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YouTube Videos I want to try to implement!

  • This might be OpenAI’s New Open-Source Model…

    News: 2025-08-01



    Date: 08/01/2025

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    Just when we thought we had seen it all, a new player entered the scene: Horizon (Alpha). This mysterious AI model just dropped on OpenRouter, and the initial benchmarks are hard to ignore. It’s outperforming both GPT-4o and Claude 3 Opus. What’s even more intriguing is that it didn’t come from one of the big labs like OpenAI or Anthropic. Its origins are a bit of a puzzle, but it looks like it might be an in-house model from the OpenRouter team.

    For those of us working with no-code tools like n8n, this is a game changer. We now have access to a new state-of-the-art model through an API aggregator, giving us another powerful option for our automations. This really challenges the notion that only the big players can deliver top-tier foundation models. It feels like we’re witnessing a shift in the AI landscape, and I’m excited to see where this goes.

  • Showrunner AI Creates ENTIRE TV SHOWS | Hollywood is cooked… | Quickstart Tutorial

    News: 2025-08-01



    Date: 08/01/2025

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    This weekly AI news roundup from Wes Roth is a great, no-fluff overview of what’s happening with the major players like OpenAI, Google, Anthropic, and NVIDIA. I found it valuable because it connects the dots between high-level announcements and the practical tools we use. Every model improvement or hardware breakthrough from these giants directly impacts the capabilities available in our no-code and automation platforms. Watching this gives you a strategic preview of the features and power that will soon be integrated into tools like n8n. It’s less about the headlines and more about understanding where the building blocks for our future projects are coming from.

  • Ollama Just Released Their Own App (Complete Tutorial)

    News: 2025-07-31



    Date: 08/01/2025

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    Ollama has just launched its own official chat interface, finally moving local AI out of the command line and into a user-friendly app. This is a significant step forward, making it simple for anyone—not just developers—to download, manage, and interact with open-source models like Llama 3.2 and DeepSeek R1 directly on their machine. The interface supports key productivity features, like uploading documents for local analysis and creating custom models with specific system prompts for tailored tasks. For anyone building automations or exploring AI workflows, this dramatically lowers the barrier to entry for testing and using models securely and privately, without relying on external APIs. It effectively provides a free, private ChatGPT-like experience that anyone can set up in minutes.

  • 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.

  • Walmart Blasts Past Agent Experimentation

    News: 2025-07-30



    Date: 07/30/2025

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    This story from Walmart caught my eye because it shows the next evolution of automation, moving far beyond simple, linear workflows. They’ve gone from experimenting with individual AI agents to deploying “agent orchestration”—a unified system where four “super agents” manage specialized sub-agents across their entire operation. For those of us building with tools like n8n, this is a fascinating glimpse into the future; it’s like moving from building individual automations to designing the AI manager that coordinates them all to solve complex business challenges.

    The results show this is no longer just a concept, with a 40% boost in customer support speed and an 18-week reduction in fashion production timelines. This shift from siloed bots to a coordinated agentic system is a powerful signal of where AI-driven productivity is heading. It’s a practical blueprint for how large-scale, intelligent automation can be achieved, moving from task-specific helpers to a truly integrated operational brain.

  • 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.

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

    News: 2025-07-29



    Date: 07/29/2025

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    I’ve been following the AI agent scene for a while, hoping to find a tool that can truly manage complex, multi-step business tasks from start to finish. This video offers a fantastic comparison between OpenAI’s new agent and a strong contender called DeepAgent from Abacus AI. The tests focus on real-world jobs that matter to us, like generating reports, automating workflows, and building dashboards. What really stood out was DeepAgent’s ability to work autonomously across different systems without needing constant hand-holding.

    For anyone who builds with tools like n8n, this is a compelling look at the next frontier of automation. It shows a system capable of tackling an entire project, not just a single, predefined task. This is a significant step toward the kind of hands-off, intelligent automation that lets small teams achieve more with less friction.

  • VEO-3 has a Secret Super Power!

    News: 2025-07-28



    Date: 07/29/2025

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    I’ve been testing a new AI video technique called “visual prompting,” and it’s a fascinating step up in creative control. The core idea is to move beyond text prompts by drawing instructions—like arrows for camera pans or circles for animation—directly onto your source image. This workflow, using free tools like Adobe Express, gives non-developers a much more direct and intuitive way to guide the AI, solving the ambiguity of text-only commands. It’s a great example of how we’re gaining more granular control over our generative tools.

    On that note, the video also previews Runway’s upcoming “Aleph” model, which looks like in-painting on steroids for video. Its ability to perform seamless video object removal could be a massive time-saver, simplifying what was once a complex post-production task for any creator or small team.