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Asphere, the enterprise services arm of Ankr, has once again set a new benchmark for simplified blockchain creation by building and launching a cutting-edge, no-code L3 blockchain deployer on behalf of the Frax team. The solution enables any dev to seamlessly create a new L3 network on top of Fraxtal's modular EVM L2 infrastructure, opening up unprecedented opportunities for the DeFi and stablecoin ecosystem.

[**Deploy a Frax L3 Now →**](https://fraxtal.rollup.asphere.xyz/)

## **Guide To Launching Your L3 Chain**

Any developer can effortlessly create a new Frax L3 by using the no-code interface to seamlessly customize and deploy their new chain!

- Create an account on the Frax UI
- Start by choosing Frax and mainnet or testnet
- Select your desired DA layer
- Choose a chainID, name, and gas token
- Choose an infrastructure package
- Connect your wallet, finalize payment, and deploy!

[**Get started →**](https://fraxtal.rollup.asphere.xyz/)

[**Read the full docs →**](https://www.ankr.com/docs/scaling-services-nocode-deployer/#fraxtal-rollup-deployment)

## **Rapidly Build, Test, and Launch L3s On Fraxtal**

Asphere's contribution to the Fraxtal ecosystem is a game-changer for scalability. By providing a no-code L3 deployer, Asphere is eliminating the steep technical barriers traditionally associated with blockchain development. Now, developers can:

- **Deploy Custom L3 Networks Instantly** – Without requiring deep blockchain expertise, developers can spin up their own L3 chains within minutes, significantly reducing time to market.
- **Access a Stablecoin-Centric DeFi Infrastructure** – Fraxtal’s core infrastructure is purpose-built for decentralized stablecoins and DeFi applications, making it an ideal environment for financial innovation.
- **Utilize Fraxtal’s Enhanced Liquidity and Composability** – By integrating with Fraxtal’s liquidity pools and DeFi mechanisms, new L3 chains benefit from seamless cross-chain transactions and enhanced user experiences.

By simplifying blockchain deployment and integrating with an already powerful modular framework, Asphere’s solution empowers devs to focus on building unique applications rather than dealing with infrastructure complexities.

[**Launch your L3 now →**](https://fraxtal.rollup.asphere.xyz/)

## **Fraxtal as the Future of Stablecoin DeFi**

Fraxtal’s ecosystem is purpose-built to transform stablecoin-driven DeFi applications. Unlike generic Layer 2 solutions, Fraxtal provides a tailored environment optimized for:

- **Decentralized Stablecoins** – Fraxtal’s infrastructure enhances the efficiency and scalability of stablecoin transactions, reducing fees and improving settlement times.
- **Optimized Liquidity & Yield Strategies** – Developers can take advantage of Fraxtal’s liquidity pools and yield-generating mechanisms, which are natively designed for stablecoin and lending applications.
- **Reduced Costs & Increased Transaction Throughput** – Fraxtal’s infrastructure is designed to handle high transaction volumes at minimal costs, making it a preferred choice for stablecoin and DeFi applications that require efficiency at scale.

## **Why Devs Should Build on Fraxtal for DeFi and Stablecoin Apps**

Fraxtal stands out as one of the most compelling blockchain environments for DeFi and stablecoin innovation. Developers choosing Fraxtal gain access to:

- **Seamless L3 Deployments** – The no-code deployer built by Asphere ensures a frictionless experience, enabling even non-technical teams to launch their own blockchain networks.
- **Pre-Built Integrations for Stablecoin and Lending Protocols** – Fraxtal’s ecosystem is designed to support lending, collateralized debt positions (CDPs), and stablecoin issuance, removing the need for extensive custom development.
- **Scalability Without Compromise** – Fraxtal’s modular infrastructure ensures that projects can scale while maintaining low fees and high transaction speeds.
- **Built-In Composability** – Developers can build applications that natively interact with Fraxtal’s existing DeFi protocols, leveraging liquidity and yield strategies to maximize user engagement.

