Claude Code is a fantastic agent and has recently taken the developer community by storm and interestingly not just for coding related things but for other things in general writing books, writing reports, things like that. And part of the reason is that it is so good at general purpose and longer time horizon planning and and doing things deeply that it it can be extended to to all of these things. This isn't the first agent that has come out that has been able to do these deep work.So we have Manessa, a g ...

AI Development & Application - The industry is currently using outdated software development techniques for AI features, hindering the full potential of AI, which should enable users to program software using natural language [1][18] - AI application development is often approached by trying to fit AI into existing applications, rather than redesigning tools from the ground up to automate repetitive tasks [18][62] - The industry needs to move beyond the chatbot paradigm and focus on AI's capability to automate work and accomplish tasks on behalf of users [58][60] - A key element is providing users with "tools" that agents can use to accomplish tasks, such as labeling emails, archiving them, or writing drafts [53][54] System Prompts & User Control - Current AI applications often hide the "system prompt" (instructions given to the AI) from the user, limiting customization and personalization [1][11] - The industry should allow users to view and edit system prompts, enabling them to tailor the AI's behavior to their specific needs and preferences [8][10] - Allowing users to control system prompts shifts the responsibility for the AI's output from the developer to the user [35] - While not everyone may want to write system prompts from scratch, the option should be available, and AI could assist in generating and customizing prompts based on user history and feedback [41][42][48] Future of AI Development - The industry needs to develop better tooling and UI conventions for interacting with and teaching AI, potentially including AI-assisted system prompt writers [45][46] - AI models are good at processing instructions and turning them into text output, making them particularly effective for coding agents [31][32] - Founders should rethink existing tools from the ground up with AI, focusing on offloading repetitive work from users [61][62]

整理 I 褚杏娟 近日，Github 上有一个开源项目，曝出了 FULL v0、Manus、Cursor、Same.dev、Lovable、Devin、Replit Agent、Windsurf Agent 和 VSCode Agent 的完整官方 System Prompt（系统提示词）和内部工具，有超过 6,500 行关于其结构和功能的见解。截至目前，该项目已经斩获了近 2.5 万颗星和 7700 多分叉。 与 User Prompt（用户提示词）不同，System Prompt 的设计方式，能极大地影响大模型或 Agent 的输出效果。 System Prompt 是在对话开始前设置的一段隐藏性说明，用来对模型进行一些初始化设定，如定义 AI 的角色、行为准则和整体风格等，不会随着用户 每轮的输入而更新。默认情况下，System Prompt 通常由开发者预先设置，对用户不可见。 项目作者在 Github 上的账户为 lucknitelol，这个人彻底破解了上述工具的 System Prompt，这里面有很多大家可以借鉴的地方。 开源链接： https://github.com/x1xhlol/syst ...