# RisingStack Node.js Tutorials & Resources This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## GPT-Red: OpenAI's Internal Model for Testing Prompt-Injection Defenses DevFeed: [GPT-Red: OpenAI's Internal Model for Testing Prompt-Injection Defenses]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-07-16T13:05:35Z Content type: opinion Language: en Sources: [RisingStack]() Topics: [prompt injection](), [ai safety](), [AI Development](), [OpenAI]() Tags: [agent](), [ai](), [ai-safety](), [openai](), [prompt-injection](), [red-teaming]() ### AI overview The article explains indirect prompt injection and discusses GPT-Red, an internal OpenAI red-teaming model trained to attack other AI models, mainly through prompt injection. It argues that application permissions and tool access are important factors in the resulting security risk. ### Source excerpt Prompt injection is still one of the least comfortable problems in AI development. You can improve your system prompt, restrict tools, validate outputs, and add approval steps before sensitive actions. Still, the model eventually has to read data you do not control. It might browse a webpage, process an email, inspect a repository, or use [...] The post GPT-Red: OpenAI Is Training Models to Break Other Models appeared first on RisingStack Engineering. ## ChatGPT Live and the New Architecture of Voice AI DevFeed: [ChatGPT Live and the New Architecture of Voice AI]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-07-16T12:38:22Z Content type: article Language: en Sources: [RisingStack]() Topics: [voice ai](), [Artificial Intelligence](), [ChatGPT](), [OpenAI](), [systems]() Tags: [ai](), [architecture](), [audio](), [chatgpt](), [engineering](), [gpt](), [here](), [interrupt](), [messages](), [models](), [openai](), [quality](), [speaking](), [speech](), [systems](), [talk](), [tool](), [update](), [voice-ai](), [voices]() ### AI overview The article explains how OpenAI's GPT-Live models power ChatGPT Voice through a full-duplex architecture. The system can listen and speak simultaneously, handle interruptions, pause while users think, and delegate deeper reasoning, web search, or other complex work to another model. ### Source excerpt OpenAI has introduced GPT-Live, a new generation of voice models that now powers ChatGPT Voice. At first, this may sound like another voice-quality update. The voices have been remastered, ChatGPT should interrupt less often, and it can respond more naturally when you pause, change direction or speak over it. But GPT-Live is more than a [...] The post ChatGPT Live and the New Architecture of Voice AI appeared first on RisingStack Engineering. ## GPT-5.6 Sol, Terra and Luna: What Changed in ChatGPT? DevFeed: [GPT-5.6 Sol, Terra and Luna: What Changed in ChatGPT?]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-07-16T12:28:01Z Content type: release Language: en Sources: [RisingStack]() Topics: [ChatGPT](), [OpenAI](), [interfaces](), [API](), [Availability](), [Latency]() Tags: [ai](), [api](), [availability](), [chatgpt](), [cost](), [gpt](), [interfaces](), [openai](), [reasoning](), [release](), [speed]() ### AI overview The article explains GPT-5.6 as a family of three models--Sol, Terra and Luna--and describes how ChatGPT combines model selection with reasoning controls, automatic switching, Work mode and context-dependent availability. It also explains that GPT-5.5 Instant remains the default for fast conversations while GPT-5.6 Sol is used for higher-reasoning settings. ### Source excerpt OpenAI has introduced GPT-5.6, but this release is not just another model replacing the previous one. There are three new models: Sol, Terra and Luna. ChatGPT also has new reasoning controls, a separate Work mode, automatic model switching and different model availability depending on where and how you use the product. This can be confusing [...] The post GPT-5.6 Sol, Terra and Luna: What Changed in ChatGPT? appeared first on RisingStack Engineering. ## Claude Fable 5 Restrictions Exposed Availability Risks for AI Developers DevFeed: [Claude Fable 5 Restrictions Exposed Availability Risks for AI Developers]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-07-06T13:42:50Z Content type: article Language: en Sources: [RisingStack]() Topics: [Claude](), [ai safety](), [Availability](), [API](), [context window](), [long-context]() Tags: [ai](), [ai-safety](), [api](), [availability](), [claude](), [context-window](), [models](), [tool-use]() ### AI overview The article examines how restrictions on Anthropic's Claude Fable 5 and Claude Mythos 5 exposed a new availability risk for software teams. It describes a temporary global suspension of access, Fable 5's return with updated safeguards, and Mythos 5's continued limited availability. The article argues that developers building on frontier APIs must account for government decisions, identity rules, safeguards, and provider policies alongside conventional operational dependencies. ### Source excerpt For years, most AI safety debates focused on model outputs. Could a model generate malware, explain a dangerous process, produce convincing misinformation, or comply with a jailbreak? Claude Fable 5 pushed that discussion toward a harder question: what happens when a model can inspect large codebases, use tools, maintain context across long-running tasks, and work [...] The post Claude Fable 5 Was Restricted for What It Could Do appeared first on RisingStack Engineering. ## GPT-5.5 and GPT Image 2: What Actually Changed DevFeed: [GPT-5.5 and GPT Image 2: What Actually Changed]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-04-29T20:22:17Z Content type: article Language: en Sources: [RisingStack]() Topics: [OpenAI](), [coding](), [computer-use](), [context](), [API]() Tags: [ai](), [api](), [benchmarks](), [coding](), [computer-use](), [context](), [generation](), [gpt](), [image](), [openai](), [reasoning](), [tool-use]() ### AI overview The article compares OpenAI's GPT-5.5 and GPT Image 2 updates, arguing that both emphasize outputs usable with less post-processing. It discusses GPT-5.5's reasoning, coding, tool use, large context window, workflow integration, and reported efficiency improvements, alongside GPT Image 2's image generation and editing capabilities. ### Source excerpt OpenAI has rolled out two updates that on the surface seem like two separate things, but actually share a common thread. GPT-5.5 makes a big jump in terms of reasoning, coding and tool use, while GPT Image 2 focuses on image generation and editing. At first glance, it's not the individual new features that stand [...] The post GPT-5.5 and GPT Image 2: What Actually Changed appeared first on RisingStack Engineering. ## Netflix's VOID: Fixing the Physics Problem in Video Editing DevFeed: [Netflix's VOID: Fixing the Physics Problem in Video Editing]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-04-06T22:41:15Z Content type: article Language: en Sources: [RisingStack]() Topics: [AI Models](), [Artificial Intelligence](), [diffusion-transformers](), [Netflix](), [Simulation]() Tags: [ai](), [ai-models](), [diffusion](), [netflix](), [simulation](), [training](), [video]() ### AI overview The article explains Netflix's VOID model for removing objects from videos while also recomputing their downstream physical effects. It describes VOID as a counterfactual video-generation system using video diffusion and training data produced with physics simulation and human-object interaction data. ### Source excerpt There's a familiar trick in modern video editing with AI - taking an object out, slapping some new background in, - and calling it good. It does the trick for simple things, but it all falls apart the moment the object actually starts to move or interact with anything. Take a domino chain for example, [...] The post Netflix's VOID: Fixing the Physics Problem in Video Editing appeared first on RisingStack Engineering. ## Keeping Meeting Apps Alive in the Background on iOS and watchOS DevFeed: [Keeping Meeting Apps Alive in the Background on iOS and watchOS]() Original publisher: [Read original article]() Author: Roland Published: 2026-03-26T14:55:52Z Content type: tutorial Language: en Sources: [RisingStack]() Topics: [iOS](), [watchOS](), [App](), [Artificial Intelligence]() Tags: [ai](), [apps](), [audio](), [case-study](), [code](), [examples](), [ios](), [meetings](), [pipeline](), [pitfalls](), [production](), [watchos]() ### AI overview This tutorial explains how a real-world meeting app handled reliable background recording and post-recording processing on iOS and watchOS. It covers audio interruptions, resuming recordings, AVAudioSession configuration with mixWithOthers, and background transcription and AI processing, including BGContinuedProcessingTask on iOS 26+. ### Source excerpt Building an