Qianwen launches an onboarding table for the Agent feature, supporting dialogue generation and editing Excel files

Google AI Studio Launches Tab Tab Tab: Vibe Coding’s Prompt Autocomplete Engine

Google AI developer relations lead Logan Kilpatrick announced the launch of a prompt auto-completion engine called “Tab Tab Tab,” aiming to improve developers’ interaction experience in the Vibe Coding interface of AI Studio. This feature uses Gemini to automatically suggest more complete instructions, enabling developers to express vague ideas more precisely, improving instruction quality, overcoming the bottleneck of humans providing instructions, and strengthening Google AI Studio’s competitiveness within the toolchain.

Gate founder Dr. Han: Reshaping the platform’s capability boundaries with an AI ecosystem and multi-asset strategy

Gate founder Dr. Han introduced the platform’s development in the anniversary public letter, including deepening the AI ecosystem and a multi-asset trading framework. Gate is building an AI product ecosystem and has launched a TradFi trading section, covering multiple asset types to meet users’ needs. In addition, it has rolled out a digital Pre-IPOs participation mechanism, giving users a new way to access high-quality public offering projects. Going forward, Gate will continue to strengthen its infrastructure and enhance users’ global digital asset trading experience.

A Karpathy-inspired CLAUDE.md Breaks 15K Stars: How a Markdown File Can Tame an AI’s Bad Habits of Writing Code

A Markdown file named CLAUDE.md, based on observations and principles provided by Andrej Karpathy, helped the Claude Code project break 15,000 stars on GitHub. This document sets behavioral guidelines for common mistakes LLMs make when writing code, emphasizing goal-driven behavior, confirming requirements, and proactively disclosing trade-offs. It reflects developers’ focus on engineering AI behavior, and may even be more effective than choosing a more powerful model.

Starbucks CEO Reveals an “AI Barista Assistant”: Real-Time Help Brewing and Fixing Confusion in Channel Orders

Starbucks CEO Brian Niccol unveiled two AI systems at the Dreamforce conference: “Green Dot” and “Smart Q.” The former acts as a real-time assistant for store employees, while the latter solves order mix-up issues to improve service efficiency. In the future, the Starbucks app will be able to predict what customers order, enabling more convenient drink preparation. This series of AI deployments is intended to strengthen Starbucks’ role as a social space for people.

Bitcoin miners face tough 2028 halving profits, as mining companies deploy AI infrastructure early to address the energy crisis

Bitcoin mining companies are facing profit pressure after the halving and challenges in power supply. Major operators are shoring up capital management through asset sales and seeking to diversify their energy-security arrangements. In addition, miners are turning to artificial intelligence infrastructure to improve operational flexibility. In the future, competitive advantage will belong to companies that can effectively manage debt and ensure long-term power supply.

V God shares: How I built a fully local, private, and self-controlled AI working environment

Vitalik Buterin proposed a local AI architecture, emphasizing privacy, security, and self-sovereignty, and warned about the potential risks of AI agents. He suggested avoiding cloud-based models and setting five major security goals to protect personal data. Testing showed that the NVIDIA 5090 laptop is the best hardware choice, and he stressed that a local-first strategy is crucial to the security of today’s AI tools.