Viewpoints, commentary, analysis, interviews, and discussion of trends.
Based on a survey of 300 data and AI executives, MIT Technology Review found that only about 34% of enterprise agentic AI projects reach production on average. A lack of knowledge is one of the main reasons they fail.
The latest GitHub Podcast examines five popular AI claims. AI-generated code still needs to be read and owned, with review effort scaled to risk; Skills and MCP address different needs, with Skills packaging team expertise and MCP standardizing connections to tools and data; and RAG is not dead, since it can coexist with agents, Skills, and MCP in one workflow. The episode also discusses judging AI fluency in hiring and how fine-tuning needs can signal codebase maintainability problems.
