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YouTube Videos I want to try to implement!

  • 25 Hidden n8n Features That Save Hours of Work



    Date: 06/22/2025

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    Okay, so this video is basically a treasure trove of n8n tips and tricks from someone who’s clearly been in the trenches with it for a year. It’s like getting insider knowledge straight from a seasoned user, covering everything from basic efficiency hacks to more advanced automation techniques. Think of it as a “level up your n8n game” guide.

    Why’s it valuable for us? Because as we’re shifting towards AI-enhanced development, tools like n8n are becoming essential for orchestrating workflows between different services and LLMs. We can use this to build custom AI agents, connect them to our Laravel apps, automate tedious tasks, and basically glue everything together without writing a ton of code. The video’s progression, starting with simple tips and moving to advanced ones, acknowledges that learning curve we’re all facing.

    Imagine this: using these n8n tricks to automate the process of training a custom LLM on new data, then deploying it to a Laravel API endpoint. Or even simpler, automating lead generation and follow-up sequences based on specific triggers in our applications. Honestly, what makes this worth experimenting with is the potential time saved and the ability to focus on higher-level logic instead of getting bogged down in the nitty-gritty details of workflow construction. It’s about working smarter, not harder, which is the whole point of embracing AI in our workflow, right?

  • I was wrong about Claude Code (UPDATED AI workflow tutorial)



    Date: 06/22/2025

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    Okay, so Chris is building productivity apps like Mogul, Ellie, Luna, and Lily, and in this video, he’s diving deep into his updated AI coding workflow using Claude Code. He explains why he switched from Cursor and shares his thoughts on the whole AI coding landscape. Crucially, he claims this new setup makes him 20x faster as a developer.

    For those of us transitioning into AI-assisted development, this is gold! Chris outlines his 9-step Claude Code workflow and even provides concrete examples where Claude Code outperformed Cursor’s agents. He gets into the nitty-gritty of which model he’s using and explores the downsides of Claude Code – it’s not all sunshine and roses, apparently. He caps it off with who he thinks should be using it. The fact that he switched from one AI tool to another and provides a clear, step-by-step breakdown of his reasoning and workflow is super valuable.

    This isn’t just theoretical; Chris is building real productivity apps! Imagine applying his workflow to automate tedious tasks in Laravel, generate boilerplate code, or even refactor legacy code. He’s essentially showing us how to leverage LLMs for a significant productivity boost. Honestly, the potential to 20x your output is reason enough to experiment! I’m eager to see how this integrates with my existing Laravel projects, especially with the promise of such a dramatic speed increase. Worth a try, right?

  • I was wrong about Claude Code (UPDATED AI workflow tutorial)



    Date: 06/22/2025

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    Okay, this video by Chris about his updated AI coding workflow using Claude Code is seriously inspiring, and here’s why. As someone neck-deep in transitioning to AI-enhanced development, seeing a fellow indie developer go all-in and achieve a “20x faster” speed boost is hard to ignore. The video dives into his 9-step workflow using Claude Code, explaining why he switched from Cursor, and highlighting instances where Claude Code outshone Cursor agents. We are talking real-world comparisons between different AI tools in a coder’s real workflow.

    The real value lies in Chris’s practical approach. He doesn’t just hype up AI; he breaks down his exact workflow. The examples provided and the time-stamps make it easy to drill down into the most important sections. For someone like me, who’s actively looking for ways to integrate LLMs into Laravel and PHP projects, this is gold. Imagine automating the generation of complex Eloquent queries or scaffolding entire API endpoints with a few well-crafted prompts. I’m really interested in testing some of Chris’s examples in my day to day.

    Ultimately, what makes this worth experimenting with is the promise of tangible productivity gains. Chris is upfront about the downsides, which keeps it real. It’s not about replacing developers, but about augmenting our abilities. The video is not just about coding, but about building apps and increasing productivity. Now, if I can carve out a couple of hours this week, I will definitely dive into the same approach.

  • New AI video editor, Bytedance’s VEO, new top 3D generator, new open-source AI beats DeepSeek



    Date: 06/22/2025

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    Okay, so this video is a rapid-fire roundup of some seriously cool AI advancements. We’re talking about everything from 3D model generation (Hunyuan 3D 2.1, PartTracker) to video creation (Midjourney V1) and even AI that can understand and interact with humans in a more nuanced way (InterActHuman, POLARIS). There’s also some interesting stuff on prompt engineering and model editing (LoraEdit). It’s a lot to take in, but that’s what makes it so inspiring.

