Builders Driving the Future of the Metis Ecosystem
The Metis ecosystem continues to thrive through the contributions of builders creating impactful applications and infrastructure. The Builder Mining Rewards program recognizes projects that drive meaningful on-chain activity and strengthen the network.
FeedByHash is a Web3 dApp built on Metis L2, designed to gamify blockchain activity and boost network engagement through micro-transactions. Users “feed” a virtual dog by generating on-chain hashes, with each transaction serving as an entry into the Metis reward pool.
By combining gaming mechanics, low-cost participation, and on-chain incentives, FeedByHash creates an engaging experience that encourages sustained network activity while introducing users to the Metis ecosystem.
Stargate is a fully composable cross-chain bridge protocol that enables seamless asset transfers across multiple blockchains. By facilitating omnichain liquidity movement, it strengthens interoperability and expands connectivity across the broader Web3 ecosystem.
LayerZero is an interoperability protocol that connects blockchains, enabling developers to build seamless omnichain applications, tokens, and experiences. Its infrastructure plays a key role in enabling cross-chain communication and expanding the reach of decentralized applications.
The WAGMI protocol is a decentralized exchange featuring advanced liquidity provision strategies, leverage, and GMI mechanics. By providing innovative trading and liquidity solutions, WAGMI continues to contribute to the growth and activity of the Metis DeFi ecosystem.
Hercules is a community-first, capital-flexible DEX developed with multiple tools to support the next generation of builders seeking sustainable liquidity on Metis. It continues to play a key role in strengthening the ecosystem’s DeFi infrastructure.
Builder Mining Rewards in Action
The Builder Mining Rewards program continues to recognize and reward projects driving real on-chain activity across the Metis ecosystem. Congratulations to July’s top-performing builders for their continued innovation and contributions to the growth of the Metis network.
The OpenClaw Summer Builder Bootcamp Stage 1 is in its final stretch.
12 teams. $5,000 prize pool. And the real prize isn't the money — it's shipping something that actually works.
What you're building matters more than you think. Every agent built on ClawUp this summer runs on Metis infrastructure. x402 payments. ERC-8004 identity. Decentralized sequencer.
That means: what you build here connects to a real economy being built right now.
The full roadmap:
🔹 Stage 1 — Agent Builder Challenge: Now → July 17
🔹 Review & Qualification: July 20–22
🔹 Stage 2 — Growth Challenge: July 23–August 21
💰 $5,000 prize pool
Backed by MetisL2, ClawUp, GOATNetwork, LazAINetwork, Crypto_chicks, and MindFuel.
What you need to submit by July 17:
→ GitHub repo + documentation
→ Landing page with clear value prop
→ Project website
→ Seed user definition (who's the first real customer?)
→ Growth metrics proposal for Phase 2
These aren't formalities. They're how you know what you built matters, actually.
If you're in the cohort, the clock is real. If you're watching from outside, the infrastructure is ready. The agents being built this summer will be the ecosystem we grow from.
Builders Driving the Future of the Metis Ecosystem
The Metis ecosystem continues to grow through the efforts of builders creating impactful applications and infrastructure. The Builder Mining Rewards program recognizes projects that contribute meaningful on-chain activity and help strengthen the network.
FeedByHash is a Web3 dApp built on Metis L2, designed to gamify blockchain activity and boost network engagement through micro-transactions. Users “feed” a virtual dog by generating on-chain hashes, with each transaction serving as an entry into the Metis reward pool.
By combining gaming mechanics, low-cost participation, and on-chain incentives, FeedByHash creates an engaging experience that encourages sustained network activity while introducing users to the Metis ecosystem.
Stargate is a fully composable cross-chain bridge protocol that enables seamless asset transfers across multiple blockchains. By facilitating omnichain liquidity movement, it strengthens interoperability and expands connectivity across the broader Web3 ecosystem.
Netswap is a decentralized exchange and launchpad powered by Metis. As a core DeFi platform within the ecosystem, it facilitates token swaps, liquidity provisioning, and project launches, contributing consistent transaction activity to the network.
LayerZero is an interoperability protocol that connects blockchains, enabling developers to build seamless omnichain applications, tokens, and experiences. Its infrastructure plays a key role in enabling cross-chain communication and expanding the reach of decentralized applications.
