Original author: BUBBLE

Reposted: Luke, Mars Finance

After the emergence of Terminal of Truths, the on-chain AI Agent era began. Today, 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. New conceptual projects emerge almost daily, overwhelming people. On December 11, a mysterious smiley face referencing the Matrix's 'we take the red pill then the blue pill' meme sparked the market after a lengthy discussion on topics related to 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 robust technical background and cross-industry experience. Founder Tachi '@0thTachi' was responsible for nuclear physics and aerospace engineering research at the Southwest Research Institute before entering blockchain. This institute is the oldest and largest independent nonprofit applied technology R&D organization in the United States. After creating Playground, he transitioned into a blockchain developer.

Another co-founder and product lead, Terry, is also a member of the network technical advisory board of Graph, a well-known blockchain data service provider. Stopher '@chairman_stoph' has extensive software engineering experience and joined Tachi's team after graduating during the pandemic, entering the cryptocurrency field. Mateo '@belangermatteo' joined Ledger as a data analyst after earning his master's degree at ETH Zurich, and later joined Playgrounds as a core technical staff member. Full-stack engineer Mochan '@0xMochan' and other engineers possess substantial technical experience.

Before arc, the Playgrounds team delivered successful experiences in complex blockchain infrastructure. For example, they built the first Ordinals and inscriptions subflow API, as well as a Python library called Subgrounds for analyzing blockchain data indexed on The Graph network.

Revolutionary AI Agent Framework - Rig

The Agent framework Rig, developed initially as an internal project at Playgrounds, aims to provide reusable infrastructure for AI and cryptocurrency projects that require querying on-chain data, with a focus on chat interfaces. As development progressed, the team realized Rig had broader application potential and decided to open source it to encourage wider community participation and innovation.

Rig aims to go beyond traditional chatbot applications and explore more possibilities for LLMs, such as 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, Llama Index, etc.) before development and predicted trends for future LLM and AI developments. At that time, there was a lack of similar frameworks in the Agent domain based on Rust, and Rust's high performance and safety made the architecture more efficient. Coupled with the team members' 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 develop an innovative framework based on Rust, standing out. It's not just in Crypto; even among all open-source agent architectures, very few use Rust as the development language, with notable examples being Sobel.io's llm-chain and Rig developed by Playgrounds.

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

Developing Rig with Rust brings advantages that other architectures lack. Firstly, safety: Rust's type system can preemptively prevent bugs at compile time, unlike TypeScript or Python, which only reveal issues after execution, thus reducing the risk of runtime errors. Rust's memory management mechanisms (like RAII) ensure there are no memory leaks and avoid data races.

In terms of performance efficiency, Rig significantly improves operational efficiency and reduces costs by utilizing Rust's zero-cost abstractions along with efficient pipelines. By using the Tokio runtime, Rig can process parallel tasks efficiently, enhancing the overall performance of agents. It allows developers to add new functional modules through Tratis, maintaining the framework's flexibility and scalability, and it can operate across multiple platforms. Modularization and concurrency ensure flexibility and scalability, while dynamic tasks and event-driven design make Agent behavior more intelligent and efficient.

Compared to most current LLM architectures in Crypto, it offers higher performance, scalability, manageability, and safety. Its position in the industry chain can optimize Rag architectures like Eliza downward, while supporting the current hot trend of multi-AI Agent integration upward. This also 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, demonstrating excellent performance across gaming, robotics, automation 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 offers high-quality products for enterprise-level clients rather than merely entertaining ordinary users, these enterprise-level AI Agents can, in some cases, replace entire industry chains, as has already been validated in the Web2 AI Agent market. Currently, Rig has over 100 forks and 1,400 stars on GitHub, with this data rapidly increasing.

What exactly is the mysterious smiley face arc?

As new conceptual projects emerge almost daily and technology rapidly iterates alongside a plethora of scams, this is often a point of criticism for blockchain. Regardless of how sectors rotate, there will always be fraudulent projects consuming the market's trust in certain concepts, reminiscent of iterations of Gresham's law. Arc's approach is quite the opposite. Recently, the prologue displayed on the official website finally unveiled its first layer, referred to as handshake. The promotional video begins with the 'creation of Adam' featuring robot and human versions, progressing to two hands slowly coming together as if about to shake hands, symbolizing the arrival of the era of cooperation between humans and AI Agents, which is quite intriguing.

Most Agent platforms aim to streamline the process of creating, issuing, and funding 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 a win-win situation for both the platform and its users. However, the market is not necessarily the same; with rapid updates and the MeMe era's fervor, the pipeline-like approach seems applicable to the current AI wave. Developers will be pressured for faster update speeds and shorter development cycles, while the depth of development and market understanding differ. Excluding already recognized leading projects, it is hard for products on the market to settle down for actual innovation.

Handshake's issuance logic is almost entirely different from that of other Agent platforms on the market. Tachi stated that their development standards are very high and implemented one of the strictest code review processes in the crypto field to ensure ecosystem quality. Arc requires participants to deposit $500 in arc to a designated address to verify and reduce spam, though this is not a necessary step.

Official participants must first submit a proposal 'clearly outlining the project's objectives, technical plans, team background, and contributions to the $arc ecosystem,' followed by a proposal review 'where teams 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, which means the team has conducted the first part of due diligence before presenting the project to community members. Then, they can raise funds or form arc or Sol trading pairs through community donations.

This project submission model resembles Grant or hackathon submissions, similar to IDO, which could be a failure in other projects due to the high barrier for intermediate participants and low review efficiency, leading to significantly reduced potential returns or 'fees.'

While it is possible that a Pump.fun-like AI Agent release model may be introduced in the future, there is a certain rationale behind arc's current approach. From a technical perspective, the high barrier to entry for Rust development compared to developers of Python or TypeScript leads to fewer developers and longer development cycles. Competing for development efficiency with other developers is counterproductive; over time, product quality will gradually decline.

From a commercial perspective and the overall vision of the team, they aim to create products that truly achieve efficient performance at the enterprise level, not just chatbots. Their ultimate vision is to integrate all AI Agent thinking patterns and reasoning methods through the Agent Pipeline, ultimately fostering a deeper understanding of existence, thereby enabling AI to generate more profound thoughts. This requires higher quality data feeds and more mature reasoning abilities, where quality is more important than quantity.

It is worth mentioning that on the handshake page, arc stated that it would cooperate with the ecosystems of the Solana and Arbitrum chains for review. Previously, the market had been discussing how difficult it is not to make associations when the best Rust-based Layer 1 meets the best Rust-based AI framework; it seems that an answer has been given now.

Like many AI projects in Crypto, arc is at the intersection of two transformative technologies: artificial intelligence and blockchain. We are rapidly entering a new paradigm where humans and agents will interact both 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 information resources.

arc is also a bridge, connecting excellent talents in the blockchain and AI fields to build the infrastructure needed for the future Crypto+AI Agent.

Arc is also a platform for issuing AI Agents, building trading pairs based on $arc for the AI Agents within this architecture, Agent systems, or improvements to the Rig framework itself.

arc has taken the red pill to understand the shortcomings of the Agent architecture and the chaos in the market, recognizing that these changes cannot happen overnight. With the team's technical strength, the power of community developers, and the support of those who acknowledge his ideas, 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.