## **A New Era for Fraxtal Development**

With the no-code L3 deployer, the future of blockchain is more accessible, scalable, and developer-friendly than ever before. Whether you’re an established DeFi project or a new developer entering the space, now is the perfect time to explore the possibilities that Fraxtal and Asphere’s groundbreaking technology have to offer.

## Join the Conversation on Our Channels!

[Twitter](https://twitter.com/ankr) | [Telegram](https://t.me/ankrnetwork) | [Substack](https://ankr.substack.com/) |  [Discord](https://discord.ankr.com/) | [YouTube](https://www.youtube.com/c/AnkrOfficial) | [LinkedIn](https://www.linkedin.com/company/ankr/) | [Reddit](https://www.reddit.com/r/Ankrofficial/) | [All Links](https://id.tomo.inc/x@ankr)

Learn more about launching an L3 on one of the leading ecosystems for stablecoins and DeFi.

Just Shipped: Fraxtal’s No-Code L3 Deployer

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Kevin is a business writer, journalist, and avid explorer of the blockchain and tech industry. His work has been covered across crypto and traditional media as Ankr’s Senior Writer, with topics spanning the big picture of “Web3,” tech breakthroughs, and how blockchain is changing our digital lives. Working with some of blockchain’s most talented engineers daily, Kevin gains unique insight into what advances we can expect next and the implications they hold for us all.

Technical Writer

Kevin Dwyer

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Ethereum’s upcoming upgrade, known as Pectra, is expected to launch on mainnet around May 2025. It introduces several meaningful changes to the way Ethereum handles staking, data throughput, and account functionality. For stakers, Pectra is especially notable, introducing the most impactful validator changes since the Shapella upgrade in April 2023.

This article provides a breakdown of the upgrade with a focus on staking, while also covering the broader implications across the Ethereum network.

## Key Upgrade #1: Max Effective Balance Increase (EIP-7251)

Currently, each Ethereum validator can earn rewards on a maximum of 32 ETH. This limit forces large staking services and institutions to operate thousands of validators to manage larger amounts of staked ETH. While it gives the appearance of decentralization, in practice many of these validators are operated under a single entity, and maintaining this structure adds unnecessary overhead to the network.

With Pectra, the maximum effective balance (MaxEB) will increase from 32 ETH to 2,048 ETH per validator.

**How does this impact stakers:**

- Large staking operators can consolidate their validators, reducing the overall number of validators on the network.
- Network bandwidth and validator churn are reduced, improving efficiency.
- For solo stakers, rewards above 32 ETH will now count toward staking returns, allowing for compounding without needing to spin up additional validator instances.

It’s important to note that slashing penalties scale with stake size, so the risks will also increase. Misbehavior from a validator holding 2,048 ETH would result in a significantly larger penalty than a 32 ETH validator.

## Key Upgrade #2: Execution Layer Triggerable Withdrawals (EIP-7002)

Previously, only a validator’s signing key could trigger an exit from the active validator set. Pectra introduces the ability for a withdrawal address, such as a smart contract or externally owned account (EOA) to also initiate a validator exit.

**Why this matters:**

- Adds more flexibility to validator setups.
- Enables more trust-minimized withdrawal configurations.
- Useful for staking pools and DAOs that want to maintain control over validator exits without access to signing keys.

This change improves operational security for staking infrastructure and simplifies withdrawal management.

## Key Upgrade #3: Faster Deposit Processing (EIP-6110)

Ethereum’s pre-merge architecture included a delay between when a deposit was made and when it became active on the Beacon Chain. This delay (previously around 9 hours), was a safeguard against proof-of-work chain reorganizations.

With Pectra, this delay is removed. Validator deposits will now become active after roughly 13 minutes, aligned with modern network conditions.

This reduces time-to-activation for new validators and makes the overall staking process more responsive. For liquid staking platforms, it means users can see their stake become productive sooner.

