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2025-04-04-top

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討論重點​

以下是14篇文章的重點條列總結，並附上對應的錨點連結與逐條細節說明：

1. 10 Agent Papers You Should Read from March 2025​

主題：AI Agent 最新研究進展與應用

  • 技術架構優化：長期任務規劃框架（PLAN-AND-ACT）、記憶增強機制（MemInsight）。
  • 多代理系統挑戰：失敗模式分析（Why Do Multi-Agent LLM Systems Fail?）、協作工作流生成（WorkTeam）。
  • 應用場景突破：3D遊戲代理（PORTAL）、網頁自動化任務（BEARCUBS基準）。
  • 安全與評估：網頁代理安全性測試（SAFEARNA）、未知環境適應力評估（EconEvals）。
  • 認知能力探索：角色扮演中的內部思維建模（ROLETHINK）。

2. I Built an AI Agent to find and apply to jobs automatically​

主題：AI 驅動的求職工具 SimpleApply

  • 功能：自動篩選職位、匹配技能、預測面試機率。
  • 優勢：發現冷門遠端職缺、提供匹配分數、三種申請模式（手動/半自動/全自動）。
  • 簡易性：僅需上傳履歷，AI 處理後續流程。

3. Aren't you guys concerned about AI privacy?​

主題：AI 隱私風險與替代方案

  • 隱私風險：敏感數據（財務、法律）可能被記錄或濫用。
  • 透明度不足：大型科技公司主導，缺乏開源與獨立審查。
  • 矛盾點：便利性 vs. 隱私保護的可行性。

4. The dev that lost $5,800 building an agent for a client​

主題：AI 自由職業者的客戶失信風險

  • 問題：未簽合約導致經濟損失。
  • 解決方案：平台內建合約、分期付款、客戶驗證。
  • 社群共創：透過案例分享推動制度設計。

5. Human in the loop​

主題：人類在自主系統中的監督角色

  • 必要性：高風險任務需人類介入（如自動駕駛）。
  • AI 局限性：即使 99% 準確率，1% 失誤仍可能致命。
  • 未來挑戰：平衡效率與風險控管。

6. I built an open-source Operator that can use computers​

主題：開源桌面自動化工具 Spongecake

  • 功能：虛擬桌面（Xfce/VNC）建置與自動化操作。
  • 技術細節：Docker 容器、Marionette 提取 DOM、併發處理。
  • 目標：支援缺乏 API 的企業應用（如醫療、供應鏈）。

7. I built an MVP that helps you set automated phone calls reminders​

主題：提醒服務商業化可行性

  • 功能：設定電話提醒（如服藥）。
  • 動機：解決個人需求（父親失智症）。
  • 疑問：市場需求與訂閱制潛力。

8. Tools recommendations for unstructured to structured database​

主題：非結構化數據轉結構化工具選擇

  • 需求：GIS 系統需整理郵件、會議記錄等。
  • 工具困惑：n8n（工作流程） vs. LangGraph（代理）。
  • 關鍵問題：釐清代理應用與工作流程管理的差異。

9. We built a toolkit that connects your AI to any app​

主題：AI 與應用整合工具包 MatonAgentToolkit

  • 優勢：3 行程式碼整合 SaaS 工具（如 Salesforce、Slack）。
  • **功能

文章核心重點​

以下是各篇文章的一句話摘要（條列式輸出）：

  1. 10 Agent Papers You Should Read from March 2025

    • 精選2024年2月發表的10篇AI Agent論文，涵蓋技術架構、多代理系統、應用場景與安全評估等前沿動態。

  2. I Built an AI Agent to find and apply to jobs automatically

    • 介紹免費工具SimpleApply，透過AI自動篩選與申請職缺，提升求職效率與精準度。

  3. Aren't you guys concerned about AI privacy?

    • 探討AI聊天機器人的隱私風險，質疑現有服務的數據處理透明度與替代方案可行性。

  4. The dev that lost $5,800 building an agent for a client made us completely rethink AI agent freelancing

    • 反思AI代理自由接案的客戶失信風險，主張平台需內建合約與付款保護機制。

  5. Human in the loop

    • 強調人類監督在自主系統（如AI代理）中的必要性，質疑完全自動化的可行性。

  6. I built an open-source Operator that can use computers

    • 開發者推出開源工具Spongecake，簡化虛擬桌面建置與自動化操作，解決現有工具限制。

  7. I built an MVP that helps you set automated phone calls reminders (My dad has alzheimer)

    • 個人開發的電話提醒工具，評估其商業化潛力以幫助類似需求者（如照護失智症患者）。

  8. Tools recommendations for unstructured to structured database.

    • 尋求工具建議，將非結構化市場情報轉為結構化數據，以滿足GIS系統需求。

  9. We built a toolkit that connects your AI to any app in 3 lines of code

    • 推出MatonAgentToolkit，以簡潔程式碼整合AI模型與SaaS應用，簡化開發流程。

  10. How to make the AI agent understand which question talks about code, which one talks about database, and which one talks about uploading file ?

