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AI & Enterprise

Conditions for the fastest AI-native engineering team

Andrew Ng (응) of Stanford University posted a summary of how AI-native software teams operate differently from traditional teams. He wrote that the biggest difference is using coding agents to build products much faster, which changes team structure, roles and decision-making. As development speeds up, planning, design, marketing and compliance can become bottlenecks. Ng urged engineers to learn product management skills and product managers to learn how to build. He also stressed the value of working in the same space for faster communication.

AI & Enterprise

Spring creator unveils Embabel Java AI agent framework, aims to rival Python tools

Rod Johnson, creator of the Spring Java development framework, introduced Embabel, a Java-based agent AI framework, at Microsoft’s JDConf developer conference. The Apache-licensed open-source framework is available on GitHub. Built on Spring Boot and written in Kotlin, it is fully compatible with Java. Johnson said Embabel aims to address predictability issues companies face in AI by balancing generative AI with more predictable Java code, using the GOAP pathfinding algorithm.

Crypto

Bithumb to build companywide tailored AI work environment

Bithumb said on Wednesday it will introduce tailored artificial intelligence agents across its operations as it seeks to innovate companywide work processes. The company will use an “insight agent” to support data collection and report writing, and is operating an “analysis agent” that converts natural-language requests into SQL queries. It has also deployed coding agents and plans to add an adviser support agent at its call centre from May. It is reviewing AI automation in compliance.