## Key Upgrade #4: Blob Scaling Improvements (EIP-7691 and EIP-7623)

Ethereum introduced “blobs” in the Dencun upgrade as a cheaper way for Layer-2 networks to post data to Ethereum. Since launch, blobs have helped reduce fees for L2 users by an order of magnitude.

However, blob demand has grown rapidly. To address this, Pectra increases:
- Target blobs per block from 3 to 6
- Maximum blobs per block from 6 to 9

**What this achieves:**
- Increases the data throughput of the Ethereum base layer.
- Keeps Layer-2 transaction costs low, even during periods of high usage.

To ensure node performance isn’t negatively impacted, EIP-7623 also caps the size of blocks that contain excessive calldata. This protects the network from bandwidth overload while allowing for blob expansion.

## Key Upgrade #5: Account Abstraction via EIP-7702

Account abstraction refers to making Ethereum accounts (wallets) more programmable and flexible. Currently, EOAs can’t batch transactions or offer more advanced security without turning into full smart contracts.

EIP-7702 introduces a hybrid model: EOAs can temporarily adopt smart contract-like capabilities for specific transactions.

**Practical benefits include:**

- **Bundled transactions**: For example, approve and stake can happen in one step.
- **Gas sponsorship**: Third parties can cover gas fees.
- **Alternative authentication**: Users can sign transactions using device-level security like passkeys.
- **Spending limits and recovery options**: Improved safety for users without the need for new wallets.
While not staking-specific, this upgrade improves the usability of Ethereum wallets, especially in onboarding new users to staking platforms or managing smart contract wallets used in delegation setups.

## Rollout Status and Mainnet Expectations

- **Holesky Testnet**: Pectra was activated on February 24, 2025. A configuration issue caused a chain split, which was patched quickly. Holesky performance has since recovered but remains under observation.
- **Sepolia Testnet**: Successfully upgraded on March 5, 2025, with no major issues.
- **Mainnet Activation**: Expected in May 2025, assuming stability continues across testnets.

Node operators and validators must update their client software ahead of the mainnet activation to avoid being forked off the network.

## Summary for Stakers

Pectra represents a meaningful evolution in Ethereum staking:
- **More efficient staking setups** with the 2,048 ETH MaxEB.
- **Improved validator control and automation** through execution-layer withdrawals.
- **Faster onboarding for new validators** with reduced deposit delays.
- **Better network scalability** for all users through blob expansion.

Ankr Stakers will benefit from improved infrastructure efficiency, smarter withdrawal paths, and better compounding mechanics. These upgrades move Ethereum closer to its long-term goals of performance, flexibility, and accessibility, while directly improving the staking layer’s design and usability.

We’ll continue monitoring the mainnet rollout and will provide additional updates as client releases and final activation dates are announced!


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Ethereum’s Pectra Upgrade: What It Changes for Stakers and the Network

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Ankr Staking Team

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The demand for effortless development tools is expanding at a breakneck pace as no-code building becomes the new normal thanks to the advent of AI and other innovations. Asphere has been at the forefront of the no-code blockchain movement, providing a powerful rollup deployer that allows users to create and launch their own networks effortlessly. Now, Asphere is taking things to the next level with a significant upgrade that introduces new customization options for rollup stack frameworks, data availability (DA) layers, and gas tokens. These enhancements empower users with even greater flexibility in designing their ideal blockchain.

[**Launch your own blockchain in minutes →**](https://www.ankr.com/rollup-as-a-service-raas/)

## **Expanded Stack Options: Polygon CDK and ZK Stack**

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One of the standout additions to the Asphere No-Code Deployer is the inclusion of two widely recognized rollup frameworks—**Polygon CDK and ZK Stack**.

