The trend of AI Agents continues.

On Base and Solana, there have already been numerous AI Agent-related protocols and memes, stirring up both capital and attention in the market.

However, the current AI Agent protocols are mostly focused on the application layer, typically carving out their own AI track within existing public blockchain ecosystems.

Yet, infrastructure tends to be a higher-valued narrative in the crypto world (whether the market will buy into it is another matter). Would creating a dedicated blockchain for AI Agents, allowing more AI Agents to run on it, raise the narrative ceiling even higher?

Or, to put it another way, if some infrastructure projects can tap into the AI Agent hype amidst the market’s reluctance to back VC tokens, could it become a lifeline for them?

While you might still have doubts, someone is already working on it.

Venture Capital Is Flooding The Battlefield, With AI Agent Recognition Projects.

On November 26, Talus Network, an L1 blockchain designed specifically for AI Agents, announced it secured $6 million in funding led by Polychain, with participation from Foresight Ventures, Animoca, Geek Cartel, Echo, and others.

Additionally, a group of angel investors, including Polygon co-founder Sandeep Nailwal, Sentient core contributor and Symbolic Capital co-founder Kenzi Wang, 0G Labs CEO Michael Heinrich, Allora Labs CEO Nick Emmons, and Nuffle Labs co-founder Atlan Tutar, also participated.

Back in February this year, when the AI Agent narrative wasn’t as strong, the project completed its $3 million first-round funding, also led by Polychain Capital, with participation from dao5, Hash3, TRGC, WAGMI Ventures, and Inception Capital.

As a result, Talus’ total funding reached $9 million.

Interestingly, the “L1 designed specifically for AI Agents” caught the attention of another AI Agent.

Recently, the rapidly rising AI Agent on Base, @aixbt_agent, has also keenly identified Talus Network. Aixbt is an AI Agent that monitors hot topics in crypto Twitter, capable of analyzing and judging events happening within the industry.

Aixbt believes Talus can build fully on-chain AI Agents and states that it is closely watching this trend.

This wave of promotion has undoubtedly increased Talus’ popularity and discussions. In an environment where AI memes are everywhere, a serious infrastructure project has instead garnered more attention.

Design L1 for AI Agent and engage in system-level optimization

So, how does Talus Network create an L1 specifically designed for AI Agents?

Before discussing that, there’s a more critical narrative question: Why do AI Agents need a dedicated blockchain?

The current AI ecosystem faces three major pain points: unclear ownership, lack of transparency, and absence of permissionless features.

Specifically, in today’s centralized AI systems, control of resources is concentrated in the hands of a few entities, and users have little say over their own data and computing power. AI decision-making processes are often black-box operations, lacking auditing and verification mechanisms. Additionally, users find it difficult to customize and adjust AI services based on their needs.

Although platforms from different ecosystems, such as Virutals and vvaifu, allow users to create AI agents, the focus is primarily on permissionless aspects, followed by tokenizing AI agents and sharing asset earnings through token holdings.

However, questions like who truly owns the AI and whether it’s actually an AI still require some infrastructure to address.

Thus, a public chain dedicated to AI Agents can follow the classical blockchain problem-solving approach:

• LedgerClear—-recording and trading of resource ownership
• Contracts—-Transparency and verifiability of decision-making processes
• Cryptography—-Permissionless open ecosystems

For the Talus project, it allows for the design and deployment of decentralized, on-chain intelligent agents that seamlessly, trustlessly, and interoperably leverage both on-chain and off-chain resources and services.

It has established a protocol to represent, utilize, and trade these agents, resources, and services in a permissionless and verifiable way.

Breaking down Talus’ design, the following four technical components are worth attention:

• Infrastructure Layer: Cosmos SDK and CometBFT Combination

The Cosmos SDK is already mature and reliable, but more importantly, its modular features allow the entire blockchain system to be flexibly extended like building blocks. This flexibility becomes particularly important when AI technology is rapidly evolving.

