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YouTube Videos I want to try to implement!

  • Make AI videos with audio of anyone. Free & offline



    Date: 06/11/2025

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    This video is a fantastic dive into Tencent’s HunyuanVideo Avatar, an open-source project for creating AI-driven talking head videos, and also covers similar tools like Vidu AI. The presenter walks through installation, usage, and demos, showing both online and local implementations. It’s like a playground for generative video!

    What makes this video valuable for me, and potentially for any developer embracing AI, is its practicality. It showcases how to actually use these open-source tools instead of just talking about them. I’m already envisioning how I can integrate these AI avatars into client projects for more engaging presentations, automated training videos, or even internal communication. Seeing the installation process using Git and Conda, plus the alternatives presented, gives a solid understanding of what’s possible and the different avenues for exploration. I’m particularly interested in seeing how well these tools can be integrated into existing Laravel applications to dynamically generate content.

    Honestly, the “try it yourself” aspect is what really sells it. Seeing the presenter’s demos and knowing there’s an open-source project and a sponsored option, Vidu AI, that I can experiment with using the provided code, makes it an immediate to-do. It’s a chance to move beyond theory and get hands-on with the future of video generation, blending traditional coding with cutting-edge AI. I’m especially keen to test how these AI video tools can be integrated into existing marketing workflows, automating personalized video content creation.

  • I Built the Ultimate Browser Agent with No Code (n8n + Airtop)



    Date: 06/09/2025

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    This video showcasing how to build a no-code browser AI agent in n8n using Airtop is seriously inspiring! It’s all about automating browser interactions – clicking buttons, filling forms, scraping data – without writing any code. For someone like me who’s been knee-deep in PHP and Laravel for years, but is now actively integrating AI and no-code solutions, this is pure gold. I can already see how this could replace some of the clunky Selenium scripts and manual processes we currently rely on.

    The real value here lies in its accessibility. Instead of writing complex browser automation code, you’re visually orchestrating actions within n8n using Airtop’s agent capabilities. Imagine using this to automate product research, monitor competitor pricing, or even automatically fill out and submit complex government forms. The possibilities are vast! The video’s breakdown of setting up the agent, connecting Airtop and OpenRouter, and seeing a live browser executing the task is incredibly compelling.

    Honestly, the ease with which you can create a functional AI agent that interacts with the web is amazing. I am already thinking about how this could save us time and resources on client projects, and allow us to focus on higher-level strategic work. I definitely want to try implementing this using the NateHalfOff code, and will likely use my real BestBuy example as my starting point! This video moves AI from theoretical to applicable in a very practical way.

  • Stop Using N8N’s Built-in Scraper (It’s Actually Terrible)



    Date: 06/07/2025

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    Okay, so this video is all about leveling up your web scraping game using n8n, a no-code workflow automation tool. It dives into five different scraping techniques, ranging from basic HTTP requests to more advanced methods like mimicking human behavior and even tapping into internal APIs. Think of it as a practical guide to extracting data from even the most stubborn websites, which is gold when you’re trying to build AI-powered automations.

    Why is this relevant to our AI/no-code journey? Well, data is the lifeblood of any AI model or automated workflow. This video is valuable because it bridges the gap between the raw data out there on the web and our ability to feed it into LLMs or use it to trigger actions in our no-code applications. Imagine using n8n to scrape product data, then feeding that data into a Laravel application via API to auto-update inventory or trigger marketing campaigns. This hands-on approach is key to moving beyond theoretical AI concepts and into practical, impactful implementations.

    I’m genuinely excited to try out some of these techniques, especially the “pretending to be human” method. I’ve wrestled with anti-bot measures before, and the thought of bypassing them using n8n’s automation capabilities is super appealing. Plus, the Shopify scraping section alone could open up a ton of e-commerce automation possibilities. Definitely worth an afternoon of experimenting to see how these methods can streamline my data acquisition processes and unlock new automation possibilities.

  • The Simplest Way to Automate Scraping Anything with No Code (Apify + n8n tutorial)



    Date: 06/07/2025

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    Okay, so this video is all about using Apify and n8n together for no-code web scraping and automation – scraping everything from Instagram profiles to Google Maps. As someone diving deep into AI-enhanced workflows, this immediately caught my eye. We’re constantly looking for ways to streamline data collection and integration, and this looks like a serious time-saver! Think about it, instead of wrestling with custom scraping scripts (which I’ve spent countless hours debugging over the years!), you can leverage pre-built Apify actors and pipe the data directly into n8n for further processing or integration with other systems.