- **Polygon CDK (Chain Development Kit)**: As a modular toolkit for launching customized Layer 2 chains on Ethereum, Polygon CDK offers seamless integration with Ethereum while leveraging zero-knowledge proofs (ZKPs) for enhanced scalability and security. With Asphere’s no-code approach, users can now deploy a rollup utilizing Polygon CDK with just a few clicks, eliminating the complexity and time requirement of starting from scratch.
- **ZKsync’s ZK Stack**: As a leading ZK-rollup framework, ZK Stack allows developers to deploy Ethereum-compatible Layer 2 rollups with the benefits of cost efficiency, security, and high throughput. By integrating ZK Stack into its deployer, Asphere enables users to create zkSync-based rollups without the need for in-depth technical knowledge.

With these additions, users can now select the optimal rollup stack that aligns with their specific use cases, whether it be for DeFi, gaming, or enterprise applications.

## **New Data Availability (DA) Layer Options: Avail, Celestia, Eigen, and NEAR**

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Asphere is also expanding its data availability layer (DA) choices, allowing users to select from multiple cutting-edge DA solutions. DA layers play a crucial role in ensuring rollups can store and access data efficiently while maintaining security and decentralization. The newly added DA layers include:

- **Avail DA**: Avail DA is a horizontally scalable data availability layer that combines KZG Commitments and Data Availability Sampling (DAS) to deliver trust-minimized verification and near-instant finality—unlocking unlimited blockspace that dynamically expands with network demand. Avail DA empowers builders to deploy high-throughput applications at a fraction of the cost, while enabling lightning-fast transaction pre-confirmations (~250ms) and throughput 15x faster than conventional layers.
- **Celestia DA:** As one of the pioneers in modular blockchain infrastructure, Celestia enables rollups to securely outsource data storage while verifying availability through Data Availability Sampling (DAS). Celestia's modular architecture allows developers to deploy unstoppable apps with full-stack customizability.
- **Eigen DA:** EigenDA utilizes EigenLayer’s decentralized restaking infrastructure to access significant cryptoeconomic security and to provide efficient, secure, and decentralized storage of transaction data. . It offers ultra high throughput and cost-effective data availabilty for rollups, as well as a mechanism to stake your own token, making it a compelling choice for developers seeking hyperscalable use cases .
- **NEAR DA**: NEAR Protocol's DA solution provides fast, low-cost, and secure data availability services for rollups. By utilizing NEAR’s advanced sharding technology, rollups benefit from improved performance and lower costs.

These expanded DA layer options allow users to fine-tune their rollup deployments based on their preferred balance of decentralization, performance, and cost.

## **New Gas Token Customization: ANKR, USDC, or Custom Tokens**

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Gas tokens serve as the lifeblood of blockchain transactions, and Asphere is now providing more options for users to define their rollup’s native gas token. With this upgrade, users can select from the following options based on their stack and DA layer choice:

- **ANKR**: A popular token within the Web3 infrastructure space, ANKR can now be used as the native gas token for rollup transactions, providing seamless integration with staking and other network incentives.
- **USDC**: Stablecoins like USDC are gaining traction as gas tokens due to their price stability and broad acceptance across blockchain ecosystems. Using USDC as a gas token reduces volatility risks and enhances user experience.
- **Custom Token Creation**: For those looking to define a unique economic model, Asphere now allows users to create their own native gas token. This feature is particularly valuable for projects that want to build their own token economy and governance structures.

By offering these gas token customization options, Asphere gives rollup creators more control over their transaction fee models, further enhancing the flexibility of their deployments.

## **Unlocking Limitless Possibilities with Asphere**

With the introduction of these new rollup stack frameworks, DA layers, and gas token options, Asphere is solidifying its position as the premier no-code rollup deployment platform. These additions empower users—whether they are developers, enterprises, or blockchain enthusiasts—to build and customize their rollups with unprecedented ease and efficiency.

[**Explore the new features today and build your own rollup in minutes with Asphere!**](https://www.ankr.com/rollup-as-a-service-raas/)

## Join the Conversation on Our Channels!

[Twitter](https://twitter.com/ankr) | [Telegram](https://t.me/ankrnetwork) |  [Discord](https://discord.ankr.com/) | [YouTube](https://www.youtube.com/c/AnkrOfficial) | [LinkedIn](https://www.linkedin.com/company/ankr/) | [Instagram](https://www.instagram.com/ankr) | [Reddit](https://www.reddit.com/r/Ankrofficial/) | [All Links](https://id.tomo.inc/x@ankr)

Learn more about the new options now live on the no-code rollup deployer!