    For a developer like me, who’s been diving headfirst into AI-assisted workflows, this video is gold. It’s not just about flashy demos; it’s about seeing practical applications of these tools that could revolutionize how we build software. Imagine using Hunyuan 3D 2.1 to rapidly prototype 3D assets for a game, or leveraging LoraEdit to fine-tune a model for a specific client’s needs without retraining from scratch. And Midjourney V1 video? Think about creating engaging marketing materials or explainer videos in a fraction of the time. The possibilities for automation and faster development cycles are huge.

    Honestly, what makes this video worth experimenting with is the sheer breadth of tools presented. It’s a reminder that the AI landscape is evolving at warp speed. While I might not use every single tool showcased, it’s crucial to stay informed and explore how these advancements can be integrated into my existing Laravel and PHP projects. Plus, the resources and links provided offer a solid starting point for hands-on experimentation. Definitely adding a few of these to my “try this next” list.

  • Cursor VS Claude Code: The Winner



    Date: 06/21/2025

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    Okay, so this video is a head-to-head comparison of Claude Code and Cursor AI, two AI-powered tools that aim to drastically reduce the amount of traditional coding you need to do. The creator walks you through building a full-stack micro SaaS app using Claude Code and constantly compares the experience to using Cursor AI, which they use more often. It’s a practical look at how these tools can help you ship ideas faster.

    As someone diving deeper into AI coding and no-code, this video is gold. It’s not just theoretical; it shows you a real build process. We get to see the strengths and weaknesses of each platform regarding things like setup, command structures, troubleshooting, and even agentic workflows. I found the comparison especially useful because I’ve been juggling similar choices – should I stick with what I know (similar to Cursor) or invest time in learning something like Claude Code? The video also touches on the practical stuff, like costs and how to integrate these tools into your existing workflow, like setting up a Product Requirements Document (PRD) for better AI guidance.

    What makes this worth experimenting with is that it directly addresses the question, “Which of these tools will actually help me build something?” It goes beyond just demos and into real-world application. Seeing someone build a micro SaaS, showcasing how to use seed prompts, plan mode, and even leverage web searches within the workflow, gives you a concrete idea of what’s possible. Plus, the discussion around the tool’s memory and using Minimum Viable Components (MCPs) is super insightful for structuring complex projects. Honestly, it’s inspiring to see how much of the development process can be augmented, and sometimes even replaced, with these AI tools, pushing us towards faster iterations and reduced development time.

  • n8n Can Now Browse the Web Like a Human with Airtop



    Date: 06/21/2025

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    Okay, this Airtop + n8n integration video is seriously inspiring! It’s all about using Airtop’s no-code web scraping, driven by plain English commands, directly within n8n workflows. Forget wrestling with complex selectors and brittle DOM structures – Airtop lets you define what you want to scrape in natural language, and then you bring that action into n8n for automation. They even have AI Agent versions of these nodes, so you could give your AI agent the power to scrape dynamic web pages. It’s a game changer for data extraction and workflow automation.

    For me, this hits the sweet spot of blending no-code ease with the power of a workflow engine. We’re talking about rapidly building integrations that used to take hours, if not days, to code manually. Think about automating lead generation by scraping social media profiles or gathering product information from e-commerce sites. Plus, the move to AI Agent tool versions means these workflows are even more adaptable and intelligent. It’s like giving my LLM projects eyes and hands to interact with the web.

    What really sells it is the idea of defining scraping actions in plain English. That’s a huge leap towards accessibility and maintainability. I’m already picturing how this could streamline some of our current data pipeline projects and potentially open up completely new automation possibilities. I’m definitely going to be experimenting with this to see how it stacks up against our current scraping solutions. The potential time savings and reduced maintenance alone make it worth the effort!

  • How to Build AI Agent Teams in Flowise (Step-by-Step)



    Date: 06/21/2025

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    Okay, so this video is all about leveling up your Flowise game by building AI “teams” to tackle complex tasks. It walks you through setting up a supervisor system – think of it as a project manager AI – that coordinates specialized AI “workers,” like software engineers and code reviewers, all within Flowise. It dives deep into conditional routing, managing the flow’s state, and structuring outputs, using JSON and enums for validation. This enables your team of agents to hand off tasks and collaborate to solve bigger problems.

    Why is this inspiring? Because it’s the next step in moving beyond simple chatbot demos. For me, it’s about orchestrating multiple LLMs to handle entire development workflows. Imagine automating code generation, testing, and even deployment, all orchestrated by a Flowise supervisor. The video’s focus on structured output, conditional routing, and state management are key to building systems that are not just cool demos but are reliable and predictable, a challenge in the world of LLMs. You can take one task and break it down into a series of smaller more manageable tasks for each agent.

