Try@DailyAi.Studio

Category: Try

  • The KEY to Building Smarter RAG Database Agents (n8n)



    Date: 08/06/2025

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    Okay, these videos on building an AI agent that queries relational databases with natural language are seriously cool and super relevant to what I’ve been diving into lately. Forget those basic “AI can write a simple query” demos – this goes deep into understanding database structure, preventing SQL injection, and deploying it all securely.

    The real value, for me, is how they tackle the challenge of connecting LLMs to complex data. They explore different ways to give the AI the context it needs: dynamic schema retrieval, optimized views, and even pre-prepared queries for max security. That’s key because, in the real world, you’re not dealing with toy databases. You’re wrestling with legacy schemas, complex relationships, and the constant threat of someone trying to break your system. Plus, the section on combining relational querying with RAG? Game-changer! Imagine being able to query both structured data and unstructured text with the same agent.

    Honestly, this is exactly the kind of workflow I’m aiming for – moving away from writing endless lines of code and towards orchestrating AI to handle the heavy lifting. Setting up some protected views to prevent SQL injection sounds like a much better security measure than anything I could write by hand. It’s inspiring because it shows how we can leverage AI to build truly intelligent and secure data-driven applications. Definitely worth experimenting with!

  • Run OpenAI’s Open Source Model FREE in n8n (Complete Setup Guide)



    Date: 08/06/2025

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    Okay, this video on OpenAI’s new open-source model, GPT-OSS, is exactly the kind of thing I’ve been diving into lately! It’s all about setting up and using this powerful model locally with Ollama, and also exploring the free Groq cloud alternative—and then tying it all together with N8N for automation. Forget those crazy API costs!

    Why is this cool? Well, for one, we’re talking about running models comparable to early frontier models locally. No more constant API calls! The video demonstrates how to integrate both local and cloud (Groq) options into N8N workflows, which is perfect for building AI agents with custom knowledge bases and tool calling. Think about automating document processing, sentiment analysis, or even basic code generation – all without racking up a huge bill. The video even tests reasoning capabilities against the paid OpenAI models! I’m already imagining using this setup to enhance our internal tooling and streamline some of our client onboarding processes.

    Frankly, the biggest win here is the democratization of access to powerful AI. The ability to experiment with these models without the constant fear of API costs is massive, especially for learning and prototyping. Plus, the N8N integration makes it practical for real-world automation. It’s definitely worth setting aside an afternoon to experiment with. I’m particularly excited about the Groq integration – blazing fast inference speed combined with N8N could be a game-changer for certain real-time applications we’re developing.

  • The end of me, new #1 open-source AI, top image model, new GPT features, new deepfake AI



    Date: 08/03/2025

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    Okay, so this video is a rapid-fire rundown of some seriously cool AI advancements – everything from Tencent’s Hunyuan World (a generative world model!) to GLM-4.5, which boasts improvements over GPT-4, and even AI-powered motion graphics tools. It’s basically a buffet of what’s new and shiny in the AI space.

    Why is this useful for us, moving towards AI-enhanced development? Well, first, it’s about awareness. We need to know what’s possible. Seeing things like X-Omni (for AI-driven UI/UX) and the FLUX Krea dev tool (AI-powered image generation) immediately sparks ideas about how we can automate front-end tasks, create dynamic content, or even rapidly prototype interfaces. Imagine using something like Hunyuan World to generate realistic test environments for our applications. The key is to keep our minds open to how these tools could be integrated into our existing workflows, potentially saving us hours on design, testing, and even initial coding.

    Honestly, staying on top of this stuff can feel like drinking from a firehose, but that’s why these curated news roundups are so valuable. It’s worth experimenting with a couple of these tools – maybe that Hera motion graphics tool for spicing up our UI or diving into GLM-4.5 to see if it can streamline our code generation. The goal isn’t to replace ourselves with AI, but to find those 20% of tasks that AI can handle, freeing us up to focus on the higher-level problem-solving and architecture that makes development truly rewarding. Plus, keeping our skills current means we can deliver more value to clients and stay ahead of the curve.

  • Ollama Just Released Their Own App (Complete Tutorial)



    Date: 08/01/2025

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    This video showcasing Ollama’s new ChatGPT-style interface is incredibly inspiring because it directly addresses a pain point I’ve been wrestling with: simplifying local AI model interaction. We’re talking about ditching the terminal for a proper UI to download, run, and chat with models like Llama 3 and DeepSeek R1 – all locally and securely. Forget wrestling with command-line arguments just to experiment with different LLMs! The ability to upload documents, analyze them, and even create custom AI characters with personalized prompts opens up so many possibilities for automation and tailored workflows.