    • 探討改進LangChain應用，使AI能更精準辨識與處理多功能用戶請求（如文件上傳、數據庫查詢）。

  11. Understanding and Preventing Prompt Injection

    • 分析提示注入攻擊的風險與成因，呼籲開發AI時需強化安全設計。

  12. What's Your Expectation for an AI Agent That Can Help You with Data Analysis?

    • 徵求用戶對理想數據分析AI工具的需求，以打造兼顧新手與進階用戶的差異化產品。

  13. Give Postgres access to an AI Agent directly (good idea?)

    • 討論如何安全限制AI代理的PostgreSQL存取權限，避免開放完整數據庫控制權。

  14. Are AI Agents Making Us Too Lazy or Just More Efficient?

    • 辯論AI代理提升效率的同時，是否導致人類過度依賴與認知能力退化。

目錄​

  • [1. 10 Agent Papers You Should Read from March 2025](#1-``` 10-agent-papers-you-should-read-from-march-2)
  • [2. I Built an AI Agent to find and apply to jobs automatically](#2-``` i-built-an-ai-agent-to-find-and-apply-to-job)
  • [3. Aren't you guys concerned about AI privacy?](#3-``` aren-t-you-guys-concerned-about-ai-privacy- )
  • [4. The dev that lost $5,800 building an agent for a client made us completely rethink AI agent freelancing](#4-``` the-dev-that-lost-5-800-building-an-agent-fo)
  • [5. Human in the loop](#5-``` human-in-the-loop
- [6. ```
I built an open-source Operator that can use computers
```](#6-```
i-built-an-open-source-operator-that-can-use)
- [7. ```
I built an MVP that helps you set automated phone calls reminders (My dad has alzheimer)
```](#7-```
i-built-an-mvp-that-helps-you-set-automated-)
- [8. ```
Tools recommendations for unstructured to structured database.
```](#8-```
tools-recommendations-for-unstructured-to-st)
- [9. ```
We built a toolkit that connec``` your AI to any app in 3 lines of code
```](#9-```
we-built-a-toolkit-that-connec```-your-ai-to)
- [10. ```
How to make the AI agent understand which question talks about code, which one talks about database, and which one talks about uploading file ?
```](#10-```
how-to-make-the-ai-agent-understand-which-q)
- [11. ```
Understanding and Preventing Prompt Injection
```](#11-```
understanding-and-preventing-prompt-injecti)
- [12. ```
What's Your Expectation for an AI Agent That Can Help You with Data Analysis?
```](#12-```
what-s-your-expectation-for-an-ai-agent-tha)
- [13. ```
Give Postgres access to an AI Agent directly (good idea?)
```](#13-```
give-postgres-access-to-an-ai-agent-directl)
- [14. ```
Are AI Agen``` Making Us Too Lazy or Just More Efficient?
```](#14-```
are-ai-agen```-making-us-too-lazy-or-just-m)

---

## 1. ```
10 Agent Papers You Should Read from March 2025
``` {#1-```
10-agent-papers-you-should-read-from-march-2}

這篇文章的核心討論主題是「AI Agent（人工智慧代理）的最新研究進展與應用」，具體聚焦於2024年2月發表的10篇相關論文。主要涵蓋以下方向：

1. **技術架構優化**  
   - 長期任務規劃框架（如PLAN-AND-ACT）  
   - 記憶增強機制（MemInsight）  

2. **多代理系統挑戰**  
   - 失敗模式分析與評估方法（Why Do Multi-Agent LLM Systems Fail?）  
   - 協作工作流生成（WorkTeam）  

3. **應用場景突破**  
   - 3D遊戲代理（PORTAL）  
   - 網頁自動化任務（API/GUI代理比較、BEARCUBS基準）  

4. **安全與評估基準**  
   - 網頁代理安全性測試（SAFEARENA）  
   - 未知環境適應力評估（EconEvals）  

5. **認知能力探索**  
   - 角色扮演中的內部思維建模（ROLETHINK）  

整體而言，文章透過精選論文呈現AI Agent領域在「技術創新」、「系統可靠性」、「實用性驗證」三大層面的前沿動態，同時凸顯當前研究對「複雜環境適應性」和「人機協作」的關鍵關注。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jq0f1q/10_agent_papers_you_should_read_from_march_2025/](https://reddit.com/r/AI_Agents/comments/1jq0f1q/10_agent_papers_you_should_read_from_march_2025/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jq0f1q/10_agent_papers_you_should_read_from_march_2025/](https://www.reddit.com/r/AI_Agents/comments/1jq0f1q/10_agent_papers_you_should_read_from_march_2025/)
- **發布時間**: 2025-04-03 05:29:40

### 內容

We have compiled a list of 10 research papers on AI Agen published in February. If you're interested in learning about the developmen happening in Agen```, you'll find these papers insightful.

Out of all the papers on AI Agen``` published in February, these ones caught our eye:

  1. PLAN-AND-ACT: Improving Planning of Agen``` for Long-Horizon Tasks A framework that separates planning and execution, boosting success in complex tasks by 54% on WebArena-Lite.

  2. Why Do Multi-Agent LLM Systems Fail? A deep dive into failure modes in multi-agent setups, offering a robust taxonomy and scalable evaluations.

  3. **Agen Play Thousands of 3D Video Games** PORTAL introduces a language-model-based framework for scalable and interpretable 3D game agen.

  4. API Agen vs. GUI Agen: Divergence and Convergence A comparative analysis highlighting strengths, trade-offs, and hybrid strategies for LLM-driven task automation.

  5. **SAFEARENA: Evaluating the Safety of Autonomous Web Agen** The first benchmark for testing LLM agen on safe vs. harmful web tasks, exposing major safety gaps.

  6. WorkTeam: Constructing Workflows from Natural Language with Multi-Agen``` A collaborative multi-agent system that translates natural instructions into structured workflows.

  7. **MemInsight: Autonomous Memory Augmentation for LLM Agen** Enhances long-term memory in LLM agen, improving personalization and task accuracy over time.

  8. **EconEvals: Benchmarks and Litmus Tes for LLM Agen in Unknown Environmen** Real-world inspired tes focused on economic reasoning and decision-making adaptability.

  9. **Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agen** Introduces ROLETHINK to evaluate how well agen model internal thought, especially in roleplay scenarios.

