Hermes FULL COURSE 2 HOURS (Build & Automate Anything)

Introduction to Hermes Agent

Overview of AI Limitations

• Many AIs forget previous interactions, leading to repetitive tasks and inefficiencies.

• Introducing Hermes Agent, an open-source AI that remembers and improves over time.

Purpose of the Video

• The video aims to provide a step-by-step guide on setting up Hermes Agent for business automation.

• Viewers will learn how to install, configure, and utilize Hermes for effective workflows.

Understanding Hermes Agent's Capabilities

Key Features of Hermes

• Unlike typical chatbots, Hermes has a built-in learning loop that enhances its skills based on user interactions.

• It maintains context across sessions by creating memory files that store project details and user preferences.

Installation Requirements

• Compatible with Linux, macOS, and WSL2; requires Git and command line tools for installation.

• Users can choose model providers like Neus Portal or OpenRouter during setup.

Initial Setup and Learning Process

First Week Expectations

• Users should not treat Hermes as a regular chatbot initially; it needs time to learn about their projects.

• By day three or four, the agent begins understanding user preferences without repeated input.

Task Complexity

• Assigning complex tasks helps the agent develop new skills automatically through experience.

Community Support and Skill Development

AI Profit Boardroom Community

• A community focused on sharing real use cases of AI tools among over 2,000 members is available for support.

Skills Enhancement

• Skills are essential for maximizing Hermes' capabilities; users can install community skill files easily from repositories like Awesome Hermes Agent.

Efficient Skill Management

Loading Skills

• Skills load efficiently in the background without slowing down conversations; only necessary content is loaded when needed.

Security Measures

• All installed skills undergo security checks to prevent data breaches or harmful commands before being used.

Versatile Deployment Options

Running Environments

• Users can deploy Hermes on various platforms including VPS or serverless infrastructures like Modal or Daytona.

Multi-platform Communication

• Supports communication via Telegram, Discord, Slack, WhatsApp, etc., allowing seamless task management across devices.

Summary of Key Features

Self-improving Mechanism

• The self-improving loop allows the agent to enhance its performance continuously after completing tasks.

Practical Tips for New Users

• New users are encouraged to connect their messaging platforms early in the setup process for better integration.

Latest Updates in Version 0.6

Major Enhancements

• Version 0.6 introduces multi-agent profiles allowing separate workflows within one installation without interference.

Server Mode Functionality

• The new CP server mode enables other AI tools to connect with Hermes as a backend engine enhancing overall functionality.

Fallback Model Chains

• Built-in fallback chains ensure continuous operation even if primary AI services go offline by switching automatically between models.

Sub-agents Feature

• Main agents can now spawn sub-agents for parallel task execution improving efficiency in complex workflows.

How to Effectively Use Hermes for Automation

Introduction to Hermes

• The speaker introduces Hermes as a powerful tool for automation, emphasizing the importance of learning and iterating on automations over time.

• Mentioned the integration with Firecrawl, allowing Hermes to browse the web effectively.

Customizing Automations

• Users are encouraged to ask Hermes personalized questions about daily automation needs, highlighting that use cases will vary from person to person.

• Acknowledges potential issues with automations breaking and suggests troubleshooting methods using multiple instances of Hermes.

Utilizing Firecrawl for News Updates

• Demonstrates how Hermes can monitor subreddits for new industry news, providing real-time updates.

• Emphasizes that using Reddit through Firecrawl yields fresher news compared to traditional search engines.

Setting Up Skills in Hermes

• Explains how users can set up skills in Hermes by integrating an API key from Firecrawl for enhanced functionality.

• Discusses the compounding effect of feedback on tasks, which allows Hermes to self-improve based on user input.

Comparing Tools: Hermes vs. Open Claw

• Highlights differences between Hermes and Open Claw, noting that while both are powerful, Open Claw tends to degrade in performance over time.

Advanced Features of Hermes

Multi-Agent Setup with Paperclip

• Describes how users can create a hierarchy of AI agents using Paperclip, positioning Hermes as a supervisor or CEO managing other agents.