No-Code Rollup Deployer: New Stack, DA, Gas Token Options!

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Building AI-powered crypto agents isn’t the easiest job — these systems need to complete tasks like analyzing market trends, interacting with blockchain networks via APIs, and executing transactions autonomously, all while handling massive amounts of data in real-time.

But what’s the key to making agents truly intelligent and efficient? Choosing the right AI model to power them.

With so many large language models (LLMs) available, from OpenAI’s ChatGPT-4.5 to Google’s Gemini and Anthropic’s Claude, it can be tough to determine which one is best suited for crypto-focused automation. On top of that, newer AI models like DeepSeek-R1 offer unique advantages that could be game-changers for blockchain applications. In this article, we’ll break down the strengths and weaknesses of each AI model so you can make an informed decision about which one fits your needs best.

[Build AI agents using Ankr & elizaOS](https://www.ankr.com/blog/how-to-build-a-crypto-ai-agent-using-eliza-os-and-ankr-in-5-steps/) 

## 1. OpenAI’s ChatGPT-4.5: A Versatile AI With Strong Language Capabilities

ChatGPT-4.5, OpenAI’s latest iteration, builds upon the strengths of GPT-4 with improved contextual understanding and enhanced reasoning abilities. This model is especially useful for AI agents that need to engage in complex decision-making, execute natural language queries, and integrate real-time web search capabilities.

#### *Pros:*

- **Strong contextual understanding** – Great for analyzing smart contract terms, financial news, and user queries.
- **Broad general knowledge** – Useful for multi-purpose crypto AI agents that need to handle diverse topics.
- **Web-enabled capabilities** – Can fetch real-time blockchain data when integrated properly.

#### *Cons:*

- **Computationally expensive** – Running a full-scale crypto agent on GPT-4.5 can be resource-intensive.
- **Limited math reasoning** – It still struggles with highly technical mathematical computations, which can be crucial for crypto trading bots.

## 2. Google Gemini 2.0: Advanced Multimodal AI for Comprehensive Blockchain Analysis

Google's Gemini 2.0 represents a significant advancement in AI technology, designed to excel in large-scale applications with robust multimodal capabilities. This model processes and generates text, images, and audio, making it particularly advantageous for crypto agents that require comprehensive analysis of diverse data types, such as blockchain charts, NFT marketplaces, and complex financial reports. Gemini 2.0's integration with Google's ecosystem enhances its utility in developing and deploying scalable crypto solutions.

#### *Pros:*

- **Enhanced Multimodal Processing:** Capable of interpreting and generating text, images, and audio, facilitating a holistic approach to analyzing crypto trends across various media.
- **Seamless Integration with Google Services:** Offers compatibility with Google's cloud-based tools, streamlining the development and deployment of large-scale crypto projects.
- **Scalability and Efficiency:** Engineered for high performance, providing efficient solutions suitable for extensive blockchain applications.

#### *Cons:*

- **Potential Ecosystem Lock-In:** Deep integration with Google's infrastructure may limit flexibility for developers seeking open-source or platform-independent alternatives.
- **Learning Curve for Advanced Features:** Utilizing the full spectrum of Gemini 2.0's capabilities may require a substantial understanding of Google's AI ecosystem.

## 3. Anthropic’s Claude 3.7 Sonnet: Pioneering Hybrid Reasoning for Complex Problem-Solving

Anthropic's Claude 3.7 Sonnet introduces a groundbreaking "hybrid reasoning" approach, allowing users to adjust the model's reasoning depth to suit specific tasks. This flexibility is particularly beneficial for crypto agents engaged in intricate activities such as smart contract audits, regulatory compliance assessments, and detailed financial analyses. The model's "extended thinking mode" enables thorough deliberation on complex queries, enhancing the accuracy and reliability of outputs.