    The value here is clear: rapid prototyping and deployment. The video claims you can set up your first actor in under 5 minutes, and connect it to n8n with simple copy-pasting. That’s huge! Imagine automating lead generation, market research, or content aggregation without writing a single line of code. We could easily integrate scraped data into our Laravel apps via APIs triggered by n8n, essentially building AI-powered data pipelines without the typical coding overhead. They even touch on advanced techniques like polling, which is crucial for handling asynchronous tasks and ensuring data consistency.

    Honestly, the promise of combining Apify’s scraping capabilities with n8n’s automation power is super compelling. I’m keen to experiment with this to see how quickly we can build out some proof-of-concept data-driven features for our clients. Even if it only saves us a few hours per project, that adds up fast, freeing us up to focus on the more complex AI and logic aspects. Plus, that 30% discount on Apify with the code is a nice little incentive to jump in and give it a try. Worth checking out, for sure!

  • Convex Chef: FASTEST + FREE Way To Create HIGH Full-Stack Applications With NO CODE! (Opensource)



    Date: 06/05/2025

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    Okay, so this video is all about Convex Chef, an open-source AI coding agent that helps you spin up full-stack, real-time apps using just a single prompt. No backend setup, no limits, apparently! It leverages the Convex reactive database and throws in some cool features like “Recipes” for instantly adding things like real-time text editors or even AI chat.

    Why is this inspiring? Well, for those of us knee-deep in transitioning to AI-enhanced development, this is a potential game-changer. Think about it – we’re moving away from hand-cranking every line of code and towards orchestrating AI to build the scaffolding for us. The video shows Convex Chef building clones of complex apps like Notion and Slack, all from a single prompt, which is mind-blowing. Plus, with Gemini 2.5 Pro integration for AI-powered coding and a built-in real-time backend, it sounds like a full package.

    Imagine using this to prototype a new feature for a client in a matter of hours instead of days. You could iterate faster, experiment with different UIs, and focus on the core business logic instead of wrestling with infrastructure. The open-source aspect is a huge plus, too. It means we can peek under the hood, contribute, and potentially customize it to fit our specific needs. Honestly, the prospect of building a functional app with essentially a text prompt is too tempting to ignore. I’m downloading it now to give it a spin – who knows, it could become a staple in my AI-powered toolkit.

  • My new FAVORITE way to use Supabase



    Date: 06/04/2025

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    Okay, this Supabase MCP Server video is seriously cool, and here’s why I think it’s worth your time. It shows how to give your AI agent deep context about your Supabase project, essentially letting it “understand” your backend in the same way it groks file structures and code. Jon Meyers walks through setting up the Supabase MCP server within Cursor IDE and then uses Claude to whip up an Edge Function that intelligently scrapes recipe websites. Forget the ad-ridden, SEO-spam versions – this pulls out just the core recipe data and stores it in a Postgres database, then displays it in a Next.js app.

    The real value for us, as developers moving towards AI-assisted workflows, is how it streamlines development and automation. Imagine the possibilities! Instead of manually writing complex scrapers and data cleaning scripts, you can leverage AI to handle that heavy lifting. I’ve spent countless hours wrestling with web scraping in the past (and honestly, who hasn’t?), so seeing this level of automation makes me genuinely excited. This isn’t just about scraping recipes; it’s about connecting AI to your database schema, table relationships, and even your custom functions, allowing it to assist in tasks you hadn’t even imagined.

    I’m already brainstorming ways to apply this to our internal tools and client projects. Think automated data migrations, intelligent report generation, or even AI-powered API development. This video gives a practical, hands-on example of how to bridge the gap between LLMs and real-world development tasks. The combination of Supabase’s backend capabilities and AI coding tools like Claude could seriously boost productivity and unlock new levels of automation, it’s definitely worth experimenting with.

  • YOU WON’T BELIEVE How Simple Building AI Agents Gets with Flowise v3



    Date: 06/04/2025

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    Okay, so this video is all about leveraging Flowise v3 to build AI agents using a no-code interface. It shows you how to create an assistant that can do everything from searching the web and answering questions from uploaded documents to connecting with external APIs like Gmail. It also dives into setting up document stores, handling data chunking with OpenAI embeddings, and integrating Postgres vector databases (Supabase). The real kicker is the focus on practical tools like SERP API and Composio to truly extend what your AI agent can do.

