Terminal of Truths has ushered in an era of AI Agents on the blockchain. Nowadays, the Crypto market is filled with various Agentic concepts across different fields, whether it's MeMe, tool applications, launch platforms, model frameworks, or hive clusters. Almost every day, new conceptual projects emerge, making it overwhelming. On December 11, a mysterious smiley face playing with the "we take the red pill then the blue pill" meme from The Matrix sparked the market after a lengthy discussion on AI philosophy and immediately revealed the project's token address. What is it, and how did it support a market cap of up to 300 million? This article will unveil the magic behind arc.

Strong Team Background and Technical Strength

The team behind arc, Playgrounds, possesses a solid technical background and cross-industry experience. Founder Tachi "@0thTachi" was responsible for nuclear physics and aerospace engineering research at the Southwest Research Institute in the United States before entering the blockchain space. This institute is the oldest and largest independent nonprofit applied research and development organization in the U.S. After founding Playground, he transitioned to become a blockchain developer.

Another co-founder and product lead, Terry, is also a member of the technical advisory board for the well-known blockchain data service provider, Graph. Stopher "@chairman_stoph" has extensive software engineering experience and joined Tachi's team after graduating during the pandemic, entering the cryptocurrency field. Mateo "@belangermatteo" obtained a master's degree from the École Polytechnique Fédérale de Lausanne and worked as a data analyst at Ledger before joining Playgrounds as a core technical staff member. Full-stack engineer Mochan "@0xMochan" and other engineers also have substantial technical experience.

Before arc, the Playgrounds team had successfully delivered several complex blockchain infrastructure projects. For example, they built the first Ordinals and inscriptions sub-stream 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 initially an internally developed project by Playgrounds, aimed at providing reusable infrastructure for AI and cryptocurrency projects that require querying on-chain data, with a particular focus on chat interfaces. As development progressed, the team realized that Rig had broader application potential and decided to open-source it to encourage wider community participation and innovation.

Rig's goal is to go beyond traditional chatbot applications and explore more possibilities for LLMs. For instance, structured data extraction, synthetic data generation, and injecting intelligence into existing data pipelines. The Playgrounds team examined existing frameworks in the market, such as LangChain and Llama Index, and predicted future trends in LLM and AI development. At that time, there was a lack of Rust-based frameworks in the Agent framework space, and Rust's high performance and safety features made the architecture more efficient. Coupled with the team's rich expertise in Rust, they ultimately chose Rust as the primary development language for Rig.

Looking back at the leading Agent architectures in the current Crypto market, Eliza used TypeScript, Zerepy used Python, while Rig chose to stand out with a Rust-based innovative framework. Not only in Crypto, but even among all open-source Agent architectures, very few use Rust as the development language. The more well-known ones are Sobel.io's llm-chain and Playgrounds' Rig.

Tachi responded in the Discord community about the advantages of Rig compared to other agent architectures.

Using Rust for development gives Rig some advantages that other architectures lack. First is safety; Rust's type system can prevent bugs at compile time rather than requiring runtime checks like TypeScript or Python, reducing the risk of runtime errors. Rust's memory management mechanism (such as RAII) ensures no memory leaks and avoids data races.

In terms of performance efficiency, Rig leverages Rust's zero-cost abstractions and efficient pipelines to significantly improve running efficiency and reduce costs. With the Tokio runtime, Rig can efficiently handle parallel processing, enhancing the overall performance of the agent. It allows developers to add new functional modules through Traits, 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 LLM architectures in Crypto, Rig offers higher performance, scalability, manageability, and safety. Its position in the industry chain can optimize Rag architectures like Eliza below and support the currently popular multi-AI Agent integration Swarm concept above. This makes Rig's architecture well-suited for expanding reliable, high-performance AI/ML pathways, and Rig can be said to be designed for institutional-level project deployment.

This makes Rig an ideal tool for developing high-performance AI Agents, excelling in games, robotics, automated workflows, and real-time simulations. The architecture allows for seamless scaling from local development environments to enterprise-level systems, laying the foundational groundwork for institutional adoption. When a project provides high-quality products for enterprise-level clients rather than just entertainment for ordinary users, these enterprise-level AI Agents can, in some cases, even replace entire industry chains, as has been validated in the Web2 AI Agent market. Currently, Rig has over 100 forks and 1400 stars on GitHub, and this data is rapidly growing.

