After the advent of Terminal of Truths, the AI Agent era was launched on the chain. Nowadays, the Crypto market is full of Agentic concepts in various fields, whether it is MeMe, tool applications, launch platforms, model frameworks, honeycomb clusters and other concepts, there are new concept projects almost every day, which makes people overwhelmed. On December 11, there was a mysterious smiley face with a brief introduction that played the we take the red pill then the blue pill stalk of The Matrix. After a long speech on topics related to AI philosophy, and finally announcing the token address of the project, it immediately ignited the market. What is it, and how does it support a market with a market value of up to 300 million? This article will reveal the magic behind arc for you.
Strong team background and technical strength
The team behind arc, Playgrounds, can be said to have a very deep technical background and cross-industry experience. The founder Tachi @ 0 thTachi worked at the Southwest Research Institute in the United States before entering the blockchain, responsible for research on nuclear physics and aerospace engineering. The institute is the oldest and largest independent non-profit applied technology research and development institution in the United States. After creating Playground, he transformed into a blockchain developer.
Another co-founder and product manager, Terry, is also a member of the network technical advisory board of Graph, a well-known blockchain data service provider. Stopher @chairman_stoph has considerable software engineering experience. After graduating during the epidemic, he joined Tachis team and entered the cryptocurrency field. Mateo @belangermatteo joined Ledger as a data analyst after obtaining a masters degree from the Federal Institute of Technology in Lausanne, and then joined Playgrounds as a core technical staff member. Full-stack engineer Mochan @0x Mochan and other engineers have considerable technical experience.
Before arc, the Playgrounds team also had some successful experience in delivering complex blockchain infrastructure. For example, they built the first Ordinals and Inscriptions substream APIs, as well as a Python library called Subgrounds for analyzing blockchain data indexed on the Graph Network.
Breakthrough AI Agent Framework - Rig
The Agent framework behind arc, Rig, was originally developed internally by Playgrounds to provide reusable infrastructure for AI and cryptocurrency projects that need to query on-chain data, with a particular focus on chat interfaces. As development progressed, the team realized that Rig has broader application potential, so they decided to open source it to promote broader community participation and innovation.
Rigs goal is to go beyond traditional chatbot applications and explore more possibilities of LLM. For example, structured data extraction, synthetic data generation, and injecting intelligence into existing data pipelines. Before development, the Playgrounds team reviewed existing frameworks in the market, such as LangChain, Llama Index, etc., and made predictions about the future development trends of LLM and AI. At that time, there was a lack of similar Rust-based frameworks in the Agent framework field. Rusts high performance and security can make the architecture more efficient. In addition, the team members also have rich Rust expertise, and finally chose Rust as the main development language for Rig.
Looking back at the current leaders of the Agent architecture in the Crypto market, Eliza uses Typescript, Zerepy uses Python, and Rig chooses to develop a groundbreaking framework based on Rust and stands out. Not only Crypto, but even among all Agent open source architectures, there are very few that use Rust as a development language. The more well-known ones are Sobel.ios llm-chain and Rig developed by Playgrounds.
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 dont have. The first is security. Rusts type system can prevent bugs early during compilation, rather than having to check after running like typescript or python, reducing the risk of runtime errors. Rusts memory management mechanism (such as RAII) ensures that there are no memory leaks and avoids data competition.
In terms of performance efficiency, Rig uses Rusts zero-cost abstraction and efficient pipelines to greatly improve operating efficiency and reduce costs. When using tokio runtime, Rig can efficiently process in parallel to improve the performance of the overall agent. Developers are allowed to add new functional modules through Tratis, maintain the flexibility and scalability of the framework, and can operate on multiple platforms. Modularity and concurrency ensure flexibility and scalability, and dynamic tasks and event-driven make Agent behavior smarter and more efficient.
Compared with most LLM architectures on Crypto, Rig has higher performance, scalability, manageability, and security. Its position in the industry chain can optimize Rag architectures like Eliza downward, and support the current hot Swarm concept of multi-AI agent integration upward. This also makes Rigs architecture very suitable for expanding reliable and high-performance AI/ML channels. Rig can be said to be designed for institutional-level project deployment.
This makes Rig an ideal tool for developing high-performance AI Agents, whether in games, robots, automated workflows or real-time simulations. The architecture allows seamless expansion from local development environments to enterprise-level systems, laying the underlying foundation for institutional adoption. When a project provides high-quality products to enterprise-level customers, rather than just entertainment for ordinary users, these enterprise-level AI Agents can even replace the entire industry chain in some cases, which has been verified in the AI Agent market of Web2. Currently, Rig has more than 100 forks and 1,400 stars on Github, and this data is growing at an accelerated rate.