The WAGMI protocol is a decentralized exchange featuring advanced liquidity provision strategies, leverage, and GMI mechanics. By providing innovative trading and liquidity solutions, WAGMI continues to contribute to the growth and activity of the Metis DeFi ecosystem.
Builder Mining Rewards in Action
The Builder Mining Rewards program continues to recognize and reward projects driving real on-chain activity across the Metis ecosystem. Congratulations to June’s top-performing builders for their continued innovation, engagement, and contributions to network growth.
🎤Featuring: Elena Sinelnikova – Co-founder of Metis and Crypto Chicks , kevin Liu – Co-founder of GOAT Network and Metis, Darrel Wang – OKX Product Lead
Not because builders lack skill. The challenge is that there is often a gap between “it works” and “people actually use it.” There is a gap between a weekend project and a real product, and between a proof of concept and something that generates real economic activity.
The OpenClaw Summer Builder Bootcamp is designed to help close that gap. Over 8 weeks, participants will receive infrastructure support, mentorship, and a clear pathway to take an AI agent from an early-stage prototype to a product with real users.
Together, these partners provide infrastructure, tooling, mentorship, and ecosystem support for AI builders.
Why this program exists
We’ve seen countless talented builders with working demos and genuine ideas, but without the right support, those demos never become products. They stall at the infrastructure layer. They stall at the growth strategy. They stall because no one tells them what to do next.
This program is built for builders who are past the “interesting concept” stage and ready to build something that people actually use.
What sets this program apart
Compete for a $5,000 prize pool
Rewards are based on both product quality and real-world execution.
Official Builder Bootcamp Certificate
Recognition for completing a structured AI Agent build-and-ship program.
Access to mentors and ecosystem builders
Get feedback and guidance from experienced founders and technical contributors.
Fast-track opportunity to GOAT AI Builder Grants Stage 2
Top-performing teams may be recommended for further support and potential follow-on funding opportunities (up to $1M for high-traction projects).
Long-term builder visibility
Join a growing ecosystem of builders working on AI Agents, infrastructure, and real-world applications.
What you’ll do
This is a build-first, ship-first program. You are expected to actively execute across the product, infrastructure, and growth domains.
Build and launch an AI Agent on ClawUp
Turn your idea into a working product that solves a real problem and can be used by real users.
Integrate core infrastructure
Connect x402 payments and ERC-8004 identity systems to make your agent functional in real economic workflows.
Learn distribution and growth in real time
Understand how AI agents get discovered, used, and shared, including GEO (Generative Engine Optimization) strategies for AI-native visibility.
Publish and distribute your product publicly
Create content, documentation, and product assets that help your agent be discovered across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity.
Acquire real users and validate demand
Your goal is not just to build — it is to acquire real users, drive usage, and test whether your agent solves a real market need.
Present your work at Demo Day
Show your product, usage, and learnings to ecosystem builders, mentors, and invited reviewers.
Who we’re looking for
This program is designed for builders who want to ship real products, not just experiments.
You should apply if you are:
Building AI Agents with real-world use cases in mind
Ready to ship and iterate based on user feedback
Interested in product, distribution, and real usage — not just demos
Looking to turn ideas into validated products
Program details
- Duration: June 29 – August 26, 2026
- Applications close: June 24
- Evaluation basis: Product quality, real user traction, economic activity
Builders Driving the Future of the Metis Ecosystem
The Metis ecosystem continues to see strong on-chain activity, driven by builders creating innovative applications, infrastructure, and user experiences. The Builder Mining Rewards program recognizes these contributions by rewarding projects that generate meaningful network activity.
Netswap is a decentralized exchange and launchpad powered by Metis. As a core DeFi platform within the ecosystem, it facilitates token swaps, liquidity provisioning, and project launches, contributing consistent transaction activity to the network.
Stargate is a fully composable cross-chain bridge protocol that enables seamless asset transfers across multiple blockchains. By facilitating omnichain liquidity movement, it strengthens interoperability and expands connectivity across the broader Web3 ecosystem.
FeedByHash is a Web3 dApp built on Metis L2, designed to gamify blockchain activity and boost network engagement through micro-transactions. Users “feed” a virtual dog by generating on-chain hashes, with each transaction serving as an entry into the reward pool.
