WEEX Labs: The Lobster Craze, What Can Agentic Economy Bring to Web3?

marsbitPublicado em 2026-03-18Última atualização em 2026-03-18

Resumo

WEEX Labs: The Rise of OpenClaw and What Agentic Economy Brings to Web3 NVIDIA CEO Jensen Huang recently praised OpenClaw as the "largest, most popular, and most successful open-source project in human history." This AI agent, developed by a former Apple engineer, gained 320,000 GitHub stars in just three months, surpassing Linux and React. Its logo resembles a lobster claw, hence the nickname "Lobster" in Chinese communities. Unlike traditional AI chatbots like ChatGPT or Claude, which primarily respond to queries, OpenClaw represents a shift towards autonomous execution. It can take over operating systems, autonomously use browsers, code executors, APIs, and iMessage, planning and performing tasks until completion. Its official skill marketplace, ClawHub, already offers over 27,000 skills, expanding its capabilities. This development signals the beginning of the Agentic Economy, where AI evolves from conversational tools to proactive doers. Web3 is identified as the ideal ecosystem for this growth due to its native compatibility with autonomous, code-driven interactions. Key integrations include: - The x402 protocol enabling autonomous payments and model switching. - ERC-8004 providing portable reputation and identity. - ClawPay, ClawCredit, and ClawRouter facilitating private payments, native credit, and routing. - Stablecoins like USDT and USDC serving as 24/7 banking for agents. Notable projects leveraging this synergy include KITE (a PoAI L1 blockchain for agents), ...

Goodbye Agent, Hello OpenClaw

"It is now the largest, most popular, and most successful open-source project in human history. This is absolutely the next ChatGPT."

This is not the rant of a geek, but the evaluation of OpenClaw by NVIDIA CEO Jensen Huang in an interview this past Tuesday.

This open-source AI Agent, released by a former Apple developer, saw its GitHub stars surge to 320,000 within three months, surpassing Linux and React. Because its logo resembles a lobster claw, the Chinese community directly calls it "Lobster".

But the craze around Lobster is essentially not another AI tool hype; it is the prelude to the Agentic Economy—a critical turning point where AI moves from "talking" to "doing".

From Chat Assistants to Digital Employees, This Time It's Different

Over the past two years, the term "AI Agent" has been repeatedly mentioned but always remained in PowerPoint presentations. It wasn't until the emergence of OpenClaw that this stalemate was truly broken.

Its core difference lies in "execution" rather than "dialogue".

Traditional products like ChatGPT and Claude are essentially tools for answering questions—you ask, it answers, and the next step is still up to you. The logic of the new generation of Agents represented by OpenClaw is completely different: OpenClaw is authorized to take over the operating system, can autonomously call browsers, code executors, APIs, iMessage, etc., and autonomously plans, executes, and corrects based on goals until the task is completed.

Of course, this fully managed approach comes with inherent risks, but that's a topic for later.

Many compare this moment to the ChatGPT moment of 2022, but the author believes a more accurate analogy might be that distant afternoon many years ago when Steve Jobs unveiled the iPhone.

Innovation has not stopped. OpenClaw's official skill market, ClawHub, currently offers over 27,000 Skills for various AI Agents to call for free—this digital employee can do more and more things.

Looking further ahead, the popularity of OpenClaw is not just another simple AI tool frenzy but the prelude to the Agentic Economy, and Web3 is naturally its best soil.

Why is Web3 the Most Natural Economic Carrier for AI Agents?

On the surface, this "Lobster" is just a somewhat intelligent executor: automatically checking emails, booking tickets, managing files, and even cross-platform posting. But digging deeper, it is precisely the true引爆点 (ignition point) of the Agentic Economy—and Web3 is the most matching "ocean" for this lobster to crawl ashore.

The integration of blockchain and "Lobster" has natural advantages for effect amplification:

The x402 protocol allows Agents to use a single wallet to autonomously pay fees, switch AI model providers, without manual review;

The ERC-8004 protocol endows Agents with a portable reputation system and legal identity;

Clawpay, ClawCredit, ClawRouter enable private payments, native credit, and autonomous routing;

Stablecoins (USDT/USDC) become the Agent's "24/7 bank", perfectly matching the settlement needs driven by code.

In summary, the automatic execution of smart contracts, permissionless on-chain interactions, and instant global settlement of stablecoins—these features can greatly compensate for the bottlenecks of traditional AI Agents in payment closure, identity reputation, and contract execution.

More innovative scenarios are on the way:

Circle's open-source Circle Skills already allow AI Agents to directly generate USDC payments, cross-chain transfers, and smart contract logic;

SlowMist's MistTrack Skills provide Agents with on-chain AML risk analysis capabilities, enabling automatic security checks before transfers;

RootData has encapsulated thousands of crypto project databases, financing data, token economics, social activity, etc., into a Skill, increasing content creation efficiency by 10 times.

Therefore, we have reason to believe that the craze of OpenClaw is just the prelude. When integrated into Web3, the Agentic Economy will unleash astonishing potential.

Agentic Concept Projects in the Spotlight

KITE

KiteAI is an Agent-specific PoAI L1 blockchain, deeply synergistic with the OpenClaw ecosystem: it supports OpenClaw developer activities and allows Agents to autonomously pay for computing resources/API calls.