  10. **BEARCUBS: A benchmark for computer-using web agen** A challenging new benchmark for real-world web navigation and task completionhuman accuracy is 84.7%, agen score just 24.3%.

You can read the entire blog and find links to each research paper below. Link in commen```


---

## 2. ```
I Built an AI Agent to find and apply to jobs automatically
``` {#2-```
i-built-an-ai-agent-to-find-and-apply-to-job}

這篇文章的核心討論主題是介紹一個名為 **SimpleApply** 的免費工具，其主要功能是透過 AI 技術幫助求職者更高效地尋找和申請適合的工作，並在雇主與求職者之間創造更公平的競爭環境。  

具體重點包括：  
1. **工具目的**：  
   - 減少求職者手動填寫申請表的時間。  
   - 根據求職者的技能和經驗，精準匹配職位（而非濫發申請）。  

2. **獨特優勢**：  
   - 能發現其他平台難以找到的遠端職缺。  
   - 提供「職位匹配分數」，預測面試機率，幫助求職者優先申請高匹配度的工作。  

3. **使用方式**（三種彈性選項）：  
   - 僅由 AI 篩選職位並評分，用戶手動申請。  
   - AI 篩選後，用戶選擇職位並由 AI 代為申請。  
   - 全自動申請匹配度 60% 以上的職位。  

4. **簡易性**：用戶只需上傳履歷，AI 即自動處理後續流程。  

總結：文章聚焦於 **AI 驅動的求職工具如何優化找工作流程**，強調其效率、精準度和免費特性。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqloxe/i_built_an_ai_agent_to_find_and_apply_to_jobs/](https://reddit.com/r/AI_Agents/comments/1jqloxe/i_built_an_ai_agent_to_find_and_apply_to_jobs/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqloxe/i_built_an_ai_agent_to_find_and_apply_to_jobs/](https://www.reddit.com/r/AI_Agents/comments/1jqloxe/i_built_an_ai_agent_to_find_and_apply_to_jobs/)
- **發布時間**: 2025-04-03 23:38:32

### 內容

It started as a tool to help me find jobs and cut down on the countless hours each week I spent filling out applications. Pretty quickly friends and coworkers were asking if they could use it as well so I got some help and made it available to more people.

The goal is to level the playing field between employers and applican. The tool doesnt flood employers with applications (that would cost too much money anyway) instead the agent targe roles that match skills and experience that people already have.

Theres a couple other tools that can do auto apply through a chrome extension with varying resul```. However, users are also noticing were able to find a ton of remote jobs for them that they cant find anywhere else. So you dont even need to use auto apply (people have varying opinions about it) to find jobs you want to apply to. As an additional bonus we also added a job match score, optimizing for the likelihood a user will get an interview.

Theres 3 ways to use it:

  1. Have the AI Agent just find and apply a score to the jobs then you can manually apply for each job

  2. Same as above but you can task the AI agent to apply to jobs you select

  3. Full blown auto apply for jobs that are over 60% match (based on how likely you are to get an interview)

Its as simple as uploading your resume and our AI agent does the rest. Plus its free to use, its called SimpleApply


---

## 3. ```
Aren't you guys concerned about AI privacy?
``` {#3-```
aren-t-you-guys-concerned-about-ai-privacy-
}

這篇文章的核心討論主題是：  
**「使用者對AI聊天機器人隱私問題的擔憂，尤其是數據是否被存儲、分析或用於訓練模型，以及是否存在真正注重隱私的替代方案。」**  

具體要點包括：  
1. **隱私風險**：使用者廣泛將AI用於敏感領域（如財務、法律、心理健康），但擔憂個人數據可能被平台記錄或濫用。  
2. **透明度不足**：多數AI服務由大型科技公司運營且不開源，缺乏獨立審查機制，用戶難以確認數據處理方式。  
3. **替代方案的疑問**：探討是否存在真正不記錄數據的隱私導向AI，或此需求在當前技術與商業模式下是否難以實現。  

整體圍繞「AI便利性與隱私保護之間的矛盾」展開質疑。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqcjsx/arent_you_guys_concerned_about_ai_privacy/](https://reddit.com/r/AI_Agents/comments/1jqcjsx/arent_you_guys_concerned_about_ai_privacy/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqcjsx/arent_you_guys_concerned_about_ai_privacy/](https://www.reddit.com/r/AI_Agents/comments/1jqcjsx/arent_you_guys_concerned_about_ai_privacy/)
- **發布時間**: 2025-04-03 15:54:41

### 內容

I see people using AI chatbo``` for personal finance, legal advice, even mental health support, basically feeding it everything about their lives. I'd love to do the same, but how do you know that data isnt stored, analyzed, or even used to train future models?

Most AI services are closed source and run on Big Techs infrastructure, meaning theres no way to audit whats really happening behind the scenes. Are there privacy focused AI options that dont log everything, or is true AI privacy just a pipe dream?