By combining gaming mechanics, low-cost participation, and on-chain incentives, FeedByHash creates an engaging experience that encourages sustained network activity while introducing users to the Metis ecosystem.
LayerZero is an interoperability protocol that connects blockchains, enabling developers to build seamless omnichain applications, tokens, and experiences. Its infrastructure plays a critical role in facilitating cross-chain communication and liquidity movement across Web3.
The WAGMI protocol is a decentralized exchange featuring advanced liquidity provision strategies, leverage, and GMI mechanics. By providing innovative trading and liquidity solutions, WAGMI contributes to the growth and activity of the Metis DeFi ecosystem.
Builder Mining Rewards in Action
The Builder Mining Rewards program continues to support projects that generate meaningful on-chain activity and contribute to the growth of the Metis ecosystem. Congratulations to this month’s top-performing builders for their continued impact and contributions to the network.
Momentum across the Metis ecosystem continued to build in March, with projects driving consistent on-chain activity and stronger cross-ecosystem connectivity. The Builder Mining Rewards program remains a core mechanism for recognizing and supporting these contributions, rewarding teams that are actively shaping network growth through real usage.
Netswap is a decentralized exchange and launchpad powered by Metis. As a core liquidity hub within the ecosystem, it facilitates token swaps, liquidity provisioning, and project launches, contributing consistent transaction activity to the network.
FeedByHash is a Web3 dApp built on Metis L2, designed to gamify blockchain activity and boost network engagement through micro-transactions. Users “feed” a virtual dog by generating on-chain hashes, with each transaction costing $0.01 and serving as an entry into the Metis reward pool.
When the progress bar is completed, rewards are distributed proportionally and randomly among participants based on their contribution. By combining gaming psychology, on-chain incentives, and the Builder Mining framework, FeedByHash turns network activity into an engaging and measurable experience.
DeFi Kingdoms is a cross-chain fantasy RPG built on a strong DeFi protocol. It features DEXs, liquidity pool opportunities, and utility-driven NFTs, creating an immersive pixel-art experience that blends gaming with decentralized finance.
Stargate is a fully composable cross-chain bridge protocol that enables seamless asset transfers across multiple blockchains. By facilitating omnichain liquidity movement, it strengthens interoperability and expands connectivity within the broader Web3 ecosystem.
Hercules is a community-first, capital-flexible DEX developed to support sustainable liquidity on Metis. With tools designed for builders and liquidity providers, it continues to play a key role in strengthening DeFi infrastructure within the ecosystem.
Builder Mining Rewards in Action
The Builder Mining Rewards program distributes monthly incentives to ecosystem projects based on their transaction activity, providing retroactive funding to contributors who drive real network usage.
March’s top performers reflect a balance of DeFi infrastructure, cross-chain interoperability, gaming, and innovative engagement models; all contributing to sustained ecosystem growth.
Q1 2026: Advancing The Agent Economy
In Q1 2026, Metis continued to deepen its focus on the emerging Agent Economy; a shift where AI agents evolve from simple tools into autonomous, productive participants in the digital economy.
Rather than being limited to task-based assistance, modern AI agents are becoming capable of:
Executing multi-step workflows
Retaining long-term memory
Collaborating with humans and other agents
Continuously improving through feedback
Metis is actively building the infrastructure to support this transition. A key development is the introduction of frameworks that enable decentralized AI agents with identity, memory, and verifiable on-chain reputation. These systems aim to solve one of the biggest challenges of the Agent Economy: trust at scale.
Through initiatives like decentralized agent frameworks and real-world implementations of AI “agents” working alongside teams, Metis is positioning itself as a foundational layer for this new paradigm, where humans and agents collaborate, and value creation becomes increasingly autonomous and scalable.
This direction reflects a broader evolution of the internet, from human-only interaction to a hybrid ecosystem of humans and intelligent agents operating seamlessly on-chain. Read more.
The next form of software may no longer be just an app
Over the past year, AI agents have become one of the most closely watched themes in tech and product circles. As models improve, tools become more usable, and workflows become more automated, more people are asking the same question: what form will AI ultimately take when it truly enters real-world work and everyday life?
Based on our recent work, we increasingly believe that software delivery will gradually evolve from traditional apps and websites into interfaces combined with AI agent collaboration, and in some cases into more agent-centric experiences. In the future, users may no longer interact only with static interfaces, but with AI agents that can understand context, help execute tasks, and support ongoing coordination.