Currently, KiteAI has joined the Agentic AI Foundation (in collaboration with OpenAI, Google, etc.) and is an important infrastructure for the Agentic Economy.

https://x.com/GoKiteAI/status/2024738751155716600

PIEVERSE

The on-chain payment protocol Pieverse recently launched Purr-Fect Claw, transforming OpenClaw into a fully on-chain tool. Users can deploy Agents directly within Web2 applications like Line, Kakao, WhatsApp, etc., to achieve gasless on-chain transactions and operations.

https://x.com/pieverse_io/status/2033791178156757094

GPS

GoPlus Security launched SafuSkill—a security-first Skills market based on BNB Chain, integrating a skill market, automatic security scanning engine, and developer tools to help users filter safe AI Agent Skills.

https://x.com/GoPlusSecurity/status/2032038367266009141?s=20

Lobster

This is not an AI Agent, but a Chinese Meme coin for OpenClaw. Like many同名 (same-name) Meme coins that蹭热点 (ride the hype) of hot events, "Lobster" has also been speculated on due to OpenClaw's breakout popularity.

https://x.com/WEEX_Official/status/2031680807396601872

CLAWD

"clawd.atg.eth" is a self-hosted personal AI assistant deployed by Ethereum developer Austin Griffith based on the open-source clawd.bot. The Agent can independently write, test, and deploy dApps to the Ethereum/Base mainnet and has already produced 14+ production-level applications (such as the ClawFomo game, PFP prediction market, Incinerator burning mechanism).

KELLYCLAUDE

KellyClaude is a personal AI executive assistant created by Austen Allred, running on the Claude model. It can proactively manage schedules, emails, travel, and other tasks and actively shares experiences in Agent communities like Moltbook.

CLUDE

Clude.io focuses on an independent memory layer,剥离 (stripping) memory from the model to achieve a persistent, private, and cross-model portable "brain-like" system, perfectly addressing the pain points of Agent memory and privacy sovereignty.

Final Thoughts

In 2023, the arrival of ChatGPT popularized the AI data sector represented by Fetch.ai (FET), SingularityNET (AGIX), and Ocean Protocol (OCEAN), as well as the early AI+DePIN thematic sector represented by Render (RNDR), Akash (AKT), and io.net (IO);

At the end of 2024, TURBO, GOAT, and Fartcoin triggered an AI Meme狂欢 (carnival), shifting AI from utility to culture and speculation;

In 2025, market focus turned to AI agents as economic entities. Bittensor (TAO), The Graph (GRT), etc., shifted to support AI agent data queries and autonomous transactions, while projects like SkyAI emphasized multi-agent collaboration;

Now, OpenClaw is starting to further push Agents to truly execute 7×24 trading, collaboration, and entrepreneurship, feeding back massive on-chain (on-chain) traffic and new DeFi narratives. This marks our leap into the Agentic era.

The "Lobster" has entered the water, and the vast "ocean" of Web3 awaits it.

Is everyone ready?

Perguntas relacionadas

QWhat is OpenClaw and why is it considered a significant development in the AI space?

AOpenClaw is an open-source AI Agent that has rapidly gained popularity, with its GitHub stars surging to 320,000 in three months, surpassing Linux and React. It is significant because it represents a shift from AI as a conversational tool to an execution-focused agent, capable of autonomously performing tasks by接管 operating systems, calling browsers, code executors, APIs, and more, marking a key turning point in the Agentic economy.

QHow does Web3 serve as a natural economic carrier for AI Agents like OpenClaw?

AWeb3 is the ideal economic载体 for AI Agents due to its blockchain features: protocols like x402 enable autonomous payments, ERC-8004 provides portable reputation and identity, and tools like Clawpay and stablecoins (e.g., USDT/USDC) offer 24/7 banking for code-driven settlements. These elements address traditional AI Agent bottlenecks in payment, identity, and contract execution.

QWhat are some examples of Web3 innovations integrating with OpenClaw to enhance AI Agent capabilities?

AExamples include Circle's开源 Circle Skills allowing AI Agents to generate USDC payments and handle cross-chain transfers, SlowMist's MistTrack Skills for on-chain AML risk analysis, and RootData's Skill that encapsulates crypto project databases to boost content creation efficiency by 10 times.

QName a few Agentic concept projects mentioned in the article and their roles in the ecosystem.

AKey projects include KITE (a PoAI L1 blockchain for Agent resources), PIEVERSE (enabling gasless on-chain transactions via OpenClaw in Web2 apps), GPS's SafuSkill (a security-focused Skills market on BNB Chain), and CLAWD (a self-hosted AI assistant for deploying dApps on Ethereum/Base).

QHow has the AI narrative evolved in the crypto space from 2023 to the present, according to the article?

AIn 2023, ChatGPT spurred growth in AI data板块 (e.g., FET, AGIX) and AI+DePIN themes (e.g., RNDR, AKT). By late 2024, AI Meme coins like TURBO gained traction. In 2025, focus shifted to AI agents as economic entities (e.g., TAO, GMT). Now, OpenClaw drives Agentic execution, enabling 24/7 trading and collaboration, marking the transition to the Agentic era.

Leituras Relacionadas

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHá 3m

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHá 3m

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHá 4m

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHá 4m

Trading

Spot
活动图片