• Contract Layer: Move Language Makes Design Elegant

The native object model of the Move language makes on-chain management of AI resources natural and elegant. For example, an AI model can be directly represented as an object in Move, with clear ownership and lifecycle, which is much simpler than traditional account-based blockchain models. Additionally, the concurrency handling capabilities of MoveVM can support hundreds or thousands of AI Agents running simultaneously, which is unimaginable in traditional serial execution environments.

• Resource Mapping Layer: Mirror Objects System

This system cleverly solves the problem of how AI resources are represented and traded on-chain. When you need to use a large language model, you can’t place the entire model on-chain.

To explain simply, you can think of Mirror Objects as “digital twins” of these off-chain resources. Through them, on-chain smart contracts can trustfully operate off-chain AI resources.

Specifically, the Model Object is responsible for the on-chain representation of AI models. It not only records the model’s metadata but also includes the model’s access permissions and usage conditions. The Data Object manages access control for datasets, ensuring the privacy and security of data when used by the AI model. The Computation Object tokenizes computing power resources, allowing computing power to be traded freely on-chain like cryptocurrency.

• Verification Layer: Multi-layer Verification Scheme

For typical AI Agent interactions, such as chatbot conversations, lightweight digital signatures can be used to ensure the authenticity of the responses.

In high-risk scenarios, such as financial decision-making, zero-knowledge proofs can be enabled to ensure the correctness of the decision-making process without revealing specific details.

For scenarios that require fast responses but can accept delayed verification, such as AI NPC behaviors in games, an optimistic fraud-proof mechanism can be used to maintain performance while ensuring final correctness.

For more technical details, refer to our previous article: “Interpretation of the Talus Whitepaper: Decentralized AI Agent Hub.”

Infrastructure At The Back, AI Dating Apps At The Front.

Currently, Talus is still in the testnet phase, and it will take time before the mainnet goes live. From the perspective of project operations and attracting user attention, while preparing for the major infrastructure launch, releasing some applications as pilots in stages will allow the market to see the utility of this L1 and build confidence.

At the same time as the funding announcement, Talus also unveiled its first application in the ecosystem, “AI Bae.” The name “Bae” comes from the internet slang “Before Anyone Else,” meaning “the most important person,” hinting at the social nature of the app.

Interestingly, Talus chose to position its first app as an AI dating game, rather than a more serious financial or business application, making it clear that the intention is to attract more ordinary users through engaging applications.

From the information disclosed so far, AI Bae will allow users to create and customize their own AI companions and introduce a Polymarket-style betting mechanism. This design is quite creative: it not only allows users to interact with AI but also enables them to tokenize their AI companions and turn them into exclusive memecoins. In other words, your “digital boyfriend/girlfriend” could not only chat with you but might also become a marketable asset.

This blending of social, gaming, and financial elements is not uncommon in the crypto market. For new blockchains aiming to break through, creatively leveraging popular trends could be an effective way to stand out.

Currently, AI Bae is open for whitelist registration. In a crypto market that is generally pessimistic about new blockchains and infrastructure, Talus’ unconventional approach might bring some unexpected surprises to the project. After all, in a bull market, sometimes a fun application is far more effective than merely talking about technical advantages.

Task-Based Gameplay, Old-School Flavor.

In addition to the aforementioned dating app, Talus has also launched a gamified task event — “Enchanted Seasons.” The first season event is called “The Awakened Orb,” running from November 11th to January 11th next year.

This design has a “gaming” vibe: daily tasks (Daily Rituals), weekly tasks (Weekly Quests), and team challenges (Team Challenges)—looking at the task system, it’s indeed a common operational strategy in Web3 projects. Currently, users can participate in tasks like linking social media accounts and posting to earn points, which is a familiar approach seen in previous projects.

However, in the current market environment, user enthusiasm for pure task systems has waned. The key to breaking through might lie in designing more differentiated tasks or making the economic value of the points clearer.

Even an L1 designed specifically for AI Agents still relies on traditional community incentive models during its early operation.

In the crypto world, no matter how advanced the technology is, success requires understanding user psychology and behavior, leveraging narratives and assets effectively.

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