Xavier Blary’s Post

**Step-by-Step: RAG AI Agents in n8n** Dive into the world of AI automation with this comprehensive tutorial on creating Retrieval-Augmented Generation (RAG) AI Agents using n8n! Learn how to seamlessly integrate real-time data retrieval with workflow automation to build intelligent, context-aware chatbots. Perfect for developers and tech enthusiasts looking to enhance their AI skills. Watch the full tutorial here: [YouTube Link](^https^://https://lnkd.in/dqnqGTw3)

Watch this lightning demo with Neil Dixit for an overview of Glimpse, showcasing features such as AI question creation, open-ended coding AI engine, Persona chat, segment chat, and data enrichment tools. Available for free, on-demand.

In this post on Medium, I overview a simple implementation of speech-to-text and text-to-speech technology alongside a generative AI agent capable of performing google searches autonomously using (mostly) open-source tools.

Imagine a digital worker that doesn’t just sit there waiting for instructions but actively engages with tasks, learns from experiences, and even follows up on its own. Sounds like something out of a sci-fi movie, right? Welcome to the world of AI agents! Unlike traditional software that merely executes commands, AI agents are designed to think, learn, and act autonomously. They’re like the overachievers of the digital realm, capable of not just processing information but also making decisions based on that information.

AI is eating the world (of software, too) - some of the world's largest corporations already spend north of $60M per year on enterprise LLMs, trying to automate previously human-led jobs and invent new, AI-specific ones. Stuff that's already automated is not immune as well - several companies reported divesting from traditional enterprise software like CRMs and trusting those business processes and data to AI. While industries are scrambling for ROI and demonstrate mixed results (at least as of today), some CTOs are completely reimagining their IT strategy, putting AI at the helm. What is your opinion on AI-centric vs traditional IT?

The Rise of AI Agents: Beyond RAG and Towards Autonomous Reasoning In the rapidly evolving world of AI, one term that has gained significant traction is Agents. Businesses are investing heavily in this technology, yet many struggle to grasp the fundamental differences between standard Retrieval-Augmented Generation (RAG) and Agents. So, what sets them apart? RAG vs. Agents: The Key Difference At its core, RAG enhances Large Language Models (LLMs) by extending their knowledge with external data sources. While LLMs are inherently limited by their training data, RAG enables them to retrieve relevant information from databases, APIs, or documents, making their responses more up-to-date and contextually relevant. However, RAG lacks reasoning capabilities—it merely fetches information and presents it. This is where Agents come in. The Power of AI Agents Agents introduce an additional decision-making layer on top of LLMs. Instead of just retrieving information, Agents analyze, reason, and act based on the retrieved data. They can: ✅ Plan and execute multi-step actions ✅ Interact with external tools, APIs, and databases dynamically ✅ Adapt and refine responses based on the evolving context ✅ Automate complex workflows beyond simple query-answering #Agents#LLM

You know what's better than being on camera? Letting an AI do the talking for you! 🪄📢 I shared a video demo the other day showcasing how PrimeRFP helps quickly find contract opportunities across thousands of sources. Well, I believe I just one-upped myself... I created a new demo video highlighting PrimeRFP's generative AI assistant, currently called PrimeBot. But I think we'll rebrand it as PRAI - it's a bit less boring! Except this time, I used an AI voiceover instead of me on camera. My voiceover skills didn't make the cut this time. 😆 But if an AI can upstage my videography talents, it must be pretty impressive! As much as I enjoy being on camera (ha!), I'm really excited about the potential of AI to supercharge proposal and capture management productivity for #smallbusinesses and #GovCon. Give the new "PRAI" video a watch and let me know - would you welcome an AI assistant like this or is it a bridge too far?

Prompts are not enough. "Prompt libraries" are a subpar way to structure and share AI workflows. We need empowering, yet simple tools to master our own workflows and share them. That's why I'm building Esquisse 

✨#GPT-4o brings a whole host of new features and improvements to the table, here’s a few: 1️⃣ Multimodality (hence the “o” at the end for omni): This model can take in and output video, audio, text and images. 2️⃣ 2x faster in text tasks: make your AI applications and automations faster than ever before. 3️⃣ 16x quicker in #VoiceAI applications: assistants such as Vapi AI will get a huge boost from this. 4️⃣ 2x cheaper: the lowered prices of this model make it a no-brainer for everyone! In my video below, I discuss the real difference between the old ways of #AI and GPT-4o. Check it out below: https://lnkd.in/duNp6iNc

Published my thoughts on the current AI hype cycle and how the real ROI will be unlocked for the modern enterprise