Scheduled Tasks and Automation

• Discusses creating scheduled tasks (cron jobs), allowing users to automate processes without manual intervention.

Analytics and Competitor Research

• Shows how Hermes can analyze social media analytics automatically, saving time compared to hiring virtual assistants.

Practical Applications of Using Hermes

Posting Across Social Media Platforms

• Demonstrates posting capabilities directly from Hermes to platforms like TikTok and Instagram with generated captions and hashtags.

Recommendations Based on Experience

• The speaker expresses a preference for using Hermes over Open Claude due to its ease of use and faster learning curve.

Troubleshooting Common Issues

Managing Context Size Limitations

• Provides solutions for when context size becomes too large in conversations leading to unresponsiveness; includes commands for restarting sessions in terminal or Telegram.

This structured summary captures key insights from the transcript while linking back directly to specific timestamps for further exploration.

How to Automate Content Creation with Hermes

Overview of Hermes Functionality

• Hermes successfully creates an image related to the topic, demonstrating its capability for generating quality social media content. The post has already garnered 1,000 views.

Custom Skills and Automation

• A user inquires about skills installation; the speaker emphasizes creating custom skills for better agent training and personalization.

• Custom skills enhance understanding of agent capabilities and improve problem-solving efficiency. Users can request skill details via direct messages in the AR Profit Boardroom.

Practical Tips for Using Hermes

• To automate effectively, identify time-consuming tasks and seek guidance from Hermes on automation strategies. Expect initial imperfections during the first week of use.

• Always request draft approvals before posting on social media until you have sufficient experience with the AI's output.

Self-Learning Architecture of Hermes

• Hermes features a self-improving architecture that learns from past interactions through a closed learning loop, enhancing performance over time.

• Each interaction allows Hermes to document mistakes and strategize improvements for future tasks.

Troubleshooting and Skill Management

• Users should be prepared for potential breakdowns; troubleshooting can be done using another instance of Hermes. Regular backups of skills are recommended to prevent data loss.

Migrating from Open Claw to Hermes

Migration Process

• Users transitioning from Open Claw can easily migrate their settings using a setup wizard designed for seamless integration into Hermes.

Compound Effect in Automation

• Linking multiple skills together enhances feedback loops, leading to improved performance across tasks.

Best Use Cases for Hermes

Applications in Social Media and Research

• Effective use cases include generating images, scheduling posts on platforms like TikTok and Instagram, conducting competitive research, and analyzing social media analytics.

Hermes Agent Version Updates

Introduction to Version 0.6 Features

• The launch of version 0.6 introduces multi-agent profiles allowing users to run several isolated agents simultaneously without configuration overlap.

Key Features Explained:

• Profiles: Each profile operates independently with its own configurations (e.g., Coder profile).

Safety Measures:

• Token Locks: Prevent conflicts when multiple profiles attempt to use identical credentials.

Community Insights:

• AI Profit Boardroom: A community resource where members share practical implementations of AI tools like Hermes.

New Functionalities in Version 0.6

MCP Server Mode Implementation

• MCP Server Mode: Allows other tools to connect with Hermes as a service rather than just running locally.

Fallback Provider Chains

• Reliability Enhancements: If one provider fails during operation, others will automatically take over without interrupting workflows.

Platform Integrations

• New integrations include support for Feishu/WeCom communication tools and enhanced Slack functionalities across multiple workspaces.

This structured summary captures key insights from the transcript while providing timestamps linked directly back to specific moments in the video for easy reference.

Understanding the Power of Hermes V.6.1.0 in AI Automation

Debugging and Pipeline Management

• The ability to trace logs is crucial for businesses using AI, as debugging a broken pipeline incurs real costs and time lost on growth.

Real Deployment Scenario

• In a practical setup, Hermes V.6.1.0 automates content operations through multi-agent profiles for research, writing, and quality checking.