---

## 4. ```
The dev that lost $5,800 building an agent for a client made us completely rethink AI agent freelancing
``` {#4-```
the-dev-that-lost-5-800-building-an-agent-fo}

這篇文章的核心討論主題是：  
**「在AI代理（AI agent）等新興技術領域的自由職業者（或開發者）面臨的客戶失信風險（如未簽合約、未付款等），以及如何透過平台設計（例如內建合約、分期付款機制、客戶驗證等）來保障服務提供者的權益。」**

具體要點包括：  
1. **問題背景**：自由職業者因缺乏合約或客戶失信而遭受經濟損失的普遍現象。  
2. **解決方向**：平台需內建保護機制，例如強制合約、分階段付款、客戶身分驗證、明確的專案範圍界定等。  
3. **社群共創**：透過分享實際案例（如Reddit貼文引發的反思），推動更完善的系統設計，以減少從業者的風險。  

整體強調「從過往教訓中學習」並「以技術或制度設計預防風險」，尤其聚焦於新興科技領域中自由接案者的權益保障。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqh69q/the_dev_that_lost_5800_building_an_agent_for_a/](https://reddit.com/r/AI_Agents/comments/1jqh69q/the_dev_that_lost_5800_building_an_agent_for_a/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqh69q/the_dev_that_lost_5800_building_an_agent_for_a/](https://www.reddit.com/r/AI_Agents/comments/1jqh69q/the_dev_that_lost_5800_building_an_agent_for_a/)
- **發布時間**: 2025-04-03 20:31:04

### 內容

A few weeks ago I saw the post from u/crazychampion2 about losing $5,800 after building an AI agent for a client who vanished. No contract, no payment, no accountability.

Annoyingly, this isn't a rare story. All of us freelancers have experienced this or know someone who has.

As with all big new tech trends, lo``` of young and excited new builders enter the space wide eye'd and bushy tailed, only to make small mistakes and get f*ckd for them.

We were already working on our ai agent job board. But the thread has shifted our focus & made us double down on ensuring the sellers on the other side are protected too.

We're now thinking about things like:

  • Contrac``` baked into the platform by default

  • Milestone-based payment releases

  • Client verification, so you know who you're working with

  • Clear scope definitions to avoid vague expectations and finger-pointing

It's crazy how much a single post in this sub has changed our roadmap... hoping more builders share their stories too. Because the more we surface the messy stuff, the better we can design for the people actually doing the work.

If any of you have been burned in the past LMK what wouldve helped you avoid it? What protections would you want if you could design the system from scratch?

Would love to hear the though``` of devs and agent-buyers alike.


---

## 5. ```
Human in the loop
``` {#5-```
human-in-the-loop
```}

這篇文章的核心討論主題是：  
**「人類在自主系統（如自動駕駛車輛和AI代理）中的關鍵監督角色」**，並探討未來當軟體普遍轉向代理驅動（agentic workflows）時，人類應如何參與以確保系統的可靠性與安全性。  

具體要點包括：  
1. **遠端監督的必要性**：以自動駕駛為例，強調「人類介入」（human in the loop）是系統運作的關鍵，尤其在高風險任務中。  
2. **AI代理的局限性**：即使代理達到99%準確率（當前僅80%），剩餘1%的失誤仍可能引發重大危機，任務越關鍵越需人類把關。  
3. **未來挑戰**：當軟體全面轉向代理驅動的工作流程時，如何設計人類角色以平衡效率與風險控管。  

本質上，文章聚焦於「人類與自主系統協作」的框架，並質疑完全自動化的可行性。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jq757s/human_in_the_loop/](https://reddit.com/r/AI_Agents/comments/1jq757s/human_in_the_loop/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jq757s/human_in_the_loop/](https://www.reddit.com/r/AI_Agents/comments/1jq757s/human_in_the_loop/)
- **發布時間**: 2025-04-03 10:36:44

### 內容

We come from autonomous vehicles where remote operations and remote human in the loop is key to deploy a functioning vehicle. Seeing the same with agen``` now.

Without a human in the loop agen``` will always be less than 100% and even if 99% working (todays benchmark is 80%) there is still a 1% chance of a big mess and a huge crisis depending on the agents task. The more crucial it is, the more human in the loop is a must.

How do you see human play their roles in the future of all software becoming agentic workflows?


---

## 6. ```
I built an open-source Operator that can use computers
``` {#6-```
i-built-an-open-source-operator-that-can-use}

這篇文章的核心討論主題是：  
**「開發者Terrell介紹其開源工具Spongecake，旨在簡化虛擬桌面（Xfce/VNC）的建置與桌面自動化操作，並解決現有工具的限制。」**  

具體重點如下：  
1. **工具目的**：  
   - 提供開源解決方案，讓開發者能快速建立自己的「Operator」（自動化代理），結合Next.js/React前端與Flask後端。  
   - 支援虛擬桌面（如Xfce）和VNC，並自動化桌面互動（例如模擬人類操作，類似OpenAI的電腦使用模型）。  

2. **解決痛點**：  
   - 現有工具多局限於瀏覽器自動化，或需高成本/不開源。  
   - 針對缺乏API的桌面應用（如醫療、供應鏈行業）或企業內部環境（如VPN/防火牆限制）提供自動化方案。  

3. **技術細節**：  
   - 使用Docker容器管理虛擬環境，整合VNC、API伺服器、Marionette（網頁DOM提取）等工具。  
   - 透過截圖與API指令實現代理與虛擬機的互動。  

4. **挑戰與創新**：  
   - **併發處理**：支援多代理平行任務，需解決端口衝突問題。  
   - **滾動優化**：透過Marionette提取DOM，避免模型過度滾動頁面。  

5. **未來計畫**：  
   - 擴展支援Windows/macOS環境，整合Anthropic等電腦使用模型。  

總結：文章主要推廣一個開源、可擴展的桌面自動化工具，並尋求社群反饋以進一步開發。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqp5cc/i_built_an_opensource_operator_that_can_use/](https://reddit.com/r/AI_Agents/comments/1jqp5cc/i_built_an_opensource_operator_that_can_use/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqp5cc/i_built_an_opensource_operator_that_can_use/](https://www.reddit.com/r/AI_Agents/comments/1jqp5cc/i_built_an_opensource_operator_that_can_use/)
- **發布時間**: 2025-04-04 01:50:56

### 內容

Hi reddit, I'm Terrell, and I built an open-source app that le``` developers create their own Operator with a Next.js/React front-end and a flask back-end. The purpose is to simplify spinning up virtual desktops (Xfce, VNC) and automate desktop-based interactions using computer use models like OpenAIs