#### *Pros:*

- **Adaptive Reasoning Capabilities:** Users can modulate the model's reasoning processes, balancing depth and response time to meet diverse application requirements.
- **Transparency in Decision-Making:** Features like the "scratchpad" provide insights into the model's thought process, aiding in prompt refinement and enhancing trust in automated decisions.
- **Enhanced Performance in Specialized Domains:** Demonstrates superior proficiency in coding, finance, and legal tasks, making it a valuable asset for complex blockchain operations.

#### *Cons:*

- **Increased Computational Demands:** The extended reasoning capabilities may lead to higher resource consumption, impacting operational costs and efficiency.
- **Potential for Over-Processing:** In certain scenarios, the model's in-depth analysis may result in overcomplicated solutions, necessitating careful management to align with practical application needs.

## 4. DeepSeek-R1: A Cost-Effective, Open-Source AI Model for Crypto AI Development

### **Overview**

DeepSeek-R1 is an open-source reasoning model designed to excel in mathematical reasoning, logical inference, and real-time problem-solving—critical capabilities for crypto AI agents handling blockchain transactions, smart contract analysis, and algorithmic trading. Released in January 2025 under the MIT License, it offers a powerful alternative to proprietary models, giving developers full customization control without licensing restrictions.

Its low-cost training (approximately $6 million compared to OpenAI's GPT-4 at $100 million) and efficient computational resource utilization make it particularly attractive for crypto developers building AI agents that need to operate continuously without incurring excessive infrastructure costs. DeepSeek-R1 is also highly efficient, requiring only one-tenth of the power used by comparable large language models, making it a viable choice for developers running AI models on decentralized networks with limited resources.

#### *Pros:*

- **Open-Source Accessibility** – The MIT License allows unrestricted modifications, enabling developers to fine-tune the model for specific blockchain applications, such as DeFi automation, crypto market analysis, and Web3 interactions.
- **Low-Cost and Efficient** – With significantly lower training and operational costs than larger proprietary models, DeepSeek-R1 is well-suited for resource-conscious developers who need to deploy AI agents on-chain or in high-frequency trading environments.
- **Strong Mathematical and Logical Reasoning** – The model has demonstrated high performance on problem-solving benchmarks, making it useful for applications requiring precise calculations, fraud detection, and cryptographic verification.

#### *Cons:*

- **Censorship Restrictions** – The API version includes content limitations imposed by Chinese authorities, which may restrict its usability for projects requiring open-ended, unrestricted discourse, such as decentralized governance discussions or regulatory compliance analysis.
- **Potential Readability Issues** – While improved over earlier iterations, DeepSeek-R1 may still produce occasional repetitive outputs or language inconsistencies, requiring additional prompt engineering or fine-tuning for optimal performance in crypto-related applications.

## 5. Tencent's Hunyuan Turbo S

Tencent has recently unveiled Hunyuan Turbo S, an AI model designed for rapid response times, outperforming competitors like DeepSeek-R1. Hunyuan Turbo S is capable of providing answers within a second, enhancing efficiency in applications requiring swift interactions. Its capabilities in knowledge, mathematics, and reasoning are on par with advanced models, making it a strong candidate for real-time blockchain applications. Additionally, Tencent claims that Hunyuan Turbo S operates at a significantly lower cost, reflecting competitive advancements in AI technology.

#### *Pros:*

- **Fast Response Times:** Ideal for applications requiring immediate data processing and decision-making.
- **Cost Efficiency:** Lower operational costs make it accessible for a wide range of projects.
- **Advanced Reasoning Capabilities:** Suitable for complex problem-solving tasks in blockchain interactions.

#### *Cons:*

- **Limited Global Adoption:** As a newer model, it may have less community support and integration resources.
- **Regional Availability:** Primarily developed in China, which may affect accessibility and support for international developers.