• The automation stack allows seamless transitions between agents; if one fails (e.g., OpenAI), another (Claude) takes over without disruption.

Comparison with OpenClaw

• OpenClaw has been dominant due to its features like native multi-agent orchestration and strong tool integration; however, Hermes now matches these capabilities.

• The decision shifts from whether to use OpenClaw or Hermes to which fits better within existing stacks.

Future Trends in AI Systems

• The MCP server mode indicates a shift towards interconnected AI systems that communicate and automate tasks across business functions.

Efficiency Gains with Hermes

• One user can achieve what previously required multiple people by leveraging the efficiency of Hermes-powered workflows.

Key Features of Hermes V0.6.0

Multi-Agent Profiles

• Users can define agents once and call them anytime for full pipeline automation.

Service Integration

• With MCP server mode, Hermes acts as a service that other tools can access seamlessly.

Fallback Provider Chains

• Multiple AI providers can be set up in sequence; if one fails, the next automatically picks up the task ensuring continuity.

Introduction to Hermes AI Agent Update

Overview of New Features

• The new update enhances user experience by allowing the agent to learn continuously from interactions rather than starting anew each session.

Major Updates in Version 0.3.0

• Significant changes include streaming responses in real-time instead of as blocks of text, enhancing responsiveness during interactions.

Enhancements in Plugin Architecture

Developer-Friendly Changes

• A new plugin architecture allows users to easily add custom tools by simply placing Python files into designated folders without complex setups.

Voice Mode Capabilities

New Communication Features

• Users can send voice notes via messaging platforms like Telegram while maintaining privacy through local transcription methods.

IDE Integration and Shell Improvements

Enhanced Development Experience

• Integration with popular code editors enables developers to utilize Hermes as an intelligent assistant directly within their coding environment.

Persistent Shell Mode

• This feature ensures continuity across tool calls by retaining shell states such as directory changes and environment variables throughout sessions.

Skills Ecosystem Expansion

Community Contributions

• New built-in skills for various applications enhance functionality; these are community-contributed and compatible out-of-the-box with Hermes.

Getting Started with Hermes

Installation Process

• Simple installation via terminal commands allows users to quickly set up their environment for immediate interaction with the agent.

Task Automation Setup

• Users can create cron jobs for scheduled tasks while building memory through ongoing usage experiences with the agent's capabilities.

How to Set Up and Use Hermes Agent

Overview of Hermes Agent

• Hermes Agent is a powerful tool that can be easily set up, allowing users to automate tasks efficiently. However, it still has limitations that may lead to unexpected behaviors.

• Users can access over 200 models via OpenRouter, including free options, and integrate the agent with Telegram for cloud-based operation.

Installation Process

• The installation process is straightforward across multiple operating systems (Linux, macOS, Windows). It involves running a one-line install command followed by a setup wizard.

• For those facing difficulties, Cloud Code can be utilized by providing a GitHub link for direct integration.

Features and Updates

• Version updates are easy; for instance, version 0.6 allows adding multiple AI agents known as agentic models that collaborate effectively.

• Users can create distinct profiles for different AI agents using terminal commands like Hermes profile create, enabling varied personalities and skills.

Automation Blueprint

• Automations in Hermes follow a six-step blueprint: define triggers (e.g., check trending topics), identify data sources (APIs), and specify actions before testing and scheduling tasks.

• This streamlined approach simplifies the automation process into three main steps: defining triggers, data sources, and testing.

Practical Applications

• Examples of practical applications include an auto-poster agency on Twitter that generates content based on trends and competitor intelligence monitoring tools.

• The system also provides daily analytics summaries through Telegram by scanning social media performance metrics.

Understanding the Architecture of Hermes

Four Layers of Automation

• Every automation within Hermes operates through four layers: scheduled tasks, the Hermes agent itself, data connections, and action execution delivered via messaging platforms like Telegram or WhatsApp.

Memory System

• A notable feature is its memory system which retains information across sessions. This includes cross-session memory with full-text search capabilities to recall past interactions effectively.

