AI Agents & Web3 Agent Ecosystem

At the Autoresearch Hackathon hosted by Paradigm, Ryan Li used AI to complete the problem-solving process and ultimately won the championship. He used multiple AI agents to automate research, generated more than 1,000 strategies, and successfully created an approximately 900-line Python market-making algorithm, demonstrating AI’s advantages in problem-solving. The competition emphasized AI’s exploration and decision-making capabilities, showing that it can serve as a core execution unit.

U.S. well-known angel investor Jason Calacanis expressed optimism about Bittensor and its subnet project Ridges AI on the All-In Podcast, saying that this open-source AI assistant reached about 80% of Claude 4’s performance within 45 days, and highlighting the innovative advantages of decentralization and incentive mechanisms. He also founded the Stillcore Capital fund to focus on investing in the Bittensor ecosystem.

Y Combinator CEO Garry Tan open-sourced the AI knowledge system GBrain, aiming to solve memory problems for AI assistants. GBrain uses a continuous “read → respond → write” loop, enabling AI to accumulate knowledge and deliver more personalized services. Its unique knowledge storage format and automated integration features can effectively manage information from a variety of data sources, and continue learning with each interaction. This reflects the venture capital industry’s emphasis on and demand for AI agent ecosystems.

Qitmeer Network has partnered with Kuvi AI to democratize hedge fund-level tools for everyday users through the Agentic Finance Operating System. This collaboration aims to enhance accessibility, allowing individual investors to manage capital with institutional sophistication within the DeFi landscape.

Ramp Labs research output “Latent Briefing” achieves efficient memory sharing across multi-agent systems by compressing the LLM KV cache, reducing Token consumption and improving accuracy. In LongBench v2 testing, this approach successfully reduced Worker model Token consumption by 65% and improved overall accuracy by about 3 percentage points, with compression taking only 1.7 seconds. This technology performs exceptionally well across different document scenarios.

The article discusses the Top 10 AI Agent Projects in cryptocurrency based on social activity, revealing Chainlink ($LINK) as the leader. It highlights engagement and interaction metrics for various projects, indicating strong interest and demand in the market.

In brief Nunchuk released two open-source tools designed to let AI agents interact with Bitcoin wallets under strict limits. The system uses shared wallets and approval policies so agents cannot spend funds beyond defined rules. The tools aim to support automated financial tasks while

In 2026, a new consensus emerged in the AI industry: what determines whether an AI product is good or bad is no longer the model itself, but the layer around the model called “harness.” As the underlying models used by Claude Code, Cursor, and OpenClaw grow increasingly similar, what truly creates a product gap is the design of the harness. Martin Fowler’s technical blog, Anthropic product lead trq212, and Andrej Karpathy’s recent remarks all point in the same direction: the next battleground for AI is

Anthropic has launched Claude Managed Agents, an end-to-end managed AI agent development platform that streamlines enterprise automation workflows and claims it can speed up product output by 10x. The platform includes a security-first infrastructure, supports long-running execution and multi-agent coordination, and helps developers focus more on core business needs. Notion has already been an early adopter of this service, improving workplace efficiency and signaling intensifying competition in the enterprise AI market.

Anthropic has launched Claude Managed Agents, providing a fully managed AI agent development platform that simplifies enterprise automation workflows and claims it can accelerate product production by ten times. The platform includes a secure infrastructure, supports long-running execution and multi-agent coordination, and allows developers to focus more on core business operations. Notion has already been an early adopter of this service, improving work efficiency and showing that competition in the enterprise AI market is intensifying.

April 10, the China Artificial Intelligence Industry Development Alliance held its plenary meeting in Wuhan, emphasizing that artificial intelligence is entering the era of intelligent-native systems, focusing on breakthroughs in model capabilities, the rise of agent frameworks, and the activation of economic growth and security risks through large-scale applications. The alliance will focus on technological innovation and safety governance.

Anthropic has launched Claude Managed Agents, providing a fully managed AI agent development platform that simplifies enterprise automation workflows and claims it can speed up product production by ten times. The platform includes a security foundation, supports long-running execution and multi-agent coordination, and helps developers focus more on core business work. Notion has already been the first to apply this service, improving work efficiency and showing that competition in the enterprise AI market is intensifying.

Gate News message: During the 17th plenary session of the China Artificial Intelligence Industry Development Alliance on April 10, the Security Governance Committee of the China Artificial Intelligence Industry Development Alliance officially released the 《OpenClaw Class Intelligent Agent Deployment Risk Management Guidelines》. The guidelines focus on enterprises’ pain points in risk prevention and control during the process of technical implementation, and propose an overall security deployment framework and self-check standards covering the entire lifecycle from deployment, to use, to decommissioning. It aims to help intelligent agents move from “able to deploy” to “secure deployment, standardized use, and ongoing governance,” providing practical guidance for enterprises to carry out technical deployments in a compliant and standardized manner.

Cardano's founder, Charles Hoskinson, highlights the synergy between AI and blockchain, announcing an AI bot for content creation. Cardano's developer group shifts focus to growth, halting Acropolis development to prioritize chain abstraction, while addressing performance issues in their upcoming hard fork upgrade.

Solayer’s founder exposes a security vulnerability in large language model (LLM) routers; in 428 routers, more than 20% exhibit malicious behavior, such as private keys being stolen. The research recommends that developers implement a separate end-to-end integrity verification mechanism on the client side and provides three defense options to mitigate supply-chain attacks.

Anthropic has launched Claude Managed Agents, providing a fully managed AI agent development platform that streamlines enterprise automation workflows and claims it can accelerate product production by 10x. The platform includes a security-focused infrastructure, supports long-running execution and multi-agent coordination, and enables developers to focus more on core business activities. Notion has already been an early adopter of this service, improving work efficiency and signaling that competition in the enterprise AI market is intensifying.

Coinbase's developer platform upgrades the x402 protocol, launching the “Upto” plan and enabling a variable pricing mechanism that replaces the previous fixed-fee model to support large language model (LLM) inference and related computing services. This plan is intended to address the issue where users can’t predict costs because they pay fixed fees, with the final amount paid not exceeding the user-set cap. The x402 protocol has been taken over by the Linux Foundation, but transaction volume has continued to decline after the 2025 peak, and it remains to be seen whether the Upto upgrade can boost network activity.

Andrej Karpathy said that the public’s understanding of AI capabilities has developed a split, divided into two groups: ordinary users using the free version of ChatGPT and professional technical people using advanced models on a paid basis. He believes that the two are discussing entirely different products and emphasizes that progress in the technical field is significant because of verifiable reward functions and incentives driven by commercial value.