voice, generating drafts, tweet threads, or long-form content perfectly aligned with their established style and audience. Researchers might leverage Hermes to autonomously synthesize complex datasets, identify emerging patterns, or even draft initial literature reviews, accelerating discovery.

This paradigm shift moves beyond simple automation; it promises a truly symbiotic relationship between human and machine. The agent becomes an extension of your own cognitive processes, continuously adapting to your preferences, methods, and goals, without requiring constant retraining or explicit programming.

Hermes, with its open-source foundation and commitment to user control, offers more than just a powerful tool. It provides an early, tangible glimpse into the future of personalized AI, where your digital apprentice grows smarter every day, becoming an indispensable, lifelong intellectual companion.

What is Hermes Agent?

Hermes is an open-source, self-improving AI agent developed by Nous Research. It's designed to learn from user interactions, remember past conversations across sessions, and autonomously create reusable skills to improve its performance over time.

How is Hermes different from other AI agents like OpenClaw?

Hermes focuses on 'depth'—deeply personalizing a single agent through long-term memory and self-improvement. OpenClaw focuses on 'breadth'—orchestrating multiple agents across many channels with broad tool integration. Hermes learns your workflows; OpenClaw executes your commands.

Does Hermes work with models like GPT-4 or Claude?

Yes, Hermes is model-agnostic. It can connect to hundreds of models via services like OpenRouter, Nous Portal, and z.ai/GLM, as well as directly to APIs from OpenAI, Kimi, and others. You can also connect it to models running locally.

How does Hermes's memory actually work?

It uses a hybrid system. Key information is stored in a simple text file (`memory.md`) for quick loading. Full conversation history is stored in an SQLite database, allowing for efficient full-text searching of past sessions without consuming massive amounts of context tokens.