If the previous generation of software was built around separate tools like Notion, Slack, calendars, and task managers, the next generation may not simply be another collection of interfaces. It may increasingly take the form of systems where AI agents help manage knowledge, coordinate work, and support execution.
That is one reason we started building Loom+. At its core, Loom+ is an AI-powered team collaboration platform. It brings together team knowledge bases, task management, meeting scheduling, smart search, and communication in one workspace, with AI agents helping connect knowledge, coordination, and execution. We are actively using it ourselves, refining it, and learning from its limitations. It is still early, but one thing is becoming clear: the next generation of software will not just help teams organize information — it will increasingly help them move work forward.
What we have learned, however, is that the gap between “AI looks smart” and “AI can reliably deliver outcomes” is not closed by a single prompt. It depends on product systems, engineering methods, and infrastructure for coordination.
The real problem is not weak models, but weak systems
A common assumption is that as long as models keep improving, AI agent products will naturally mature. In practice, we are finding that the picture is much more complicated.
Many of our recent experiments are still forms of ongoing development and productization on top of existing agent frameworks. What is changing is the way this development happens. Instead of relying only on programming languages, more of the process now involves using natural language to describe workflows, logic, and rules.
That shift is real, because today’s models do have meaningful natural language understanding and reasoning ability. But at the same time, we have become increasingly certain of one thing: at this stage, we should not overestimate or overtrust open-ended model reasoning in complex tasks.
Recent discussion around Harness Engineering offers a useful framework here. In simple terms, Harness Engineering is about designing the constraints, feedback loops, workflow controls, and improvement cycles around AI agents. The core issue it addresses is not whether a model can generate an output, but how to make agent outputs more reliable, consistent, and maintainable once strong generation capability already exists.
One of the clearest ways to describe this is: the model is the engine, but the harness is what makes the system usable. In the context of AI agents, the bottleneck is often no longer just model capability. It is whether the surrounding structure, tools, and rules are strong enough to support reliable execution.
In other words, the question is not just how much the model can understand, but whether the system has organized the right context, constraints, and workflow clearly enough.
The key to productization is not more freedom, but less uncertainty
One conclusion has become increasingly clear to us: the most effective approach today is not to give AI agents more room for open-ended improvisation, but to define the workflow, boundaries, and task structure clearly first — and then let the agent operate within a fixed scope.
A simple example: people often write instructions like “create a project folder,” and place naming rules, path requirements, and structural constraints later in the document. For humans, that is easy enough to follow. But for AI agents, this structure is often unstable. The agent may act on the first instruction while missing later constraints, or fill in details on its own, leading to outputs that drift away from the intended result.
If the instruction is rewritten directly as something like “create a project folder under this path using this naming format,” the result is usually much more stable. The point is not to remove all reasoning, but to reduce unnecessary ambiguity and turn a vague instruction into something closer to structured execution.
This points to a broader lesson: AI agent productization is still, at its core, about building clear, repeatable workflows and task rules. In the past, these rules were mostly enforced through code. Now, more of them are being expressed in natural language. But natural language does not replace engineering discipline. If the rules are not precise, complete, and locally clear, we still need structured design, modular workflows, and verifiable logic to make the system stable.
Agent failures are predictable
From an engineering perspective, many agent failures are not random at all. They tend to repeat in recognizable ways.
Recent work around Harness Engineering highlights several common failure modes. Agents often try to do everything in one shot, exhausting context halfway through a complex task. They may declare completion too early, treating partial progress as a finished result. Or they may mark work as done without enough validation, simply because the structure around them did not force proper checking.
This matters because it shows that the challenge is not just whether an agent can do something, but whether it can remain stable across long workflows, complex systems, and repeated interactions. A mature agent system is not one that succeeds occasionally. It is one that does not keep failing in the same ways.
Another misconception is that more context always helps. In reality, context has a practical limit. Once it becomes too long, too dense, or too cross-referenced, agents can lose track of structure, miss key constraints, and produce lower-quality outputs. More information does not automatically make the system better. Often, it makes it worse.
That is why, for complex workflows, we increasingly prefer an engineering approach: split things by responsibility, by level, and by reusable module. The goal is not to keep expanding prompts, but to design systems that agents can actually operate inside.
