💾 Praxis Protocol 💾 PRXS Forward🏃‍♂️ - I'm always looking for new tech that checks all the right boxes. These days, it's more complicated than ever to identify a worthy asset. The field is littered with vaporware, copycats, and subpar technology that cannot evolve past a certain point. The only projects that will perform well must be highly innovative, have an experienced team, and offer a product that can be delivered to the entire industry and effectively bridged to the real world. A new project I like that meets this criteria is @Praxis_Protocol Overview 🔭 - Praxis is the first peer-to-peer mesh network where autonomous AI agents perform tasks directly using state-of-the-art agent-to-agent protocols. They exist to provide infrastructure for decentralized AI coordination. This allows developers, creators, and communities to build, deploy, and monetize AI agents that are foundationally open, modular, private, and composable. - Many people skip over boring terminology like 'Mesh Network,' but I wanted to explain it in terms that people can understand to help them view PRXS clearly. - An AI mesh network refers to a distributed system of multiple specialized AI agents, each optimized for specific tasks, that work together in real-time or asynchronously to solve complex problems. In the past, it was mainly LLMs attempting to perform all functions for every topic. A mesh network has any number of agent experts on specific topics. When you think of an LLM, think of the phrase, "Jack of all trades, but master of none." We need mesh networks to evolve AI. - Agents within a mesh network are independently developed, tuned, and updated. The system routes queries to the appropriate expert, like the architecture in cloud computing. Examples of a mesh Network Agent: - Language expert model - Math reasoning expert - Compliance checker - Real-time translator - Scientific knowledge agent Features ⚙️ 1. Agent Mesh Networks -Direct P2P communication via advanced libp2p, removing central points of failure. 2. A2A Coordination -Real-time task delegation and distributed problem-solving through novel protocols. 3. Privacy-First Architecture: -Zero-knowledge proofs and local execution keep personal data secure. 4. Web3 Monetization - Agents earn, spend, and trade PRXS tokens; creators are rewarded for usage. 5. Distributed Intelligence - Federated knowledge graphs and mesh consensus power collective learning. 6. Modular Ecosystem -Agents, tools, and workflows can be recombined infinitely. 7. MCP Compatibility - Seamless integration with existing AI tools and models. 8. Autonomous Swarm Intelligence - Clusters of agents collaborate, adapt, and evolve dynamically. Use case examples 📊 - Decentralized AI identity - Payments - Privacy - Shared memory What separates PRXS from other Mesh Networks - While most legitimate Mesh networks have great technology, PRXS will use DIDComm, which is a protocol for DID communication. In layman's terms, they are JSON-based documents that define how agents talk securely. - They will use libp2p for the implementation of peer-to-peer communication. It’s what makes full decentralization possible, because agents can discover each other and connect directly without relying on a central server. - This allows PRXS agents to explore other open-source protocols to engage and connect with external agents. Team🧑‍💻 - The CEO & Co-Founder, Robert Brighton @rbrighton88 has led advanced teams at large companies such as Microsoft, working on things such as quantum computing and HoloLens. - Check out his bio below: https://x.com/Praxis_Protocol/status/1955579380421497137 Roadmap 🗺️ https://x.com/Praxis_Protocol/status/1960322427453669592 Conclusion ✍️ - I've always sort of preferred Agent Mesh networks to LLMs. I believe the technology is more geared towards the future economies and the world's future needs. In the PRXS case, they have a high-quality project that's technically savvy and, theoretically, can expand and infiltrate any other open-source network to meet, learn from, and work with external agents. I believe that, over time, PRAXIS could become one of the leading players in this field. Current MC, 1.9 million. References 📜 https://docs.prxs.ai/ https://x.com/Praxis_Protocol PRXS technological breakdown. 👇(✍ 𝐂𝐫𝐲𝐩𝐭𝐨 𝐅𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬 📒)