    Think about it: I could use this to build a local AI assistant specifically trained on our company’s documentation, providing instant answers to common developer questions without exposing sensitive data to external APIs. Or maybe prototype a personalized code reviewer that understands our team’s coding style and preferences. Plus, the video touches on optimizing context length, which is crucial for efficient document processing. For anyone who, like me, is trying to move from traditional coding to leveraging local AI, this is a game-changer.

    It’s not just about ease of use, though that’s a huge plus. It’s about having complete control over your data and AI models, experimenting without limitations, and truly understanding how these technologies work under the hood. The video makes it seem genuinely straightforward to set up and start playing with, which is why I’m adding it to my “must-try” list this week. I’m especially keen on testing DeepSeek R1’s reasoning capabilities and exploring how custom system prompts can fine-tune models for very specific tasks. This could seriously accelerate our internal tool development!

  • Claude Projects: AI That Actually Does My Work



    Date: 07/31/2025

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    Okay, this video on building AI agent teams with Claude and a multi-agent framework? Seriously inspiring stuff for anyone like us diving headfirst into AI-enhanced development.

    Here’s the gist: it’s not just about firing off prompts to an LLM anymore. The video shows how to use Claude Projects (from Anthropic) alongside a multi-agent framework to create a team of AI agents that tackle complex tasks collaboratively. We’re talking about automating everything from social media content creation (with tailored mentions!) and lead qualification right out of Gmail, to even designing thumbnails. And the coolest part? It connects directly to Zapier, unlocking a world of integrations. Imagine your agents updating databases, sending emails, triggering other automations – all on their own.

    Why is it valuable? Because it gives us a glimpse into a future where we’re orchestrating AI, not just coding every single line ourselves. Instead of spending hours on repetitive tasks, we could define the high-level goals, set up the agent team, and let them handle the grunt work. Think about applying this to automating API integrations, generating documentation, or even testing. This isn’t about AI taking our jobs; it’s about AI amplifying our abilities. I’m definitely experimenting with this; the idea of having AI agents handle tedious tasks while I focus on the bigger architectural challenges? Sign me up.

  • Supabase Storage and N8N 005



    Date: 07/29/2025

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    Okay, this video on integrating n8n with Supabase for file uploads is seriously inspiring, and here’s why. It’s all about automating file management with a focus on the practical details that often get overlooked. The video dives deep into using n8n’s HTTP node to upload files to Supabase Storage, handling everything from authentication to generating signed URLs and dealing with errors. Crucially, it covers both public and private buckets, which is essential for any real-world app dealing with different levels of data sensitivity.

    Why is this valuable for us as developers shifting to AI and no-code? Well, think about it: a huge part of AI workflows involves handling data, often files like images or documents. This video shows you how to build a robust, automated pipeline for managing that data in Supabase. It’s not just theory; it walks through the tricky parts, like dealing with binary data and setting up the HTTP node correctly. Plus, the examples of connecting Supabase real-time events to n8n for triggering automations? Gold! Imagine automatically kicking off an image processing workflow in response to a new file upload – that’s a game changer for efficiency.

    For me, the most exciting part is the potential for real-world application. The video touches on use cases with mobile apps, web interfaces, and even image-to-insight AI workflows. I can immediately see how this could streamline data ingestion and processing in a ton of projects. I’m definitely going to experiment with hooking up n8n to a Supabase-backed app for automated image analysis. Being able to secure files while triggering automations? Sign me up!

  • ChatGPT Agent Alternative: The Best AI General Agent Right Now that DO ANYTHING!



    Date: 07/29/2025

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    Okay, so this video is basically a head-to-head comparison between OpenAI’s ChatGPT Agent and DeepAgent by Abacus AI. It puts them through real-world scenarios like generating PowerPoints, automating tasks, and evaluating the quality of their responses. The surprising part? DeepAgent seems to come out on top, showcasing its ability to build apps, write reports, and even generate dashboards autonomously.