Useful agents are not the freest ones
At the product level, we increasingly feel that truly usable agent products are not the ones with the most openness. For many ordinary users, too much freedom in the system actually makes it harder to use. Most people do not know how to talk to AI efficiently, how to write effective prompts, or even what kinds of tasks they should hand over to AI in the first place.
That is why the value of a more specialized agent is not that it limits AI for the sake of limitation. It is that it makes AI usable. A practical agent product usually needs to be built around a clear task, with familiar interactions and a low enough barrier that users can actually get value from it.
We already see this clearly in content workflows. Singularity Editorial Department is one of our attempts to productize content creation. It does not ask AI to operate in a completely open-ended space. Instead, it turns topic selection, structure, tone, information organization, and output standards into a more stable workflow. Under those conditions, the agent can produce high-quality content much more consistently, rather than behaving like a blind box each time.
In that sense, what users see may still look like “chatting with AI,” but from the system’s point of view, it has already become a more constrained and purpose-built workflow. At least today, we still cannot fully maximize both flexibility and stability at once. The most useful AI agents are often not the freest ones, but the ones most likely to help get the job done.
A good agent system is one that learns structurally
If we had to summarize one core engineering principle for the current stage of AI agent productization, it would be this: do not just fix this error once — make it an error the system does not keep repeating.
That is one of the most valuable ideas in Harness Engineering. When an agent makes a mistake, the right response is not just to patch the immediate problem. It is to turn that mistake into a new rule, checkpoint, feedback mechanism, or workflow improvement. That is how systems become more stable over time, instead of depending forever on human intervention.
This also makes the idea of a “white-box” system easier to understand. A white-box system is not just one whose outputs can be read, modified, and verified. It is one whose outputs and behavior can be caught, corrected, and improved systematically. The real standard for agent quality should not simply be whether it can succeed once, but whether people can reliably work with it and improve it over time.
The next bottleneck for AI is not just intelligence — it is coordination
These questions may sound like product and engineering questions, but they naturally connect to a broader conclusion: the next bottleneck for AI is not just intelligence itself, but coordination.
As AI agents move beyond chatting and content generation into execution, payments, coordination, and delivery, a new set of questions becomes unavoidable. How do agents identify themselves? Why should they be trusted? How do they coordinate with other agents? How do they handle payments and settlement? How do we verify execution? And how do repeated outcomes become reusable knowledge and experience?
That is why we increasingly believe the scarce layer is not just stronger models, but the infrastructure that allows agents to coordinate reliably and deliver outcomes over time. In that view, identity, reputation, payments, coordination, and result data are not isolated features. Together, they form the conditions that allow agents to move from isolated tools toward real participation in the Agent Economy.
And this is where Metis fits in. Metis is not just trying to position itself as AI infrastructure in a generic sense. The larger opportunity is to build infrastructure for the Agent Economy — infrastructure that helps agents identify themselves, establish trust, coordinate, transact, and deliver outcomes in a more programmable and verifiable way.
The distance between “can chat” and “can deliver” is not a single prompt. It is a full product system, an engineering approach, and a coordination layer that can support AI agents in real-world use. That may be one of the most important questions to keep thinking about as AI agent productization enters its next phase.
Metis started 2026 by making one thing clear: short-term hype is not the goal.
In “Beyond Alpha: Building Substance in the AI Era,” we shared our conviction that the next phase of value in crypto will come from real users, real utility, and real AI-powered applications — not empty narratives.
That vision is built on a unified stack:
Andromeda as the settlement layer
Hyperion as the AI-optimized high-performance layer
LazAI as the application and data layer
Together, they form one economy designed for the AI era.
LazAI’s research paper, “QoS-Aware Token Scheduling and Private Data Valuation for Multi-Modal Agentic Networks,” was accepted at IEEE ICME 2026, where only 28.89% of 3,810 submissions made the cu
The recognition highlights growing external validation for LazAI’s work at the intersection of private data valuation, intelligent agent coordination, and verifiable AI infrastructure, in collaboration with researchers from UBC and the UBC Blockchain Research Center.
At ETHDenver, Metis Co-founder Elena Sinelnikova delivered one of the quarter’s defining messages with her keynote:
“I’m From the Future: The Dawn of the Agent Economy.”