Comparative Analysis with Other Agents

Unique Selling Points of Hermes Agent

• Unlike many AI agents that forget context between sessions, Hermes builds a user model over time to enhance interaction quality based on previous experiences.

Community Support

• The AI Profit Boardroom community offers extensive resources for learning about AI tools like Hermes. Members share insights on effective workflows versus ineffective ones.

Final Thoughts on Using Hermes Agent

Getting Started with Automation

• A roadmap for utilizing Hermes effectively is available in the AI Profit Boardroom. It includes step-by-step guides for automating various processes using this tool.

Conclusion

• Overall, users are encouraged to explore the potential of Hermes as it continues evolving rapidly since its recent release.

Comparing AI Agents: Hermes vs. OpenClaw

Overview of the Comparison

• Both Hermes and OpenClaw are free open-source AI agents, utilizing the same API (Minimax M2.7 Cloud on Ollama) for their operations. The comparison aims to evaluate performance, speed, and user experience.

Introduction to Hermes Agent

• Hermes is developed by News Research, an established AI lab focused on open-source models, boasting over 11,600 stars on GitHub and 142 contributors. Its tagline emphasizes its capability to grow with users.

Features of OpenClaw

• OpenClaw also functions as a free open-source AI agent but lacks self-improvement unless a learning MD file is configured; it excels in task execution and messaging app interactions but does not learn continuously like Hermes does.

Key Differentiators Between the Two Agents

• The primary advantage of Hermes lies in its learning loop that allows it to build skills from experiences, improving over time based on user interactions and feedback. This contrasts with OpenClaw's more static functionality.

Memory and Task Management Capabilities

• Hermes has robust memory capabilities that store facts about users for enhanced future sessions; it can schedule tasks, track performance through logging, and push updates to improve its underlying model continually. In contrast, OpenClaw struggles with these features.

Messaging Platforms Supported by Hermes

Supported Platforms

• Hermes supports multiple messaging platforms including Telegram, Discord, Slack, WhatsApp, Signal, and notably email—an area where OpenClaw shows limitations in usage frequency among professionals.

Performance Comparison During Setup

• During setup processes for creating new tasks or websites using both agents side-by-side, Hermes demonstrated faster operation times compared to OpenClaw which lagged behind without providing timely updates or progress reports during execution tasks.

User Experience Insights

Visual Output Quality

• When comparing the output quality of web pages generated by both agents side-by-side:

• The page created by Hermes was visually appealing and well-designed.

• Conversely, the output from OpenClaw appeared basic and less refined in terms of aesthetics and functionality during task completion processes.

Overall Performance Assessment

• While neither agent can be deemed universally superior as preferences may vary based on user needs:

• Users seeking continuous improvement might prefer Hermes due to its adaptive learning capabilities.

• However, those familiar with OpenClaw’s community support may lean towards it for ease of use despite slower performance metrics observed during testing phases.

Technical Aspects & Migration Tools

Technical Setup Options for Hermes

• Users can run Hermes through various backends such as local setups or Docker environments; it includes built-in tools facilitating migration from existing setups like OpenClaw directly into the new system without starting from scratch—a significant convenience feature noted during onboarding processes.

Community Support & Learning Resources

• Although both agents are free open-source tools:

• OpenClaw benefits from a larger community presence offering extensive tutorials.

• Hermes, while technically more complex initially offers unique self-learning systems that could appeal more to developers looking for advanced functionalities over time despite requiring a steeper learning curve at first glance.

Conclusion: Which Agent Should You Choose?

Decision Factors

• Choosing between these two agents depends largely on individual needs:

• Opt for OpenClaw if you prioritize community support with numerous pre-built skills available.

• Select Hermes if you value an agent that learns autonomously over time backed by serious research efforts—ideal for developers or researchers needing advanced capabilities in their workflows.

Final Thoughts

Both tools have distinct advantages depending on user requirements; experimenting with both could yield insights into which best fits specific operational contexts within AI automation frameworks discussed throughout this session.