    Practically speaking, I can see this being used to automate a lot of tedious dev tasks. Think automated API creation, bug fixing based on error logs, or even generating documentation. The possibilities are huge, and the video gives you the tools to experiment and build something truly useful. I think it’s worth experimenting with because it showcases how to move from isolated LLM applications to orchestrated, collaborative systems. It really feels like the future of AI-assisted development.

  • How to Make Consistent Characters in Veo 3 (AI Video Tutorial)



    Date: 06/20/2025

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    Okay, this video looks incredibly useful for any developer like me diving headfirst into AI-assisted video creation! It’s all about achieving consistent characters in Google’s Veo 3, which, let’s be honest, is a huge pain point with most AI video generators. The presenter breaks down a workflow using Whisk (for prompt engineering) and Gemini (for prompt optimization) to get more predictable results. Plus, they cover practical post-processing tips like removing those pesky Veo 3 subtitles using Runway or CapCut and even using ElevenLabs for voice cloning.

    What makes this valuable is that it tackles a real-world problem: inconsistent characters ruining the flow of a narrative. We’ve all been there, right? Spending hours generating videos, only to have the main character morph into someone completely different in the next scene. The techniques shown—prompt refinement with Whisk and Gemini—are directly applicable to my work in automating content creation for clients. Imagine being able to generate marketing videos with a consistent spokesperson, all driven by AI.

    For me, the most inspiring part is the combination of different AI tools to achieve a cohesive final product. It’s not just about generating the video; it’s about refining it, adding voiceovers, and removing unwanted elements. The presenter even shares their full prompt and music sources! I am excited to try these tools with a recent project to create training videos for a client onboarding process. I think this approach could save us a significant amount of time.

  • Create Seamless AI Films from One Image (Consistent Characters & Backgrounds)



    Date: 06/19/2025

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    Okay, so this video by Sirio Oberati is gold for anyone like us who’s diving headfirst into AI-assisted development. It’s all about creating consistent AI-generated story scenes from a single image, and, more importantly, how to make them good enough that clients will actually pay for them. Think of it as taking AI image generation beyond just cool pictures and turning it into a scalable, commercially viable content creation pipeline. He walks through tools like Enhancor.ai for consistency and realism, Google Imagen4, and even touches on adding sound using AudioX. He even shares a ComfyUI workflow – which is awesome because it gets you started quicker!

    What makes this so valuable is the focus on consistency. As developers, we know how crucial consistent APIs, data structures, and workflows are to scaling anything. This video applies that same principle to AI-generated visuals. Imagine using these techniques to create consistent UI elements for a no-code platform, or generating training datasets with controlled variations for a machine learning model. He’s literally showing how to use these AI tools to build repeatable visual content that maintains a coherent “brand look and feel.” That’s huge for automation.

    Frankly, seeing someone bridge the gap between cool AI demos and practical, revenue-generating workflows is exactly what I’m looking for right now. He’s sharing the process, not just the output. And let’s be real, who wouldn’t want to experiment with tools that can create visually compelling content with a level of consistency that was previously out of reach? This is the type of stuff that makes me want to carve out some time this week and try building my own LLM-powered content creation service, even if it’s just a proof of concept.

  • VEO 3 KILLER!! This Is the Future of AI Filmmaking (Consistent Multi-Shot Videos)



    Date: 06/19/2025

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    Okay, this video from Sirio is definitely something I’m adding to my weekend experiment list. It’s all about generating cinematic, multi-shot videos using AI from just a single image or prompt. He’s using Enhancor.ai with their new Seedance 1.0 model and claims it’s blowing Google Veo out of the water. As someone knee-deep in trying to automate content creation for marketing campaigns (and maybe even some explainer videos for client projects), this is huge.

    Why is this valuable? Well, the idea of creating consistent characters and scenes with fluid camera movements with minimal input is like a holy grail. Forget about spending hours on storyboarding and shooting separate clips – imagine just feeding in a character design and getting a professional-looking video sequence. Sirio even breaks down how to structure cinematic prompts, which is crucial. We’ve all been there, right? Throwing random keywords at an LLM and hoping for the best? This seems way more strategic.

    For me, the most inspiring part is the potential for real-world application. Think automated ad creation, personalized video content, even generating cutscenes for games. The comparison with Google Veo and Kling is super interesting because it provides a benchmark. If Enhancor.ai can genuinely deliver better results with less effort, it’s a game-changer. I’m eager to see if it lives up to the hype. The free prompting guide he mentions is a great starting point, and diving into Seedance 1.0 could unlock a whole new level of creative automation.