RT Avi Chawla (@_avichawla)How to build a RAG app on AWS!The visual below shows the exact flow of how a simple RAG system works inside AWS, using services you already know.At its core, RAG is a two-stage pattern:- Ingestion (prepare knowledge)- Querying (use knowledge)Below is how each stage works in practice.> Ingestion: Turning raw data into searchable knowledge- Your documents live in S3 or any internal data source.- Whenever something new is added, a Lambda ingestion function kicks in.- It cleans, proce ...

Core Viewpoint - The emergence of AI Agent Sandbox technology marks a new era in AI capabilities, particularly with the introduction of OpenAI's Code Interpreter, which allows AI to execute code and perform data analysis, raising significant security concerns [1][13]. Group 1: Traditional Sandbox Era - The concept of sandboxing originated in the 1990s to safely analyze malicious software without risking system infection [2]. - Cuckoo Sandbox became a notable example, allowing researchers to observe malware behavior in a controlled environment [2]. - Virtualization technologies like VMware and Xen enhanced sandbox capabilities but introduced performance issues due to resource consumption [2][3]. Group 2: Cloud-Based Programming Revolution - The late 2010s saw a shift towards cloud-based development environments, exemplified by CodeSandbox, which provided a complete IDE in the browser [6]. - Replit focused on simplifying programming for beginners by offering a zero-configuration environment, addressing common pain points in coding education [7][9]. - AWS Lambda introduced serverless computing, allowing developers to upload code without managing infrastructure, which laid the groundwork for future innovations [10][11]. Group 3: AI Agent Sandbox Era - The release of ChatGPT in late 2022 and the subsequent Code Interpreter feature in 2023 represented a significant advancement in AI capabilities, enabling AI to not only generate but also execute code [13][14]. - AI-generated code presents unique challenges, including unpredictability and susceptibility to injection attacks, necessitating specialized sandbox solutions [15][16]. - E2B emerged to provide a simplified API for sandboxing, utilizing Firecracker technology to ensure rapid and secure code execution [18][22]. Group 4: Rise of Domestic Agent Sandboxes - PPIO Agent Sandbox, built on Firecracker MicroVM, offers a tailored environment for AI Agents, ensuring secure code execution while being cost-effective [22][24]. - PPIO's compatibility with E2B protocols allows for seamless integration into existing frameworks, enhancing its utility for AI applications [23]. - The rapid development of both E2B and PPIO indicates a growing ecosystem around AI Agent sandbox technologies, driven by market demand [30].