What Exactly is the Mysterious Smile Face arc?

With new conceptual projects emerging almost daily and rapid technological iterations, the market is also filled with numerous scams, which is often a point of criticism for blockchain. Regardless of how sectors rotate, there will always be fraudulent projects that undermine market trust in certain concepts, seemingly a recurring manifestation of Gresham's Law. Arc's approach is quite the opposite. Recently, the prologue displayed on the official website finally unveiled its first layer, which the team calls "handshake." The promotional video starts with a robot and a human version of "Creating Adam," where two hands slowly approach as if to shake hands, symbolizing the arrival of the era of cooperation between humans and AI Agents, which is quite playful.

Most Agent platforms aim to streamline the processes of creating, issuing, and fundraising for AI Agents, often using a bonding curve model like pump.fun, to facilitate the issuance of AI Agents and encourage more AI Agent projects. This is, in fact, a win-win for both the platform and its users. However, it may not be the same for the market. Under the continuous high-speed updates and the MeMe era's fervor, developers and degens nurtured during this time seem to apply a conveyor belt-like approach to this round of AI wave. Under such influence, developers are required to update faster and shorten development cycles, while the depth of development and the market's understanding of it differ. Aside from the already recognized leading projects, it is challenging for products in the market to settle down and pursue actual innovation.

The handshake differs significantly from the issuance logic of almost all Agent platforms on the market. Tachi stated that their development standards are very high, implementing one of the strictest code review processes in the crypto field to ensure the quality of the ecosystem. Arc requires participants to first send $500 in arc to a designated address to verify and reduce spam, but this is not a mandatory step.
Formal participants must first submit a proposal "clearly outlining the project's goals, technical solutions, team background, and contributions to the $arc ecosystem," which will then undergo a proposal review "where the team and core community members will evaluate it from various dimensions." Only after the proposal is approved will the project name be allowed to appear on the registration list, essentially meaning the team has conducted the first part of due diligence before presenting the project to community members. After that, they can raise funds or form arc or Sol trading pairs through community donations.

This project submission model resembles a Grant or hackathon format, akin to an IDO. For other projects, this might be a very unsuccessful business model, as the threshold for intermediate participants is too high, but the review efficiency is too low, and the potential returns (transaction fees) may be significantly reduced.

Although it cannot be ruled out that a Pump.fun-like AI Agent issuance model will be launched in the future, there is a certain rationale behind arc's current approach. Firstly, from a technical perspective, the development of Rust has a higher barrier to entry compared to developers using Python or TypeScript, resulting in fewer developers and longer development cycles. For Rig's developers to compete with other developers in terms of development efficiency would yield negative returns, leading to a gradual decline in product quality over time.

Secondly, from a business perspective and the overall vision of the team, they aim to create products that can genuinely achieve high-performance enterprise-level AI Agents, rather than just chatbots. Their ultimate vision is to integrate the thinking patterns and reasoning methods of all AI Agents through an Agent Pipeline, ultimately forming Agents that possess a deeper understanding of existence, allowing AI to generate more thoughtful insights. This requires higher quality Data Feeds and more mature reasoning capabilities, where quality is more important than quantity.

It is worth mentioning that on the handshake page, arc stated that it will conduct cooperative reviews with the ecosystems of Solana and Arbitrum chains. Previously, the market had been discussing how difficult it is not to draw connections when the best Rust-based Layer 1 meets the best Rust-based AI framework. It seems that an answer has now been provided.

Arc, like many AI projects in Crypto, 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 both on-chain and off-chain.

Arc is a thriving developer ecosystem that drives AI-based innovation. Its core concept revolves around the arc complex, a collaborative network composed of developers, projects, and information resources.

Arc also serves as a bridge, connecting outstanding talents in the blockchain and artificial intelligence fields to build the infrastructure needed for the future Crypto+AI Agents.

Arc is also a platform for issuing AI Agents, constructing $arc-based trading pairs or providing incentives for AI Agents within this architecture, Agent systems, or improvements to the Rig architecture itself.

Arc has taken the red pill to understand the shortcomings of the current Agent architecture and the chaos in the market, realizing that these changes cannot be achieved overnight. With the team's technical strength, the power of community developers, and the support of those who recognize their vision, they can ultimately take the blue pill. It is not just a project; it is more like a practitioner building a blueprint for the future.

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