## 6. Meta's Llama 3.3

Meta's Llama 3.3 is the latest in the Llama series of large language models, offering a range of parameter sizes up to 405 billion. This model is open-source, promoting transparency and collaboration within the AI community. Llama 3.3 excels in tasks requiring complex reasoning and high accuracy, making it suitable for advanced blockchain applications. Its open-source nature allows developers to fine-tune the model for specific use cases, enhancing flexibility and adaptability.

#### *Pros:*

- **Open-Source Accessibility:** Encourages community-driven development and customization.
- **High Parameter Count:** Supports complex tasks with extensive data processing needs.
- **Versatility:** Applicable to a wide range of blockchain and crypto-related tasks.

#### *Cons:*

- **Resource Intensive:** High computational requirements may pose challenges for developers with limited resources.
- **Operational Costs:** Running large-scale models can be expensive, impacting budget-constrained projects.

## 7. Grok 3

Grok is an AI model developed by xAI, a company founded by Elon Musk. Designed to integrate seamlessly with platforms like X (formerly Twitter), Grok is tailored for real-time information retrieval and interaction. Its capabilities include answering questions and providing insights based on up-to-date information, making it a valuable tool for crypto AI agents that require current data and trend analysis. Grok's integration with social media platforms allows for monitoring and analyzing market sentiment, which is crucial in the volatile crypto market.

#### *Pros:*

- **Real-Time Data Access:** Provides up-to-date information, essential for timely decision-making in crypto markets.
- **Social Media Integration:** Offers insights into market sentiment and trends by analyzing social media activity.
- **User-Friendly Interaction:** Designed for seamless user engagement, enhancing accessibility for developers and end-users.

#### *Cons:*

- **Limited Availability:** As a newer model, it may have restricted access and limited documentation.
- **Integration Constraints:** Primarily designed for specific platforms, which may limit its applicability in broader contexts.

## **Final Thoughts: Which AI Model is Right for You?**

Each of these models has unique strengths, and depending on your needs, you may even want to use a combination of them. As AI continues to evolve, crypto developers will have even more tools at their disposal to build autonomous agents that push the boundaries of decentralized finance.

## Join the Conversation on Our Channels!

[Twitter](https://twitter.com/ankr) | [Telegram](https://t.me/ankrnetwork) | [Substack](https://ankr.substack.com/) |  [Discord](https://discord.ankr.com/) | [YouTube](https://www.youtube.com/c/AnkrOfficial) | [LinkedIn](https://www.linkedin.com/company/ankr/) | [Reddit](https://www.reddit.com/r/Ankrofficial/) | [All Links](https://id.tomo.inc/x@ankr)

Learn more about which AI models are best suited as the brains behind Web3 AI agents.

Choosing the Best AI Models for Crypto Agents: The Developer’s Guide

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AI agents have come a long way, completely changing the way many businesses are looking to handle complex tasks. What started as simple tool-calling systems has evolved into advanced multi-agent networks that can tackle much more. **This isn’t just about better technology—it’s a whole new way for companies to think about automation and decision-making.** This article will dive into what multi-agent systems are and how enterprises are using them to transform and automate operations.

[Deploy your first Crypto AI Agent using Ankr →](https://www.ankr.com/blog/how-to-build-a-crypto-ai-agent-using-eliza-os-and-ankr-in-5-steps/)

## **The Evolution of AI Agents**

Modern AI agents use large language models (LLMs) as reasoning engines to determine actions for high-level tasks. These systems' foundational components include chat models (the conversational interface), tools (external functions), and chat history (ongoing context that informs decisions). While early implementations followed simple patterns, **today's enterprise solutions feature interconnected specialist agents working together to solve complex problems.**

## **The Challenge of Scale**

As organizations deployed increasingly capable agents, a critical challenge emerged: efficiency often decreased as toolsets expanded. This "agent scaling problem" manifests in several ways:

- Decision complexity increases with more available tools
- Longer reasoning chains lead to higher computational costs
- Tool selection accuracy suffers with broader options
- Overall system reliability declines

This challenge has driven the development of more sophisticated architectural approaches, with **multi-agent systems emerging as the leading solution.**

## **Multi-Agent Systems: The New Paradigm**

Developers have turned to multi-agent architectures to overcome scaling challenges. The most notable approach is the Supervisor architecture, which organizes agents into specialized, well-tested units that function as tools within a structured system.

