Original author: BUBBLE
Reprinted by: Luke, Mars Finance
With the advent of Terminal of Truths, the on-chain AI Agent era has begun. The current Crypto market is filled with various Agentic concepts across different fields, whether it's MeMe, tool applications, launch platforms, model frameworks, hive clusters, etc. Almost every day, new conceptual projects emerge, making it hard to keep up. On December 11, a mysterious smiley face playing with the Matrix 'we take the red pill then the blue pill' meme caused a market explosion after discussing topics related to AI philosophy and finally announcing the project's token address. What is it, and how did it support a market cap of 300 million? This article will unveil the magic behind arc.
Strong team background and technical strength
The team behind arc, Playgrounds, boasts a strong technical background and cross-industry experience. Founder Tachi '@0thTachi' was involved in nuclear physics and aerospace engineering research at the Southwest Research Institute in the United States before entering blockchain. This institute is the oldest and largest independent non-profit applied technology research organization in the U.S. After founding Playground, he transitioned to blockchain development.
Another co-founder and product lead, Terry, is also a member of the network technology advisory committee of the well-known blockchain data service provider Graph. Stopher '@chairman_stoph' has substantial software engineering experience, joining Tachi's team after graduating during the pandemic and entering the cryptocurrency field. Mateo '@belangermatteo' obtained his master’s degree from the École Polytechnique Fédérale de Lausanne and worked as a data analyst at Ledger before joining Playgrounds as a core technologist. Full-stack engineer Mochan '@0xMochan' and other engineers possess significant technical experience.
Before arc, the Playgrounds team successfully delivered some complex blockchain infrastructure experiences. For example, they built the first Ordinals and inscription subflow API and a Python library called Subgrounds for analyzing blockchain data indexed on the Graph network.
Breakthrough AI Agent Framework - Rig
The Agent framework Rig behind arc was originally a project developed internally at Playgrounds, aimed at providing reusable infrastructure for AI and cryptocurrency projects that need to query on-chain data, particularly focusing on chat interfaces. As development progressed, the team realized that Rig had broader application potential, leading to the decision to open source it to promote wider community participation and innovation.
Rig aims to go beyond traditional chatbots and explore more possibilities of LLMs. For example, structured data extraction, synthetic data generation, and injecting intelligence into existing data pipelines. The Playgrounds team examined existing market frameworks (such as LangChain, Llama Index, etc.) before development and predicted future trends in LLM and AI. At that time, there was a lack of similar frameworks based on Rust in the Agent framework field, while Rust's high performance and security make the architecture more efficient. With team members also possessing extensive Rust expertise, they ultimately chose Rust as Rig's primary development language.
Looking back at several leading Agent architectures in the current Crypto market, Eliza used TypeScript, Zerepy used Python, while Rig chose to develop an innovative framework based on Rust, standing out not just in Crypto but also among all open-source Agent architectures where Rust is used as the development language, with notable examples being Sobel.io's llm-chain and Rig developed by Playgrounds.
Tachi responds in the Discord community about Rig's advantages over other agent architectures.
The advantages of developing Rig with Rust are not found in some other architectures. First, security; Rust's type system can prevent bugs at compile time rather than waiting until runtime like TypeScript or Python, reducing the risk of runtime errors. Rust's memory management mechanism (like RAII) ensures there are no memory leaks and avoids data races.
From a performance efficiency perspective, Rig utilizes Rust's zero-cost abstractions combined with efficient pipelines to significantly improve execution efficiency and reduce costs. Using the tokio runtime, Rig can efficiently handle parallel processing, enhancing overall agent performance. It allows developers to add new functional modules through Tratis, maintaining the framework's flexibility and scalability, and can operate across multiple platforms. Modularity and concurrency ensure flexibility and scalability, while dynamic tasks and event-driven designs make Agent behavior smarter and more efficient.
Compared to most current LLM architectures on Crypto, it offers higher performance, scalability, manageability, and security. It can optimize Rag architectures like Eliza downward in the industrial chain while supporting the current hot multi-AI Agent integration Swarm concept upward. This makes Rig's architecture well-suited for expanding reliable, high-performance AI/ML pathways, designed specifically for institutional-level project deployment.
This makes Rig an ideal tool for developing high-performance AI Agents, excelling in games, robotics, automated workflows, or real-time simulations. The architecture allows for seamless scaling from local development environments to enterprise-level systems, laying the groundwork for institutional adoption. When a project provides high-quality products for enterprise-level clients rather than just for ordinary user entertainment, these enterprise-level AI Agents can even replace entire industrial chains in some cases, a fact already validated in the Web2 AI Agent market. Currently, Rig has over 100 forks and 1400 stars on GitHub, and this data is accelerating its growth.
