长时间运行 AI Agent 的开发者会面临结果展示和验证的痛点，HTML Artifacts 提供了一种轻量级解决方案，值得尝试整合到自己的工作流中。
用户 @omarsar0 分享了他如何将 HTML Artifacts 作为与 AI Agent 协作的核心工具。在长时间运行的 Agent 会话中，聊天窗口无法有效展示复杂工作成果，而 HTML Artifacts 提供了可视化验证层，帮助用户审查 Agent 的工作。他利用 HTML Artifacts 进行日志记录、实验追踪、代码审查、深度研究等任务，并构建了标签系统来管理。他认为随着 Agent 应用更复杂，交互形式将进化到交互式神经视频/模拟。
Increasingly, HTML Artifacts are becoming a core part of how I work with AI agents. Long-horizon ag...
Increasingly, HTML Artifacts are becoming a core part of how I work with AI agents. Long-horizon agent sessions need a better way to surface insights about what work it has done. This may not be obvious right now, but as you start to let your agent work on dynamic workflows, large codebases, long-running loops (e.g., using /goal), and deep research tasks, you need a good way to present results. Chat window is not it. You also don't want to just trust everything the agents do. Artifacts help provide an important verification layer, which in turn enables important decision-making. I like HTML artifacts because I can just ask the agent to produce as many of them (and in whatever form) as I need to verify the work and make sense out of everything. I even built a nice tab system for my artifacts. They are great for continual learning and research. I use HTML artifacts for logging, tracking experiments, brainstorming, managing my inbox, code reviews, agent session management, deep research, writing, reading, and so much more. I believe @karpathy wrote about this somewhere: As we move on to more advanced applications of AI agents and outputs get more complex, we will start to find the need for even more advanced forms of interactions with AI, including interactive neural videos/simulations. Your browser does not support the video tag. 🔗 View on Twitter 💬 12 🔄 8 ❤️ 57 👀 3820 📊 25 ⚡