app that records meetings, generates transcriptions, and produces AI analysation sounds straightforward - until you try to make it reliable while the user goes in and out of your app, takes calls, plays music, or checks notifications. This post walks through how we handled background recording and post-recording processing on iOS and watchOS [...] The post Keeping Meeting Apps Alive in the Background on iOS and watchOS appeared first on RisingStack Engineering. ## Postfix on Kubernetes: A Step-by-Step Email Guide DevFeed: [Postfix on Kubernetes: A Step-by-Step Email Guide]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2025-09-25T04:12:00Z Content type: tutorial Language: en Sources: [RisingStack]() Topics: [Kubernetes](), [email](), [Authorization]() Tags: [authentication](), [email](), [guide](), [kubernetes](), [postfix](), [spoofing]() ### AI overview A step-by-step guide to running a Postfix email server on Kubernetes. It explains the infrastructure and email-authentication requirements, including a fixed outbound IP address, a domain, PTR and SPF records, and DKIM and DMARC configuration. ### Source excerpt You are in the process of putting together your application. While designing your authorization solution, you realize you will need to send emails to potential clients.Using a third-party service (like SendGrid or Mailgun) to cover your needs for now looks pretty attractive. After all, you don't have any users yet, they offer free tiers, and [...] The post Postfix on Kubernetes: A Step-by-Step Email Guide appeared first on RisingStack Engineering. ## RAG Demystified: From Math to Self-Hosted Code DevFeed: [RAG Demystified: From Math to Self-Hosted Code]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2025-09-18T03:02:08Z Content type: tutorial Language: en Sources: [RisingStack]() Topics: [Retrieval Augmented Generation (RAG)](), [Large Language Model](), [foundation-models](), [Self-hosted](), [Artificial Intelligence]() Tags: [ai](), [code](), [large-language-model](), [open-source](), [rag](), [retrieval-augmented-generation](), [self-hosted](), [use-cases]() ### AI overview This introductory article explains Retrieval-Augmented Generation (RAG), foundation models, and why adding specialized or up-to-date context can extend large language model capabilities. It introduces use cases such as support chatbots and tailored summaries and indicates that later chapters will cover RAG-related code, including self-hosted open-source models. ### Source excerpt In today's AI hype you cannot miss the term "RAG," which stands for Retrieval Augmented Generation. In plain English, it stands for customizing large language model reasoning with your own context and knowledge. I searched a lot of resources and AI-generated content for this fairly simple technique to be explained well. I'm still looking for [...] The post RAG Demystified: From Math to Self-Hosted Code appeared first on RisingStack Engineering. ## Case Study: Modernizing a High-Traffic Streaming Platform with the AHA Stack (HTMX & Alpine.js) DevFeed: [Case Study: Modernizing a High-Traffic Streaming Platform with the AHA Stack (HTMX & Alpine.js)]() Original publisher: [Read original article]() Author: Daniel Bencz Published: 2025-08-29T17:02:07Z Content type: article Language: en Sources: [RisingStack]() Topics: [htmx](), [Web Development](), [Streaming](), [JavaScript](), [Back end](), [Flask]() Tags: [case-study](), [flask](), [htmx](), [js](), [maintainability](), [state-management](), [streaming](), [ux](), [web]() ### AI overview This case study describes modernizing a high-traffic streaming website for responsiveness, maintainability, business continuity, and easier developer onboarding. The existing Python Flask and Jinja site used jQuery; the team retained server-rendered architecture and adopted HTMX with Alpine.js instead of introducing a single-page application. ### Source excerpt Our client, a leading company in the streaming industry, acquired a highly successful indie website with over 50 million unique visitors per month. The site had been built by a single developer who prioritized functionality over maintainability. While the features were mostly bug-free, the design was outdated, and the code relied on aging technologies. The [...] The post Case Study: Modernizing a High-Traffic Streaming Platform with the AHA Stack (HTMX & Alpine.js) appeared first on RisingStack Engineering.