    For someone like me, who’s knee-deep in transitioning from traditional Laravel development to AI-enhanced workflows, this is gold. We’re talking about potentially replacing tedious tasks – like building basic dashboards or generating reports – with AI. Imagine automating all that boilerplate code and freeing up time to focus on the core logic and innovation! The video highlights how DeepAgent could be that “general-purpose AI agent” we’ve been waiting for, and seeing a direct comparison to ChatGPT Agent gives me a clearer picture of what’s possible.

    What really makes this video worth checking out, though, is the potential for real-world application. I’m already brainstorming how I could use a tool like DeepAgent to automate API integrations, generate documentation, or even build simple CRUD interfaces for internal tools. It’s about moving beyond just using AI for code suggestions and embracing a future where AI agents handle entire development workflows. I’m definitely going to experiment with DeepAgent to see if it can streamline some of my projects and ultimately, deliver more value to my clients.

  • VEO-3 has a Secret Super Power!



    Date: 07/29/2025

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    Okay, so this video is all about leveling up your AI video game with visual prompting and Runway’s new “Aleph” model. Basically, instead of just typing prompts, you’re drawing and annotating directly on images to guide AI video generation. Think adding speech bubbles to characters or drawing motion paths for dragons to follow. It also gives you a sneak peek at Runway’s new in-context video model, Aleph, for video-to-video edits and object removal.

    This is gold for us developers diving into AI-enhanced workflows! We’re always looking for ways to get more granular control over AI tools, and visual prompting seems like a natural evolution. Imagine using this to prototype animations for a client, rapidly iterating on camera angles, or even generating complex visual effects with more precision.

    The coolest part? The video shows how to get started with free tools like Adobe Express. It’s a practical guide to experimenting with these cutting-edge techniques today. I’m particularly excited to explore how visual prompting can streamline the creation of marketing materials for my own projects, and even integrate it into some of the no-code automation workflows I’ve been building with tools like Zapier. Definetly time to start experimenting with visual prompting!

  • The BEST 10 n8n Apps Released in 2025 (I Wish I Knew Sooner)



    Date: 07/28/2025

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    Okay, so this video’s all about “Top 10 n8n Tools for 2025.” It gives a rundown of new nodes and apps to supercharge your n8n workflows, with a focus on AI tools. We’re talking things like integrating Google Gemini, AI voice with ElevenLabs, web scraping with Apify, and even AI-powered search using Perplexity. I’m seeing a lot of LLM integration, with things like Mistral and DeepSeek making an appearance too.

    Why’s it interesting for us? Because it’s a direct look at how AI is being plugged into no-code platforms like n8n. Instead of building everything from scratch in Laravel or PHP, you’re orchestrating these AI services. I can immediately see using this to automate marketing content generation, improve data enrichment processes, or even build more intelligent customer support flows. Think about it: automating lead qualification using AI to analyze social media profiles scraped with Apify, then generating personalized outreach emails using an LLM through n8n. Boom!

    I think what makes this video particularly worth checking out is how practical it is. It’s not just about the “what,” but the “how” of integrating these AI tools into your existing workflow. Seeing someone demonstrate how to connect these services in n8n sparks ideas for how I could apply them to projects I’m working on right now. Definitely giving this a watch and experimenting!

  • Building an AI Agent Swarm in n8n Just Got So Easy



    Date: 07/27/2025

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    Okay, this video is seriously inspiring because it tackles a challenge I’ve been wrestling with: how to build truly intelligent AI systems without getting bogged down in code. The creator demonstrates how to build an AI agent swarm using n8n, a no-code automation platform. The key is modularity. Instead of one giant, complex AI, you have a “parent” agent delegating tasks to specialized “sub-agents.” Think of it like a team of experts focused on their specific domains, all coordinated to solve a bigger problem.

    For developers like us transitioning into AI-enhanced workflows, this is gold! We’re constantly looking for ways to streamline development and improve accuracy. Agent swarms address both. By breaking down complex tasks, we reduce prompt bloat and increase context accuracy, which are major headaches when dealing with LLMs. Plus, the video highlights how n8n’s visual workflow makes debugging and iteration much faster. It really resonated with me; managing sprawling if/else trees in code feels like ancient history compared to this!

    The potential applications are huge. Imagine automating complex customer support flows, building sophisticated data analysis pipelines, or even creating self-optimizing marketing campaigns. What I find super exciting is that this isn’t just theory. The video provides resources to download and experiment with. I’m already thinking about how I can adapt this approach to my current project, which involves orchestrating multiple LLM calls for content generation. It’s definitely worth carving out some time to dive in and see how agent swarms can up our game.