There are already various cool tools out there that allow you to build your own operator-like experience but they usually only automate web browser actions, or arent open sourced/cost a lot to get started. Spongecake allows you to automate desktop-based interactions, and is fully open sourced which will help:

  • Developers who want to build their own computer use / operator experience

  • Developers who want to automate workflows in desktop applications with poor / no APIs (super common in industries like supply chain and healthcare)

  • Developers who want to automate workflows for enterprises with on-prem environmen with constrain like VPNs, firewalls, etc (common in healthcare, finance)

Technical details: This is technically a web browser pointed at a backend server that 1) manages starting and running pre-configured docker containers, and 2) manages all communication with the computer use agent. [1] is handled by spinning up docker containers with appropriate por to open up a VNC viewer (so you can view the desktop), an API server (to execute agent commands on the container), a marionette port (to help with scraping web pages), and socat (to help with port forwarding). \[2\] is handled by sending screensho from the VM to the computer use agent, and then sending the appropriate actions (e.g., scroll, click) from the agent to the VM using the API server.

Some interesting technical challenges I ran into:

  • Concurrency - I wanted it to be possible to spin up N agen at once to complete tasks in parallel (especially given how slow computer use agen are today). This introduced a ton of complexity with managing por``` since the likelihood went up significantly that a port would be taken.

  • Scrolling issues - The model is really bad at knowing when to scroll, and will scroll a ton on very long pages. To address this, I spun up a Marionette server, and exposed a tool to the agent which will extract a websites DOM. This way, instead of scrolling all the way to a bottom of a page - the agent can extract the websites DOM and use that information to find the correct answer

Whats next? I want to add support to spin up other desktop environmen``` like Windows and MacOS. Weve also started working on integrating Anthropics computer use model as well. Theres a ton of other features I can build but wanted to put this out there first and see what others would want

Would really appreciate your though```, and feedback. It's been a blast working on this so far and hope others think its as neat as I do :)


---

## 7. ```
I built an MVP that helps you set automated phone calls reminders (My dad has alzheimer)
``` {#7-```
i-built-an-mvp-that-helps-you-set-automated-}

這篇文章的核心討論主題是：  

**「評估將個人開發的提醒服務（SaaS/AaaS）商業化的可行性」**  

具體內容包括：  
1. **產品功能**：一個可設定電話提醒的SaaS工具，用戶需輸入電話號碼、聯絡人名稱及提醒目的（例如按時服藥）。  
2. **開發動機**：解決個人需求（幫助父親每天上午10點記得吃藥）。  
3. **商業化疑問**：是否值得購買網域並將此服務推向市場，成為訂閱制軟體服務（SaaS）或代理服務（AaaS）。  

關鍵問題在於：該工具是否具備足夠的市場需求與商業潛力，值得進一步投資。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqqkr3/i_built_an_mvp_that_helps_you_set_automated_phone/](https://reddit.com/r/AI_Agents/comments/1jqqkr3/i_built_an_mvp_that_helps_you_set_automated_phone/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqqkr3/i_built_an_mvp_that_helps_you_set_automated_phone/](https://www.reddit.com/r/AI_Agents/comments/1jqqkr3/i_built_an_mvp_that_helps_you_set_automated_phone/)
- **發布時間**: 2025-04-04 02:44:52

### 內容

i created a SaaS that you set reminders

you create one with a phone number, the name of the person being called, and the purpose

I did it to help me dad remember every day at 10AM that he has to take his pills and the agent le``` him know that is time, and where he can find it

do you think this is a good idea to buy a domain and make it a SaaS/AaaS ?


---

## 8. ```
Tools recommendations for unstructured to structured database.
``` {#8-```
tools-recommendations-for-unstructured-to-st}

這篇文章的核心討論主題是：  
**如何選擇合適的工具（如 n8n 或 LangGraph）來自動化收集、整理與結構化多源異構的市場情報數據（如郵件、表格、會議記錄等），以滿足 GIS 系統對結構化數據的需求，並探討此需求本質上屬於「代理（Agent）應用」還是「工作流程管理（Workflow Management）挑戰」。**

具體要點包括：  
1. **問題背景**：GIS 系統需結構化數據，但市場情報來源多元且非結構化（郵件、表格、會議記錄等），需人工整理。  
2. **工具選擇的困惑**：  
   - 是否適用自動化代理（Agent）或工作流程管理工具（如 n8n）？  
   - 對 LangGraph 的評價兩極，不確定其適用性。  
3. **尋求建議**：釐清工具功能與實際需求的匹配度，避免誤解工具設計初衷。  

整體聚焦於「工具評估」與「工作流程優化」之間的權衡。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jq710g/tools_recommendations_for_unstructured_to/](https://reddit.com/r/AI_Agents/comments/1jq710g/tools_recommendations_for_unstructured_to/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jq710g/tools_recommendations_for_unstructured_to/](https://www.reddit.com/r/AI_Agents/comments/1jq710g/tools_recommendations_for_unstructured_to/)
- **發布時間**: 2025-04-03 10:30:57

### 內容

Hi all,

I manage a GIS system and frequently create maps and dashboards. Lately, a large part of my role involves gathering and analyzing market intelligence, including competitor pricing, market activity, and bid outcomes. This information comes in many formsemails, tables, transcrip```, meeting notes, and even video recordings. Since GIS systems rely on structured data, I need to consolidate everything into organized tables.

Im wondering if using an agent could help automate this process, or if this is more of a workflow management challenge. Ive seen tools like n8n mentioned here, and it seems to have a strong following. Im curious whether it could help with collecting and structuring this kind of data. Ive also seen LangGraph mentioned often, but opinions seem mixed. For every person who recommends it, there are a few who express concerns.