    Why is this video gold for us? Because it’s a tangible step towards blending traditional development with AI-powered automation. We’re constantly looking for ways to reduce boilerplate and speed up development cycles. Seeing how Flowise v3 simplifies the creation of sophisticated AI agents with zero code is incredibly appealing. Imagine being able to prototype and deploy a complex workflow in a fraction of the time, without getting bogged down in the nitty-gritty of code.

    Thinking about real-world applications, this opens doors to things like automated customer support systems that can pull information from various sources, or even intelligent data processing pipelines that can analyze documents and trigger actions in other applications. The Gmail integration alone has me thinking about automating email workflows based on document content. I’m personally excited to experiment with Flowise to create a personalized research assistant that automatically aggregates information from different sources and summarizes it for me. The video’s clear, step-by-step approach makes it feel immediately accessible, and honestly, that’s half the battle when diving into new tech!

  • Getting Started with Flowise v3 (No-Code AI Builder)



    Date: 06/03/2025

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    Okay, this Flowise v3 video looks seriously useful, especially given the direction I’m pushing my own workflow! Essentially, it’s a deep dive into building AI-powered apps using a no-code platform. Think visual flowcharts connecting LLMs (like OpenAI), custom knowledge bases, and even human-in-the-loop steps. It’s positioned as a real alternative to tools like N8N and Zapier, putting AI capabilities front and center.

    The reason this is valuable for someone like me (and potentially you) is that it bridges the gap between traditional coding and leveraging the power of AI. We can use our existing knowledge of APIs and system design, but visually orchestrate complex AI interactions without writing tons of boilerplate code. Imagine building an automated customer support system powered by a custom-trained knowledge base without spending weeks on intricate Python scripts. This video walks you through the basics from local installation to creating your first AI agent, handling memory, state, debugging and more!

    What’s got me excited is the potential for rapid prototyping and experimentation. Instead of getting bogged down in the weeds of low-level implementations, I can focus on the logic of the AI workflow. Building AI agents and integrating them with other tools becomes something that is actually doable. I’m definitely going to spin up a local instance and see how quickly I can adapt some of my existing projects. The promised easy integration with custom APIs and the document store functionality are huge wins too! Honestly, for a developer looking to embrace the AI wave, this seems like a solid place to start playing.

  • AG-UI: First-Ever Agent UI – Bring Agents into Frontend Applications! (Opensource)



    Date: 06/03/2025

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    Okay, this AG-UI video looks seriously interesting, especially for how I’m aiming to streamline AI integrations into my projects. In essence, it’s about AG-UI, an open-source protocol to create frontends for AI Agents that you can stream events to—messages, typing indicators, the whole shebang. Think of it as a bridge connecting your LLM-powered agent’s brain to a slick, real-time UI.

    Why does this pique my interest? Well, I’ve been wrestling with clunky, custom solutions for displaying AI interactions. This video walks through setting up a FastAPI backend that’s AG-UI-compatible and then connecting it to a CopilotKit frontend. So imagine moving beyond basic API calls and actually streaming the AI’s “thoughts” as they happen—no more stale, static responses! This aligns perfectly with the AI-enhanced workflows that I’m migrating to.

    The real kicker is the potential for automating UI development around AI agents. Instead of hand-crafting chat interfaces every single time, AG-UI provides a standardized protocol. I’m already envisioning how I can adapt this to some of my existing Laravel projects that use LLMs for content generation and customer support. Instead of wrestling with SSE implementation myself, I can leverage a ready-made solution. I’m gonna dive into this!

  • Self-Host Supabase Edge Functions



    Date: 06/02/2025

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    Okay, this video on Supabase Edge Functions on Fly.io is gold for any of us transitioning to AI-driven workflows. Jon Meyers walks through deploying a Supabase Edge Function, essentially a serverless function, on Fly.io using Deno and Oak middleware. This means we can ditch some of the heavier backend lifting and focus on orchestrating logic with tools like LLMs.

    Why’s it valuable? Because it showcases how to self-host these functions, giving us control and flexibility. Instead of being tied to a specific cloud provider’s serverless platform, we can deploy these lightweight functions anywhere, including environments where we’re integrating AI agents or no-code solutions. Imagine using an LLM to generate the core logic within the Edge Function, then deploying it to a cost-effective and scalable platform like Fly.io, orchestrated entirely by AI. We can have AI write the function, write the tests, and orchestrate the deployment!

    The real-world application is huge. Think automated content generation, dynamic API endpoints, or even real-time data transformation triggered by AI models. By experimenting with this, we’re not just learning about Supabase or Fly.io; we’re building a foundation for a whole new level of automation and intelligent applications. It’s definitely worth carving out an hour to play with!