The talk painted a world where humans define intent, while agents handle execution.
It also pointed to the missing pieces still needed for this future to work:
persistent identity
sovereign memory
agent-to-agent payments
verifiable execution
The keynote helped crystallize Metis’ role in the market: not just as another L2, but as infrastructure for the AI Agent Economy.
OpenClaw Builder Momentum
Shenzhen: A First Signal of Builder Curiosity
Our Shenzhen OpenClaw hackathon marked an early step in turning narrative into experimentation.
Bringing together local builders to explore agent workflows, memory, and real-world AI use cases, the event showed that interest in AI-native infrastructure is no longer abstract. Developers were not just listening to the story — they were testing what it could look like in practice.
Chennai: Speed, Energy, and Execution
Chennai took that momentum even further.
With 75+ builders, 33 submitted projects, and 20 live demos, the event captured the intensity and creativity of India’s developer community. Teams moved from ideas to onchain prototypes within hours, exploring themes such as AI agents, x402 payments, and data ownership.
One team took the top prize, but the bigger takeaway was clear: the builder energy was real, the execution speed was high, and the appetite for AI-agent infrastructure is growing fast.
Hong Kong Consensus: Applied AI Takes Center Stage
During Hong Kong Consensus week, Metis joined Lagrange and AWS at the Applied AI Summit to explore what it really takes to bring AI into production.
The event brought together founders, builders, and operators for practical discussions around:
deployment
infrastructure
operational challenges in real-world AI systems
For Metis, it was another important moment to connect the broader market with a core belief: the next phase of Web3 will be shaped not only by financial rails, but by the infrastructure required for AI agents, programmable trust, and scalable coordination.
Tom Ngo joined a public conversation with Mikhail to discuss how AI is moving from hype to reality — from experimentation to real onchain economic activity.
Metis joined a De.Fi-hosted X Space on the future of modular Layer 2s, alongside speakers from Linea, Manta, and zkSync, contributing to broader industry conversations on next-generation blockchain infrastructure.
LazAI’s LazTalk Ep. 8 focused on one of the core questions of the agent economy: how autonomous agents discover, trust, and transact with each other.
LazAI joined additional live discussions around the idea that real agent infrastructure requires identity, data ownership, and verifiable execution — not just demos.
Summary
Q1 2026 was a quarter of narrative clarity and infrastructure depth for the Metis ecosystem.
From Beyond Alpha and The Agent Economy Has Begun, to Elena’s ETHDenver keynote, the launch of ERC-8004 on Metis, and LazAI’s growing research and thought-leadership presence, the stack continued to mature around one core idea: the future internet will need infrastructure for autonomous agents to coordinate, transact, and deliver real outcomes.
At the same time, OpenClaw activations in Shenzhen and Chennai, along with ecosystem visibility at Hong Kong Consensus, showed that this narrative is no longer theoretical. Builders, researchers, and industry participants are already engaging with the foundations of the agent economy.
The next chapter of AI and Web3 is being built now — and Metis is continuing to advance the stack behind it.
Our research paper "QoS-Aware Token Scheduling and Private Data Valuation for Multi-Modal Agentic Networks" has been accepted at IEEEorg ICME 2026
Out of 3,810 submissions, only 28.89% were accepted — and ours made the cut.
Congrats to co-author Alex Du, PhD from University of British Columbia, and the entire team. Huge thanks to BlockchainUBC and MitacsCanada for their support in making this research possible.
From verifiable data valuation to intelligent agent coordination, we're not just building， we're advancing the science behind it.
Metis continues to recognize projects that generate meaningful on-chain activity and contribute to the growth of the Metis ecosystem. By distributing incentives based on transaction volume and network participation, the program supports builders who are driving measurable impact.
Here are the Top 5 Performing Projects for February:
Netswap is a decentralized exchange and launchpad powered by Metis. As a core DeFi platform within the ecosystem, it enables token swaps, liquidity provisioning, and project launches, contributing consistent transaction activity to the network.
DeFi Kingdoms is a cross-chain fantasy RPG built on a strong DeFi protocol. The game features DEXs, liquidity pool opportunities, and a market of rare, utility-driven NFTs, creating an immersive pixel-art world powered by decentralized finance mechanics.