Would tools like n8n or LangGraph be a good fit for this use case, or am I misunderstanding what theyre designed to do? I would really appreciate any insigh``` or suggestions.


---

## 9. ```
We built a toolkit that connec``` your AI to any app in 3 lines of code
``` {#9-```
we-built-a-toolkit-that-connec```-your-ai-to}

這篇文章的核心討論主題是介紹一個名為 **MatonAgentToolkit** 的開發工具包，其主要功能是讓開發者能夠以簡潔的程式碼（如幾行程式）將 AI 模型（如 OpenAI、LangChain 等）與各種應用程式（如 Salesforce、HubSpot、Slack 等 SaaS 工具）快速整合。  

重點包括：  
1. **簡化整合流程**：提供預先建置的 API 動作，減少開發複雜度。  
2. **跨平台支援**：兼容 OpenAI、AI SDK、LangChain 等框架，並支援多種環境（如 Claude for Desktop、Cursor）。  
3. **自動化驗證**：處理繁瑣的授權流程（如 OAuth、API Key），降低開發門檻。  
4. **開發者反饋**：邀請使用者提供意見，以進一步優化工具。  

整體聚焦於 **「透過工具包實現 AI 與應用程式的無縫連接」**，強調易用性與擴展性。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqpl7d/we_built_a_toolkit_that_connects_your_ai_to_any/](https://reddit.com/r/AI_Agents/comments/1jqpl7d/we_built_a_toolkit_that_connects_your_ai_to_any/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqpl7d/we_built_a_toolkit_that_connects_your_ai_to_any/](https://www.reddit.com/r/AI_Agents/comments/1jqpl7d/we_built_a_toolkit_that_connects_your_ai_to_any/)
- **發布時間**: 2025-04-04 02:07:21

### 內容

We built a toolkit that allows you to connect your AI to any app in just a few lines of code.

;

toolkit = new MatonAgentToolkit({

app: 'salesforce',

actions: ['all']

})

completion = await openai.chat.completions.create({

model: 'gpt-4o-mini',

tools: toolkit.getTools(),

messages: [...]

})

It comes with hundreds of pre-built API actions for popular SaaS tools like HubSpot, Notion, Slack, and more.

It works seamlessly with OpenAI, AI SDK, and LangChain and provides MCP servers that you can use in Claude for Desktop, Cursor, and Continue.

Unlike many MCP servers, we take care of authentication (OAuth, API Key) for every app.

Would love to get feedback, and curious to hear your though```!


---

## 10. ```
How to make the AI agent understand which question talks about code, which one talks about database, and which one talks about uploading file ?
``` {#10-```
how-to-make-the-ai-agent-understand-which-q}

这篇文章的核心討論主題是：  
**如何改進基於 LangChain 開發的應用程式，使其能更有效地處理用戶與 AI 的多功能互動（如文件上傳、數據庫查詢、代碼庫問答及反饋學習），並探討轉向使用 AI Agent 架構的可行性、實施方法與潛在挑戰。**  

具體要點包括：  
1. **當前功能**：用戶可透過聊天介面與 AI 互動，執行 Excel 文件上傳至數據庫、查詢數據（如銷售報表）、詢問代碼庫問題，以及提供失敗反饋。  
2. **技術痛點**：現有實現方式較為臨時性（hacky），需尋求更穩健的解決方案（如 AI Agent）。  
3. **求助方向**：不限定框架，但希望獲得實作建議（如架構設計、流程優化）與注意事項（如潛在陷阱、改進方向）。  

關鍵詞：**LangChain、AI Agent、數據庫交互、反饋學習、實施挑戰**。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqgqoz/how_to_make_the_ai_agent_understand_which/](https://reddit.com/r/AI_Agents/comments/1jqgqoz/how_to_make_the_ai_agent_understand_which/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqgqoz/how_to_make_the_ai_agent_understand_which/](https://www.reddit.com/r/AI_Agents/comments/1jqgqoz/how_to_make_the_ai_agent_understand_which/)
- **發布時間**: 2025-04-03 20:09:57

### 內容

Hi everyone, recently I have been building some app using Langchain in which you have the option to chat with the AI and either:

- Upload an Excel file and ask the AI to add it to the database.

- Ask questions about the database. Like "How much sales in last year?" or something like that.

- Ask questions about the code base of the app.

- Sometimes when the AI fails, you want to give feedback so that the AI can improve.

I have been doing it in a kinda hacky way, but now I think I should maybe try an AI agent to do it. I hope you guys can provide suggestions, not necessarily about which framework, but I'm looking for things like how to do it, possible pitfalls, etc.