Key benefits include:

- **Agent-as-tool approach**: Treating specialized agents as callable tools
- **Specific expertise**: Each agent focuses on a narrowly defined domain
- **Separation of concerns**: Tasks are distributed across multiple agents
- **Enhanced testability**: Individual agents can be independently evaluated

## **Ankr’s Moniqa: A Case Study in Advanced Agent Architecture**

Ankr's monitoring agent Moniqa exemplifies these principles in practice. As a dedicated monitoring and QA agent, Moniqa analyzes real-time telemetry metrics and RPC usage data for blockchain services, demonstrating the value of specialized focus within a broader agent ecosystem.

Moniqa works within a multi-agent architecture alongside specialized components like the NodeOps Agent, which handles aspects such as blockchain node health and host resource analysis. This separation of responsibilities ensures each agent maintains efficiency even as the overall system grows in complexity.

## **Model Context Protocol: Enabling Agent Collaboration**

For multi-agent systems to function effectively, standardized communication is essential. The Model Context Protocol (MCP) enables seamless interaction between agents, supporting:

- **Scalable deployment**: Agents operate independently but cohesively
- **Standardized messaging**: Efficient collaboration between agents
- **Optimized workflows**: Agents can call each other as needed
- **Networked expertise**: Each agent contributes specialized knowledge

In Ankr's implementation, this protocol allows Moniqa and other agents to share data and insights, creating a more responsive and integrated operational environment.

## **Enterprise Implementation Framework**

In enterprise settings, AI agent architectures typically feature distinct operational zones:

1. **Front Office**: User-facing agents handling external requests
2. **Back Office**: Specialized agents focusing on internal tasks
3. **Private Network**: Secure agents accessing protected resources

Within this framework, monitoring agents like Moniqa serve as front-office components, interacting directly with stakeholders while collaborating with back-office systems to deliver comprehensive insights.

## **Building Blocks of Modern Agent Systems**

The core components of advanced agent frameworks include:

1. **Clients**: Systems that invoke agents (messaging platforms, APIs, scheduled tasks)
2. **Preprocessors**: Components that prepare input (called "Providers" in ElizaOS)
3. **Tools**: Functions that agents can call to perform tasks
4. **Postprocessors**: Components that validate or enhance results
5. **Plugins**: Additional components that extend functionality

In practical implementations, these components work together to create resilient, capable agent systems that can address complex enterprise needs.

## **Evaluation: The Critical Component**

Unlike traditional software, AI agents require continuous assessment. Effective evaluation helps identify weaknesses, refine prompt strategies, and improve decision-making. Tools like PromptFoo facilitate structured testing, enabling teams to benchmark and iterate on agent behavior efficiently.

## **The Future of Multi-Agent Systems**

As organizations continue to deploy advanced agent architectures, we can expect to see:

- Deeper integration with existing enterprise systems
- More sophisticated collaboration between specialized agents
- Enhanced security and governance frameworks
- Expansion beyond monitoring to active operational control

Ankr's approach with Moniqa represents an early example of these trends, demonstrating how domain-specific agents can deliver substantial value when properly integrated within multi-agent systems.

## **Final Thoughts**

The evolution from simple agents to sophisticated multi-agent systems represents a fundamental shift in artificial intelligence applications. By distributing cognitive load across specialized agents, organizations can overcome scaling challenges while improving overall system performance.

As these architectures continue to mature, they will reshape how enterprises approach automation, monitoring, and decision support across industries, with monitoring agents like Moniqa serving as just one example of the broader potential of this transformative technology.

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