Metis Foundation 🌿

Imagine a world where humans and AI don’t just coexist - they collaborate seamlessly, creating a new kind of digital economy. This is the vision behind Metis Foundation, which is building an AI-native Web3 ecosystem that bridges the gap between people and autonomous agents. At the core of this ecosystem lies @MetisL2 🌿, the foundation that makes human-AI interaction intuitive and efficient. 🧵👇

AgentKit is the developer interface for giving agents economic capabilities - including x402 payments & ERC-8004 identity - across multiple chains. Install it into an existing app with: "npm install @goatnetwork/agentkit" Or start from a template with: "npm create goat-agent"

Metis thesis: AI value capture belongs to systems that can execute, verify, and settle with transparency. Hyperion performance + decentralized sequencing is not branding. It is the infrastructure requirement for AI workflows at scale.

LazAI thesis: data sovereignty plus programmable accountability is the base layer of the agent economy. Without value return rails, AI scales workload, not fairness. With DAT and verified execution, contribution can finally map to reward.

In high-stakes agent workflows, the key question is not who decides. It is whether execution is verifiable, attributable, and enforceable across participants. Where is your current stack still non-verifiable?

Why build with GOAT Network? Bitcoin-secured settlement, EVM-compatible tooling, and infrastructure for crosschain agent payments, identity, reputation, and other onchain actions. Plus a $1M-backed grants program to help turn your agent ideas into working products: goat.network/builder-program

Builders should ask three hard questions before shipping: • What execution layer does your agent system run on? • Is sequencing transparent and verifiable via decentralized ordering? • Who owns the data and control rights across the workflow? If these answers are weak, your AI product is operationally fragile.

GOAT Network is a Bitcoin L2, so how can it be compatible with Ethereum standards like ERC-20 and ERC-8004? GOAT Network is built to settle to Bitcoin, but its execution environment is Type-1 zkEVM and therefore can run Ethereum-compatible application logic. That means developers can write and deploy smart contracts using the same standards, tooling, and interfaces they already know from Ethereum, while the network itself is designed around Bitcoin-secured settlement. The stack can be understood in layers: • Bitcoin is the settlement foundation: the base layer for security, exit rights, and final settlement. • GOAT Network is the execution layer: where applications, agents, payments, contracts, and user interactions happen. Because it supports an Ethereum-compatible environment, GOAT Network can use Ethereum standards without settling to Ethereum. • ERC standards are reusable application formats. ERC-20 defines how tokens behave. ERC-8004 defines how agents can register, be discovered, and build reputation. These standards can be used anywhere the execution layer supports them. That is what makes the design so powerful: Bitcoin provides the neutral settlement base, while EVM compatibility gives developers access to the mature standards and tooling needed to build real applications.

You missed one important thing.😎

Enterprise AI does not fail because teams lack tools. It fails because workflows hit weak execution foundations. Metis Hyperion is built to fill this gap: high-performance execution that can support real workflow rewrites, not isolated copilots.

Do you want to build AI agents that make you money? Of course you do. The GOAT AI Builder Grants Program includes a $1M pool for builders who can turn a strong idea into a real, working agent product. Be a front-runner in this new economic paradigm 👇 goat.network/news/goat-ai-b…

Most enterprise AI debt persists because process redesign lacks verifiable data and enforceable accountability. LazAI’s DAT provenance layer, combined with QBFT execution verification, turns workflow claims into auditable facts.

AI is unbundling jobs. Repetitive tasks → commoditized. Judgment & coordination → premium. Own the execution stack, not just the model. WEF estimates 92M jobs displaced, 78M net new by 2030. Growth ≠ fair distribution.

Over 300 people signed up so far for our next in-person hackathon in Toronto with @MetisL2 @GOATNetwork @crypto_chicks @TorontoMet @MindFuelca @ClawUpAI @openclaw. 🚀🚀🚀 Come and build your decentralized AI agents with us on May 26 luma.com/2bntw4vd

AI agents are becoming economic actors. The real labor question is not adaptation, it is ownership. If data contributors cannot claim, track, and monetize their contribution, AI productivity becomes value extraction.

The benchmark is shifting， from “how human-like the output is” to “whether contribution is provable and payouts are programmable.” That’s not rhetoric; it’s a shift in monetization boundaries.

What kills agent products first in production? A) unstable settlement B) cost volatility C) fragmented execution path D) slow trust formation Pick one + one-line defense.

GOAT Network supports clear, technology-neutral digital asset regulation that lets builders create Bitcoin-secured applications while protecting users, self-custody, and open-source infrastructure. The CLARITY Act is a meaningful step toward replacing regulatory uncertainty with rules that responsible teams can actually follow. @GOATNetwork

Forward Deployed Engineers are bridging AI models to real business outcomes. But who owns the data and value they generate? Every deployment is a contribution. Untracked, it's free labor at scale.LazAI turns every forward deployed workflow into a verifiable data asset. Deploy, own, earn.

The gap between "can chat" and "can deliver" isn't a prompt. It's a coordination problem. AI agents don't just need smarter models. They need identity, trust, payments, and verifiable execution infrastructure. That's the layer we're building at Metis. Read the full piece →metis.io/blog/from-can-…