What is the mysterious smiley arc?
There are new concept projects coming out almost every day, and the technology is rapidly iterating, but there are also a lot of scams. This is also a point that blockchain is often criticized for. No matter how the unethical sectors rotate, there will always be scam projects to consume the markets trust in a certain concept, as if it is the reappearance of Gramsings law. Arcs approach is just the opposite. The prologue displayed on the official website some time ago has finally unveiled the first layer of veil recently. The team calls it handshake. The promotional video starts with the robot and human version of Creation of Adam and the two hands slowly approaching as if to shake hands, implying the arrival of the era of cooperation between humans and AI agents, which is quite interesting.
Most Agent platforms will shorten the creation, issuance, and fundraising process of AI Agents as much as possible (mostly using the bonding curve model of pump.fun), in order to make it easier for people to issue AI Agents, so that more AI Agent projects can emerge, which is actually a win-win situation for the platform and its users. But it is not necessarily the case for the market. With continuous and high-speed updates, the Dev and Degen developed in the MeMe era seem to be suitable for this round of AI wave. Under such influence, developers will be required to update faster and have a shorter development cycle. The depth of development is different from the markets understanding of it. Apart from the leading projects that everyone has recognized, it is difficult for products on the market to settle down and make actual innovations.
Handshake has a different issuance logic from almost all Agent platforms on the market. Tachi said that their development standards are very high and they have implemented one of the most stringent code review processes in the crypto field to ensure the quality of the ecosystem. Arc requires participants to first deposit $500 arc to a designated address to verify and reduce spam, but this is not a necessary step.
Formal participants first need to submit a proposal clearly explaining the projects goals, technical solutions, team background, and the teams contribution to the $arc ecosystem, etc., and then the proposal needs to be reviewed The team and core community members will evaluate it in various dimensions. Only when the proposal is passed will the project name be allowed to appear on the registration list. This is equivalent to the team helping to do the first part of the due diligence before presenting the project to the community members, and then they will raise funds themselves or in the form of community donations to form arc or Sol trading pairs.
This project submission model, which is similar to Grant or Hackathon, and also like IDO, may be a very failed business model for other projects. The threshold for intermediate participants is too high, but the review efficiency is too low, and the return handling fees that can be obtained may be greatly reduced.
Although it is not ruled out that an AI Agent similar to Pump.fun will be released in the future, there is actually a reason for arc to do so. First of all, from a technical point of view, Rust development has a high threshold and there are fewer developers than Python or Typescript, and the development cycle is also longer. Letting Rig developers and other developers compete for development efficiency is a negative benefit, and in the long run, the product quality will gradually decline.
Secondly, from a business perspective and the teams overall vision, the product they want to make is an enterprise-level AI agent that can truly achieve high performance, not just a chatbot. Their ultimate vision is to combine the thinking patterns and reasoning methods of all AI agents through the Agent Pipeline to eventually form an agent that has a deeper understanding of things, allowing AI to think more. This requires higher-quality Data Feeds and more mature reasoning capabilities. Quality is more important than quantity.
It is worth mentioning that on the handshake page, arc stated that it will review the cooperation with the Solana and Arbitrum chain ecosystems. Before this, the market has been discussing that when the best Rust-based Layer1 meets the best Rust-based AI framework, it is hard not to make associations. Now it seems that an answer has been given.
Arc, like many Crypto AI projects, 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 with each other both on-chain and off-chain.
Arc is a thriving developer ecosystem that drives innovation based on artificial intelligence. Its core concept revolves around the Arc Complex, a collaborative network of developers, projects, and information resources.
ARC is also a bridge that connects outstanding talents in the fields of blockchain and artificial intelligence to build the infrastructure needed for future Crypto+AI Agents.
Arc is also an AI Agent distribution platform, which builds $arc-based trading pairs or provides incentives for AI Agents and Agent systems of the architecture or improves the Rig architecture itself.
Arc took the red pill to understand the shortcomings of the current Agent architecture and the chaos in the market, and knew that all these changes would not be achieved overnight. With the technical strength of the team, the power of community developers, and the people who recognized his ideas, he could finally take the blue pill. It is not only a project, but more like a practitioner who is building a blueprint for the future.
