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Nov 12Thu
  1. Tessl Blog

    Tessl Blog Discusses Three Cycle Models of a Software Factory: Maintaining Operations, Continuous Learning, and Exploring Innovation

    Tessl Blog analyzes three cycles of the software factory: the "treadmill cycle" for maintaining operations, which accelerates daily tasks with AI but does not solve fundamental problems; the "learning cycle" for continuous learning, which uses AI to capture knowledge to improve guidelines and reduce repetitive work; and the "dream cycle" for exploring innovation, which leverages AI for small-scale experiments to push postponed improvements. AI tools need to have effective context and testing capabilities to transform knowledge accumulation into actual value.

Nov 6Fri
  1. O'Reilly Radar

    New knowledge carriers for the AI economy

    At the recent Foo Camp, participants believed that the primary carrier of software development is shifting from executable code to natural language prompts, generative processes, and developer skills. Some compared Python to assembly language, suggesting that natural language generation might make traditional code writing optional.

Oct 21Wed
  1. Tessl Blog70

    Personal applications: When JavaScript and SQLite are enough

    Personal application software is built around individual needs, and JavaScript/TypeScript and SQLite can achieve far beyond expected functionality, as shown by examples like Bonn Tonne, Daybreak, and Quote-Assist. LLMs are adept at handling these two technologies, enabling rapid generation of such applications. Cloudflare Durable Objects or self-built celld can provide the runtime environment, achieving isolation, ease of operation, and zero-cost scalability.

Jun 18Thu
  1. Dify Blog65

    Dify Cloud: A Production-Grade Platform Guide for Internal AI Applications

    Dify Cloud provides out-of-the-box capabilities such as LLM, built-in RAG, and visual workflows, allowing IT and business teams to quickly build and manage internal AI applications. The platform eliminates the complexity of building AI infrastructure, with users responsible only for application development while infrastructure is managed by Dify Cloud. It supports seamless scaling from a free Sandbox tier, ensuring application ownership, proprietary data, and governance standards.