What exactly is the mysterious smiley face arc?
As new conceptual projects emerge almost every day and technology iterates rapidly, the market is also filled with numerous scams, which is often criticized in the blockchain space. Regardless of how sectors rotate, there will always be fraudulent projects that undermine the market's trust in certain concepts, seemingly a repeated manifestation of Gresham's Law. In contrast, arc's approach is quite the opposite. Recently, the prologue displayed on the official website has finally revealed its first layer, with the team calling it handshake. The promotional video starts with a robot and a human version of 'Creating Adam,' where two hands slowly approach as if about to shake hands, symbolizing the arrival of the era of collaboration between humans and AI Agents, which is quite intriguing.
Most Agent platforms aim to shorten the process of creating, issuing, and fundraising for AI Agents, often using a bonding curve model similar to pump.fun. The goal is to facilitate the issuance of AI Agents, thus leading to more AI Agent projects. This is indeed a win-win for the platform and its users. However, for the market, it may not be the case. Amidst rapid updates and the MeMe era, the assembly-line style of projects seems also applicable to this AI wave. This influence leads developers to be demanded for faster update speeds, shorter development cycles, while the depth of development and the market's understanding differ. Aside from the already recognized leading projects, it is hard for products on the market to settle down and make actual innovations.
Handshake's distribution logic differs from almost all Agent platforms in the market. Tachi stated that they maintain very high development standards and have implemented one of the strictest code review processes in the crypto field to ensure the quality of the ecosystem. arc requires participants to first deposit $500 arc into a designated address to validate and reduce spam, but this is not a mandatory step.
Formal participants first need to submit a proposal 'clearly stating the project's goals, technical plans, team background, and the team's contributions to the $arc ecosystem.' Then the proposal needs to be reviewed 'by the team and core community members who will evaluate it from various dimensions.' Only after the proposal is approved can the project name appear on the registration list, equivalent to the team conducting the first part of due diligence before presenting the project to community members, followed by the phase where they gather funds or community donations to form arc or Sol trading pairs.
This project submission model resembles Grant or hackathon styles, similar to IDO formats, which may be a failed business model for other projects. The barrier for middle participants is too high, yet the review efficiency is too low, leading to a significant reduction in potential returns (fees).
While it is not ruled out that a release model similar to Pump.fun's AI Agent may be issued later, there is indeed some rationale behind arc's approach. From a technical perspective, the high barrier of entry for Rust development means there are fewer developers compared to Python or TypeScript, leading to longer development cycles. For Rig's developers to compete with others on development efficiency yields negative returns, and over time, the product quality will gradually decline.
From a commercial perspective and the team's overall vision, they aim to develop products that can truly achieve efficient performance for enterprise-level AI Agents, not just chatbots. Their ultimate vision is to integrate the thinking patterns and reasoning methods of all AI Agents through Agent Pipelines, ultimately forming Agents that have a deeper understanding of the existence of things, leading to more profound AI thoughts. This requires higher quality Data Feed and more mature reasoning capabilities, emphasizing quality over quantity.
It is worth mentioning that on the handshake page, arc indicated it will collaborate with the ecosystems of Solana and Arbitrum for review. Previously, the market had been discussing how difficult it is not to associate the best Rust-based Layer1 with the best Rust-based AI framework. Now it seems to provide an answer.
Like many Crypto AI projects, arc is at the intersection of two transformative technologies: artificial intelligence and blockchain. We are accelerating into a new paradigm where humans and agents will interact on-chain and off-chain.
arc is a thriving developer ecosystem that promotes AI-based innovation. Its core philosophy revolves around the arc complex, a collaborative network composed of developers, projects, and informational resources.
arc is also a bridge, connecting the excellent talents in blockchain and artificial intelligence to build the necessary infrastructure for the future Crypto+AI Agents.
arc is also a platform for issuing AI Agents, building trading pairs based on $arc for AI Agents, Agent systems, or improving the Rig architecture itself.
arc takes the red pill to understand the shortcomings of the reality Agent architecture and the chaos of the market, recognizing that such changes cannot be achieved overnight. With the team's technical strength, the power of community developers, and the support of those who recognize his vision, they can eventually take the blue pill. It is not just a project; it resembles a practitioner constructing a blueprint for the future.