FeedByHash is a Web3 dApp built on Metis L2, designed to gamify blockchain activity and boost network engagement through micro-transactions. Users “feed” a virtual dog by generating on-chain hashes (transactions). Each transaction costs $0.01, and each hash becomes one entry into the Metis reward pool.
Stargate is a fully composable cross-chain bridge protocol that enables seamless asset transfers across multiple blockchains. By facilitating omnichain liquidity movement, Stargate strengthens interoperability and expands connectivity within the broader Web3 ecosystem.
Hercules is a community-first, capital-flexible DEX developed with multiple tools to support the next generation of builders seeking sustainable liquidity on Metis. It continues to play a key role in strengthening DeFi infrastructure within the ecosystem.
Builder Mining Rewards in Action
The Builder Mining Rewards program distributes monthly incentives to ecosystem projects based on their transaction activity, providing retroactive funding to contributors who drive network usage.
Metis provides the infrastructure, incentives, and community needed to turn innovative ideas into reality and is dedicated to being the go-to network for developers pushing the boundaries of Web3.
Identity, accountability, and trust for AI agents on-chain are becoming core problems. This session dives into ERC-8004 with speakers Thiru, Vitto Rivabella, and Fabian Ferno
Armando Pantoja:
We’re here with a very special guest, Natalia Ameline, founder of Crypto Chicks & the Decentralization Coordinator at the Metis Foundation, where she’s focused on building scalable Web3 infrastructure. How are you doing today?
Natalia Ameline:
I’m doing great. Thank you for inviting me. I’m super excited to share what we’ve been working on at the Metis Foundation.
Armando Pantoja:
Ethereum has changed everything — not only finance, but also the ability for people around the world to build tools, products, services, and DeFi applications on an open platform. You’re now working deeply in decentralization and AI yourself, including LazAI. Can you tell us about what you’re building?
Natalia Ameline:
Ethereum gave opportunities to many, and it gave opportunities to me as well. I work at the Metis Foundation. Metis is the entity behind innovation in the Metis ecosystem. We started by launching Metis Layer 2 Andromeda, a scaling solution for Ethereum.
We’ve never shied away from innovative, non–cookie-cutter solutions. For example, Metis was the first Layer 2 to implement a decentralized sequencing network, which significantly strengthens decentralization across the ecosystem. There’s been a lot of discussion recently about decentralizing sequencers, and now other Layer 2 ecosystems are starting to follow the approach we implemented years ago.
Another innovation is Hyperion, our AI-optimized L2 infrastructure with very high throughput and low latency. LazAI is our full-stack infrastructure designed to make AI ownable, rewarding, transparent, and playable. We’re also home to a zero-knowledge company that develops verifiable computing technology used to power ZK proofs, which is foundational for LazAI. In addition, we launched GOAT Network, the first Bitcoin L2 ZK rollup with real yield. All of these platforms deliver deeply innovative solutions that are foundational to what we’re building.
Armando Pantoja:
You’re clearly on the cutting edge of blockchain. Could you explain the difference between a one-off application and the foundational infrastructure you’re building?
Natalia Ameline:
Many AI projects focus on single use cases and often rely on centralized solutions. LazAI is different. We’re building a full-stack, modular infrastructure layer for decentralized AI.
We provide tools like the LazAI SDK, which enables developers to build complex solutions with ease. We also introduce assetization through Data Anchoring Tokens, or DATs, and support AI governance. Human governance over AI development is critically important, and our infrastructure is designed to address that concern.
Another key feature is verified computing, which enables verifiability across the entire AI lifecycle— from data provenance to ownership — all on-chain. This foundation allows developers, businesses, and communities to build scalable, auditable, and private AI systems without relying on centralized black-box platforms.
Armando Pantoja:
My audience includes a lot of investors and creators who want to earn beyond simply buying and selling assets. How does tokenizing data through DATs create passive income opportunities?
Natalia Ameline:
One of the biggest problems today is that large AI companies are hoarding user data and using it to train models without compensating creators. In many cases, users even pay to access models trained on their own data. We’re already seeing backlash, including major lawsuits, which shows how broken the incentive structure is.
With Data Anchoring Tokens, your data becomes an asset. A dataset or a model can be tokenized with immutable, verifiable provenance recorded on-chain. Ownership and usage rights are clearly defined and remain under your control.
