The video showcases Hermes Agent, an open-source AI platform that autonomously generates, refines, and benchmarks code through a custom gravity well simulation game where AI models pilot ships, demonstrating iterative learning and competitive capabilities. It also details the installation process on a VPS, integration with advanced AI models, and highlights Hermes Agent’s potential to automate complex workflows while emphasizing safety and encouraging community engagement.
The video explores Hermes Agent, an open-source AI agent platform, demonstrating its installation, usage, and capabilities through a custom-built gravity well simulation game. In this game, AI models pilot ships around four suns, navigating gravitational forces, limited fuel, and momentum conservation to stay within a moving target circle. The entire simulation, including the website and ship control scripts, was created by large language models (LLMs) like Claude and Codex, showcasing how AI can autonomously generate complex code and iteratively improve performance over multiple runs. The presenter highlights how different AI models learn and improve their scores through repeated iterations, with some models achieving significantly higher scores than others.
The presenter details the process of benchmarking AI models by having them write and refine code to pilot ships in the simulation, iterating up to 20 times to optimize performance. The benchmark tests the AI’s ability to understand English instructions, generate specific code, and improve it through feedback. The simulation also includes a PvP mode where different AI models compete against each other, with results tracked via win rates and ELO scores. The presenter emphasizes the value of this benchmark as a personalized, transparent way to evaluate AI capabilities beyond standard industry benchmarks, which can sometimes be gamed by training on the test data.
Installation of Hermes Agent is demonstrated step-by-step, including setting it up on a VPS (Virtual Private Server) using Hostinger, which the presenter endorses for its reliability and user-friendly management. The installation involves choosing an Ubuntu LTS operating system, securing VPS access via SSH, and running Hermes Agent’s installer script. The video also covers configuring Hermes Agent with various AI model providers, including Open Router and News Portal, which aggregate multiple AI models and tools like web search and image generation under one API key. The presenter explains the benefits of running Hermes on a VPS for continuous availability and sandboxing options like Docker for safety.
The video further showcases Hermes Agent’s advanced features, such as integrating GPT-5.5 and GPT Image 2.0 models, and demonstrates how Hermes can orchestrate multiple AI sub-agents (e.g., Codex and Claude) to collaboratively generate and refine code. The presenter runs a live example where Hermes manages a duel between two AI models, iteratively improving their ship-piloting scripts and reporting results. This highlights Hermes Agent’s ability to automate complex workflows, manage persistent memory, and improve skills over time, making it a powerful tool for long-term AI-driven projects.
Finally, the presenter reflects on the broader implications of using AI agents like Hermes, emphasizing their potential to automate tedious tasks and accelerate development. They caution about safety considerations when running agents with elevated permissions and recommend isolating agents on separate machines or containers. The video concludes with encouragement for viewers to experiment with Hermes Agent themselves, noting the impressive progress of models like GPT-5.5 in handling extended, multi-step tasks. The presenter plans to open-source their benchmark code to benefit the community and invites feedback on the usefulness and impact of AI agents.