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快来看，n8n更新了！生产级AI工作流的提示测试框架 一手编译

Still guessing if your prompts work? Learn how to build a systematic prompt testing framework that catches regressions before they reach production.
n8n
qimuai 发布于 
6 0
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快来看，n8n更新了！试用新模型和服务，无需设置账户 一手编译

Starting with n8n v2.36, you can now use supported AI models and tool services on select n8n Cloud plans without creating a provider account or generating an API key. Choose Gatewa...
n8n
qimuai 发布于 
24 0
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快来看，n8n更新了！流程编排：执行模型、可观测性与生产挑战 一手编译

Compare deterministic, dynamic, and agentic process orchestration models to build reliable, scalable workflows with visibility across enterprise systems.
n8n
qimuai 发布于 
38 0
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快来看，n8n更新了！MCP与API：关键区别及各自适用场景 一手编译

MCP vs. API: Learn how the Model Context Protocol differs from traditional APIs, when to use each, and how to combine both in n8n.
n8n
qimuai 发布于 
46 0
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快来看，n8n更新了！介绍n8n助手 一手编译

If you've built anything in n8n, you know the gap: you can describe what you want to automate in a sentence, but that's not the same as knowing which nodes to use, in wha...
n8n
qimuai 发布于 
33 0
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快来看，n8n更新了！AI代理可靠性：在生产环境中进行调试、评估与监控 一手编译

Run AI agents reliably in production. Learn how to debug failures, evaluate performance, track key metrics, add guardrails, and monitor agent behavior with n8n.
n8n
qimuai 发布于 
34 0
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快来看，n8n更新了！工作流安全：受监管行业的控制措施 一手编译

Implement workflow security in regulated environments: control access, manage credentials, log every action, and meet HIPAA, SOC 2, and GDPR requirements.
n8n
qimuai 发布于 
49 0
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快来看，n8n更新了！超越提示工程的长期运行智能体 一手编译

Y'all relying too much on prompting your way through agent design. Call it context engineering or god damn loop engineering, you still ask the LLM to make sure it only generat...
n8n
qimuai 发布于 
38 0
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快来看，n8n更新了！RBAC对AI代理的适用性：静态角色为何失效及取而代之的方案 一手编译

RBAC for AI agents introduces risky security gaps. Learn why traditional access control breaks at the agentic layer and how task-based rules help.
n8n
qimuai 发布于 
50 0
article cover

快来看，n8n更新了！构建能够记住每位客户的多智能体团队：基于Amazon Bedrock AgentCore 一手编译

A triage agent routes each customer question to one of three specialists: one computes real numbers in a sandbox, one loads AWS guidance, one investigates. All four run on a single...
n8n
qimuai 发布于 
49 0

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  • twitter-author qimuai 1 年前

    We’re opening an office in Seattle

    Come join us!

    https://t.co/E9BY2xFU2j

  • twitter-author qimuai 1 年前

    Get through PDFs effortlessly with Grok.

    Highlight any section and click "Explain" to have Grok help you understand it.

    Or click "Quote" to ask a specific question. https://t.co/epQt4Nypfw

  • twitter-author qimuai 1 年前

    i have had the strangest experience reading this: i assume its all fake/bots, even though in this case i know codex growth is really strong and the trend here is real.

    i think there are a bunch of things going on: real people have picked up quirks of LLM-speak, the Extremely Online crowd drifts together in very correlated ways, the hype cycle has a very "it's so over/we're so back" extremism, optimization pressure from social platforms on juicing engagement and the related way that creator monetization works, other companies have astroturfed us so i'm extra sensitive to it, and a bunch more (including probably some bots).

    but the net effect is somehow AI twitter/AI reddit feels very fake in a way it really didnt a year or two ago.

  • twitter-author qimuai 1 年前

    Jakub and Szymon:

    https://t.co/6qrVNp5Q3u

  • twitter-author qimuai 1 年前

    有时候会觉得，写的这些东西都太浅显了，发到朋友圈会不会被加的大V们嘲笑？如果有这个想法，肯定是做不好自媒体的。

    除非大V们是你的目标用户，否则永远不要让其他无关的人左右你的选题。

    你应该只关注，你的目标用户需要什么。

  • twitter-author qimuai 1 年前

    人类在学习新知识或解决新问题时，往往不是直接“改写大脑参数”，而是通过“记笔记”或“自我提醒”的方式，将经验和策略以显式的形式保留下来。

    例如，当你遇到某类问题时，会总结出“下次遇到类似情况可以这样做”的经验。这种方式更像是在不断编辑自己的“系统提示”，而不是每次都重新训练大脑。

  • twitter-author qimuai 1 年前

    此时常有人问该选哪个模型。我的答案永远是：工作环境允许的最强模型。我们不是大规模使用AI，所以即使工程角度认为"贵"或"慢"，也要选最好的大脑。（唯一限制应是公司对敏感信息上传的规定。）

  • twitter-author qimuai 1 年前

    成功与思考伙伴（人或机器）协作的关键在于取其精华去其糟粕

  • twitter-author qimuai 1 年前

    引用David Lieb（YC合伙人、Google Photos创始人）的话："你的直觉是世界上最复杂的机器学习模型。"使用生成式AI时，用你的专业品味识别有价值的内容。

  • twitter-author qimuai 1 年前