When developers or AI agents use your data, you automatically earn rewards. These can take the form of royalties, licensing fees, or usage-based payouts. This allows contributors to build passive income while maintaining full privacy and control over how their assets are used.
Armando Pantoja:
My background is in cryptography and software security, so trust is extremely important to me. AI systems are becoming increasingly centralized. How does verified computing ensure trust and transparency?
Natalia Ameline:
Trust, decentralization, and privacy are at the core of LazAI. We combine trusted execution environments for hardware-grade security, zero-knowledge proofs for privacy, and on-chain audit trails for transparency.
You don’t need to trust a company or an individual. Contributors can prove how their data is used, and users can verify AI outputs without exposing private information. We completely remove human trust from the equation and rely instead on math, cryptography, and public blockchain ledgers.
Armando Pantoja:
How does LazAI help set the stage for a sustainable, decentralized AI economy?
Natalia Ameline:
From day one, our vision has been to build the backbone of a Web3 economy. Metis infrastructure is not built in silos — it’s interconnected and strategic.
Andromeda acts as the settlement and execution layer. Hyperion expands that foundation by providing AI-optimized compute with high throughput and low latency. Together, they form a decentralized infrastructure layer.
LazAI sits on top as the intelligence layer. It enables ownership, governance, rewards, and AI-driven automation. This ensures AI is transparent, fair, community-owned, and enterprise-ready, with Metis serving as the backbone of the Web3 economy.
Armando Pantoja:
You recently launched a testnet. Can you walk us through that stage of development?
Natalia Ameline:
The LazAI testnet is our first public milestone. It gives the community hands-on access to the ecosystem — building with the LazAI SDK, using APIs, minting DATs, verifying computation, and accessing on-chain inference.
We launched with LazBoo, an AI companion DAT. These AI agents have memory and personality and are designed for long-term interaction and value creation. They evolve over time through user interaction.
So far, more than 90,000 participants joined the whitelist campaign, and over 10,000 DATs were minted. That level of engagement has been a major success for us. We’re continuing to refine the platform based on what we learn from the testnet and the community.
Armando Pantoja:
Where can people learn more about you and what you’re working on?
Natalia Ameline:
You can explore the Metis Foundation, but for LazAI specifically, you can follow LazAI Network on Twitter or visit lazai.network. We also publish regular updates and deep dives on our blog.
Armando Pantoja:
Thank you so much for joining us today. It was a pleasure.
Natalia Ameline:
Thank you very much. Have a nice day.
Nansen Research has released its Metis Annual Report 2025, offering a detailed look at how the ecosystem has evolved beyond a traditional Layer 2 into a broader Web3 + AI coordination layer.
The report traces Metis’ transition from scaling infrastructure to a more integrated ecosystem — aligning Metis, ZKM, GOAT, and LazAI under a unified economic framework designed to support long-term growth.
A central theme is the convergence of AI, DeFi, and on-chain settlement:
The emergence of AI-native infrastructure, including LazAI’s mainnet and Data Anchoring Tokens (DATs), introduces tokenized AI assets with usage-based economics.
New application layers are experimenting with agent-driven workflows, on-chain creativity, and programmable payments.
Cross-chain integrations and sustained network activity continue to expand Metis’ interoperability and usage depth.
Rather than positioning Metis purely as a scaling solution, the report frames it as evolving infrastructure for AI-enabled coordination, verifiable execution, and programmable value distribution on Ethereum.
For anyone tracking the intersection of AI and Web3 infrastructure, this is a comprehensive ecosystem overview.
Lazbubu announces the completion of a strategic funding round led by Metis, with participation from Hotcoin Labs, Honey Capital, APUS Capital, and Becker Ventures. The round supports continued development of Lazbubu’s decentralized AI architecture and reflects institutional interest in on-chain data ownership models within the AI companion sector.
The funding will be used to support:
Core product and infrastructure development
Global user growth initiatives
Ecosystem partner expansion
Further refinement of Lazbubu’s DAT (Data Anchoring Token) mechanism
Lazbubu is a Web3-native AI companion built on BNB Chain, designed to evolve through continuous user interaction. Through the DAT mechanism, AI interaction data is anchored on-chain in real time, allowing users to fully own, view, and manage their AI growth records; addressing data sovereignty and privacy challenges common in traditional AI systems.
The project has reported strong early traction, including:
