# Custom GPTs & RAG ### About this export | Field | Value | | --- | --- | | **content_type** | lesson | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/ai-foundations/custom-gpts-rag | | **course_slug** | ai-foundations | | **lesson_slug** | custom-gpts-rag | | **markdown_file_url** | /academy/md/courses/ai-foundations/custom-gpts-rag.md | | **generated_at** | 2026-05-18T10:08:42.400Z | > Part of **[AI Foundations](https://www.contentstack.com/academy/courses/ai-foundations)** on Contentstack Academy. **Academy MD v3** — structured for retrieval; no quiz or assessment keys. #### Video details #### At a glance - **Title:** Custom Gpts & Rag - **Duration:** 2m 57s - **Media link:** https://cdn.jwplayer.com/previews/QFDJ1wlQ - **Publish date (unix):** 1714491899 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113941 kbps - video/mp4 · 180p · 180p · 185778 kbps - video/mp4 · 270p · 270p · 246070 kbps - video/mp4 · 360p · 360p · 297229 kbps - video/mp4 · 406p · 406p · 337507 kbps - video/mp4 · 540p · 540p · 469191 kbps - video/mp4 · 720p · 720p · 700410 kbps - video/mp4 · 1080p · 1080p · 1625103 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/QFDJ1wlQ-120.vtt` #### Video transcript There's two ways you can personalize an experience with generative AI tools. First, our custom knowledge bases, which in the case of ChatGPT, are called custom GPTs. Think of it as tweaking a meal recipe to suit your taste. That's what we do with custom GPTs. We start with a basic AI model, which knows a lot about a lot of things, and then we fine tune it with specific data that's unique to your needs. This could be anything from medical knowledge for a healthcare app, to customer service dialogues for support chatbots. The idea is to make the AI better at understanding and generating responses that are super relevant to particular topics or industries. It's refining the tool for a specific use case, instead of the more general-purpose, one-size-fits-all solution. This helps the AI perform exceptionally well where you need it to, by supporting it with additional context for any given topic. Now, let's switch gears and talk about retrieval-augmented generation. Imagine you're having a conversation, and you can pull out your smartphone to look up facts to make sure what you're saying is not just correct, but also super relevant. And you may already do that in your daily life. But that's what retrieval-augmented generation does for AI. While it's chatting with you, it pulls up-to-date information from external sources to boost its replies. This isn't about knowing more in a traditional sense, like what we were doing with custom GPTs, but this is about the AI being able to access a vast amount of information in real-time, ensuring it gives you the most accurate and contextual answers possible. It's particularly useful when the AI needs to handle questions on a wide range of topics and provide answers that are based on the very latest data. Mind you, custom GPTs in ChatGPT are easier to set up using a graphical interface. Other chatbots, like Google's Gemini, require you to create a custom knowledge base through APIs, and working with retrieval-augmented generation often requires another layer of training for the model. Both custom GPTs and retrieval-augmented generation have their unique strengths. If you need an AI that's an expert in a specific field, go with a custom GPT. But if you're looking for an AI that can offer the freshest, most precise information across a broad spectrum, then retrieval-augmented generation is your go-to. It's about matching the right tool for your needs to get the best out of this technology. #### Key takeaways - Connect **Custom GPTs & RAG** back to your stack configuration before moving to the next module. - Capture one concrete artifact (screenshot, Postman call, or code snippet) that proves the step works in your environment. - Re-read the delivery versus management boundary for anything you changed in the entry model. ## Supplement for indexing ### Content summary Custom GPTs & RAG. Custom GPTs & RAG in AI Foundations (ai-foundations). ### Retrieval tags - Custom - GPTs - RAG - ai-foundations - lesson 08 - Custom GPTs & RAG - ai-foundations lesson ### Indexing notes Index this lesson as a primary chunk tagged with lesson_id "08" and topics: [Custom, GPTs, RAG]. Parent course slug: ai-foundations. Use asset_references URLs as thumbnail hints in search results when present. Never surface LMS quiz content or assessment answers from this file. ### Asset references | Label | URL | | --- | --- | | Video thumbnail: Custom GPTs & RAG | `https://cdn.jwplayer.com/v2/media/QFDJ1wlQ/poster.jpg?width=720` | ### External links | Label | URL | | --- | --- | | Contentstack Academy home | `https://www.contentstack.com/academy/` | | Training instance setup | `https://www.contentstack.com/academy/training-instance` | | Academy playground (GitHub) | `https://github.com/contentstack/contentstack-academy-playground` | | Contentstack documentation | `https://www.contentstack.com/docs/` |