---

## 11. ```
Understanding and Preventing Prompt Injection
``` {#11-```
understanding-and-preventing-prompt-injecti}

這篇文章的核心討論主題是 **「提示注入（prompt injection）的安全風險及其影響」**，主要內容包括：

1. **問題本質**：  
   - 許多AI系統使用「字串拼接」方式構建提示（prompt），可能將外部可控的惡意輸入嵌入系統提示中，導致攻擊者能操控AI執行非預期行為。  
   - 常見原因是「提示填充」（prompt stuffing，將資料直接嵌入系統訊息），雖有可靠性等優點，但也帶來安全漏洞。

2. **風險嚴重性**：  
   - 系統提示（system prompt）權重高於一般用戶輸入，使其成為攻擊主要目標。  
   - 若被注入的AI代理具有敏感工具權限（如存取郵件、日曆等），後果可能極其嚴重。

3. **現狀與反思**：  
   - 作者指出此技術與20年前的滲透測試手法相似，但至今仍廣泛存在，凸顯安全意識不足或防護措施的滯後。  

總結：文章強調開發AI時需兼顧功能與安全性，避免因設計缺陷導致提示注入攻擊。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jpxn6h/understanding_and_preventing_prompt_injection/](https://reddit.com/r/AI_Agents/comments/1jpxn6h/understanding_and_preventing_prompt_injection/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jpxn6h/understanding_and_preventing_prompt_injection/](https://www.reddit.com/r/AI_Agents/comments/1jpxn6h/understanding_and_preventing_prompt_injection/)
- **發布時間**: 2025-04-03 03:36:23

### 內容

Hi everyone,

I've put together a quick tutorial on the basics of prompt injection. For many of you, this is nothing new. It's not new for me either, and in fact, it's somewhat disappointing to see the same techniques I used in my early 20s as a penetration tester still work 20 years later. Nevertheless, some might benefit from this tutorial to frame the problem a little better and to consider how AI agen``` can be built and deployed with security and privacy in mind.

The crux of the video, in case you don't want to watch it, is that many systems these days are constructed using string manipulation and concatenation in the prompt. In other words, some random data (potentially controlled by an attacker) ge into the prompt, and as a result, the attacker can force the system to do things it was not designed to do. This is so common because prompt stuffing (when you put data right inside the system message) is widely used for various reasons, including reliability and token caching. Unfortunately, prompt stuffing also opens the gates to severe prompt injection attacks due to the fact that system promp hold higher importance than normal user messages.

This is, of course, just one type of injection, though I feel it is very common. It's literally everywhere. The impact varies depending on what the system can do and how it was configured. The impact can be very severe if the AI agent that can be injected has access to tools holding sensitive information like email, calendars, etc.


---

## 12. ```
What's Your Expectation for an AI Agent That Can Help You with Data Analysis?
``` {#12-```
what-s-your-expectation-for-an-ai-agent-tha}

这篇文章的核心討論主題是：  
**「如何在現有眾多數據分析AI工具中脫穎而出，打造一個兼具新手友善與進階功能的差異化產品？」**  

具體聚焦於以下兩點：  
1. **用戶痛點挖掘**：詢問用戶在使用現有數據分析AI工具時遇到的問題或不滿（例如操作門檻、功能限制等）。  
2. **功能建議徵集**：尋求潛在用戶對理想工具的具體需求（例如無代碼設計、進階分析能力等），以設計差異化功能。  

最終目標是透過解決現有工具的不足，建立一個能同時滿足「數據分析新手」與「專業人士」需求的AI平台。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jq83ud/whats_your_expectation_for_an_ai_agent_that_can/](https://reddit.com/r/AI_Agents/comments/1jq83ud/whats_your_expectation_for_an_ai_agent_that_can/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jq83ud/whats_your_expectation_for_an_ai_agent_that_can/](https://www.reddit.com/r/AI_Agents/comments/1jq83ud/whats_your_expectation_for_an_ai_agent_that_can/)
- **發布時間**: 2025-04-03 11:25:37

### 內容

Hi guys, looking for some wisdom here. We're currently optimizing an AI Agent designed to assist with data analysis.Simply upload your data and interact with it like a chatbotasking any questions about your dataset.

We want to do this because we'd like to build a no-coding platform for some newbies who just got in the data analysis field while still offering advanced features for professionals who need more in-depth insigh```.

And the question here is obvious: with so many AI Agen``` already available for data analysis,How can we stand out?

So I'm here, would love to know if you have some pain poin when you are interacting with these data analysis AI Agen. Or do you have any suggestions for features that would make such a tool more useful to you? Thanks in a lot!


---

## 13. ```
Give Postgres access to an AI Agent directly (good idea?)
``` {#13-```
give-postgres-access-to-an-ai-agent-directl}

這篇文章的核心討論主題是：  

**如何在「AI Agent 無代碼構建平台」中安全地整合 PostgreSQL 數據庫工具**，具體聚焦於：  
1. **安全性與可控性**：透過預配置的 SQL 查詢（而非開放完整數據庫權限），限制 AI Agent 對數據庫的操作範圍，以降低風險。  
2. **設計方案的可行性**：作者提出初步構想（僅允許用戶配置特定查詢作為工具），並徵求社群對該方法的意見或替代方案。  

關鍵問題：是否應採用「預設查詢」的限制模式？或有其他更平衡的實現方式？

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqjmq1/give_postgres_access_to_an_ai_agent_directly_good/](https://reddit.com/r/AI_Agents/comments/1jqjmq1/give_postgres_access_to_an_ai_agent_directly_good/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqjmq1/give_postgres_access_to_an_ai_agent_directly_good/](https://www.reddit.com/r/AI_Agents/comments/1jqjmq1/give_postgres_access_to_an_ai_agent_directly_good/)
- **發布時間**: 2025-04-03 22:17:21

### 內容

Hi everyone!

We're building an AI Agent no-code builder and will add a Postgres tool node.

Our initial plan is to allow the user to configure only a set of queries and give these pre-configured SQL queries as tools for the AI Agent.

This approach would allow the agent to interact with your database in a safe and controlled way (versus just giving a full DB access).

Does it make sense to you? Otherwise, how would you approach it?


---

## 14. ```
Are AI Agen``` Making Us Too Lazy or Just More Efficient?
``` {#14-```
are-ai-agen```-making-us-too-lazy-or-just-m}

這篇文章的核心討論主題是：**在廣泛依賴AI工具提升效率的同時，人類是否過度外包思考與決策能力，以及如何平衡AI輔助與自主認知能力之間的關係**。  

具體要點包括：  
1. **效率與依賴的兩難**：作者肯定AI（如自主Agent）節省時間的優勢，但也質疑長期依賴可能導致基礎能力的退化（如「連基本事項都需反覆確認」）。  
2. **自我認同的困惑**：用幽默比喻（「我成了實習生嗎？」）反映人類在AI主導流程中的角色模糊化。  
3. **新常態的反思**：探討「交出任務」是否已成為不可逆的趨勢，或需主動建立界限以維持人類的認知主導權。  

整體而言，這是一場關於**科技依賴與人性能力保留的辯證**，並呼籲討論實務中的平衡策略。

- **Reddit 連結**: [https://reddit.com/r/AI_Agents/comments/1jqbmn5/are_ai_agents_making_us_too_lazy_or_just_more/](https://reddit.com/r/AI_Agents/comments/1jqbmn5/are_ai_agents_making_us_too_lazy_or_just_more/)
- **外部連結**: [https://www.reddit.com/r/AI_Agents/comments/1jqbmn5/are_ai_agents_making_us_too_lazy_or_just_more/](https://www.reddit.com/r/AI_Agents/comments/1jqbmn5/are_ai_agents_making_us_too_lazy_or_just_more/)
- **發布時間**: 2025-04-03 14:52:30

### 內容

So heres a thought I keep coming back to.... Am I actually working smarter, or am I slowly ouourcing my entire brain to a bunch of AI agen?

Dont get me wrong, I love the efficiency. At Biz4Group, weve built and tested agen``` that seriously cut down on manual workbut every now and then, I catch myself double-checking something basic and thinking wait, am I the intern now?

Anyone else feel like were getting a little too comfortable handing things off? Or is that just the new normal? Curious how you're all navigating the balance.


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# 總體討論重點

以下是14篇文章的重點條列總結，並附上對應的錨點連結與逐條細節說明：

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### 1. [10 Agent Papers You Should Read from March 2025](#1-10-agent-papers-you-should-read-from-march-2)  
**主題**：AI Agent 最新研究進展與應用  
- **技術架構優化**：長期任務規劃框架（PLAN-AND-ACT）、記憶增強機制（MemInsight）。  
- **多代理系統挑戰**：失敗模式分析（Why Do Multi-Agent LLM Systems Fail?）、協作工作流生成（WorkTeam）。  
- **應用場景突破**：3D遊戲代理（PORTAL）、網頁自動化任務（BEARCUBS基準）。  
- **安全與評估**：網頁代理安全性測試（SAFEARNA）、未知環境適應力評估（EconEvals）。  
- **認知能力探索**：角色扮演中的內部思維建模（ROLETHINK）。  

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### 2. [I Built an AI Agent to find and apply to jobs automatically](#2-i-built-an-ai-agent-to-find-and-apply-to-job)  
**主題**：AI 驅動的求職工具 SimpleApply  
- **功能**：自動篩選職位、匹配技能、預測面試機率。  
- **優勢**：發現冷門遠端職缺、提供匹配分數、三種申請模式（手動/半自動/全自動）。  
- **簡易性**：僅需上傳履歷，AI 處理後續流程。  

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### 3. [Aren't you guys concerned about AI privacy?](#3-aren-t-you-guys-concerned-about-ai-privacy-)  
**主題**：AI 隱私風險與替代方案  
- **隱私風險**：敏感數據（財務、法律）可能被記錄或濫用。  
- **透明度不足**：大型科技公司主導，缺乏開源與獨立審查。  
- **矛盾點**：便利性 vs. 隱私保護的可行性。  

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### 4. [The dev that lost $5,800 building an agent for a client](#4-the-dev-that-lost-5-800-building-an-agent-fo)  
**主題**：AI 自由職業者的客戶失信風險  
- **問題**：未簽合約導致經濟損失。  
- **解決方案**：平台內建合約、分期付款、客戶驗證。  
- **社群共創**：透過案例分享推動制度設計。  

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### 5. [Human in the loop](#5-human-in-the-loop)  
**主題**：人類在自主系統中的監督角色  
- **必要性**：高風險任務需人類介入（如自動駕駛）。  
- **AI 局限性**：即使 99% 準確率，1% 失誤仍可能致命。  
- **未來挑戰**：平衡效率與風險控管。  

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### 6. [I built an open-source Operator that can use computers](#6-i-built-an-open-source-operator-that-can-use)  
**主題**：開源桌面自動化工具 Spongecake  
- **功能**：虛擬桌面（Xfce/VNC）建置與自動化操作。  
- **技術細節**：Docker 容器、Marionette 提取 DOM、併發處理。  
- **目標**：支援缺乏 API 的企業應用（如醫療、供應鏈）。  

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### 7. [I built an MVP that helps you set automated phone calls reminders](#7-i-built-an-mvp-that-helps-you-set-automated-)  
**主題**：提醒服務商業化可行性  
- **功能**：設定電話提醒（如服藥）。  
- **動機**：解決個人需求（父親失智症）。  
- **疑問**：市場需求與訂閱制潛力。  

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### 8. [Tools recommendations for unstructured to structured database](#8-tools-recommendations-for-unstructured-to-st)  
**主題**：非結構化數據轉結構化工具選擇  
- **需求**：GIS 系統需整理郵件、會議記錄等。  
- **工具困惑**：n8n（工作流程） vs. LangGraph（代理）。  
- **關鍵問題**：釐清代理應用與工作流程管理的差異。  

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### 9. [We built a toolkit that connects your AI to any app](#9-we-built-a-toolkit-that-connec```-your-ai-to)  
**主題**：AI 與應用整合工具包 MatonAgentToolkit  
- **優勢**：3 行程式碼整合 SaaS 工具（如 Salesforce、Slack）。  
- **功能