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YouTube Videos I want to try to implement!

  • I Tried Google Antigravity (Cursor Killer?)



    Date: 11/24/2025

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    Okay, let’s talk AntiGravity, Google’s new AI IDE. I saw BetterStackHQ, specifically on YouTube (channel: BetterStack), did a video on it, and, yeah, “interesting” sums it up. They highlighted some cool ideas, some rough edges, and what they called “questionable choices,” and I think that’s a fair assessment.

    Let’s break down what makes AntiGravity newsworthy.

    What AntiGravity Is:

    It’s a cloud-based IDE pushing the boundaries of AI integration. It promises to help you build, test, and deploy apps faster with the help of AI agents.

    BetterStackHQ Breakdown:

    • Agent Manager: BetterStackHQ shows the power of this. Allowing for agents to be created, and deployed in your IDE.
    • Browser Agent: A cool feature they demo is the Browser agent which can do Browser tasks and work inside of your IDE
    • The Bad: This is where BetterStackHQ, started seeing some issues with the IDE.
    • Security Issues: The video highlights pretty big security concerns around the data it holds in your ide
    • Performance: Then they talk about the performance of the IDE.
    • Final thoughts: Giving their honest opinion on the IDE as a whole

    Why This Matters for No-Code/Low-Code Builders:

    AntiGravity is attempting to redefine how we build software, and even though it has some rough edges, it’s a glimpse into the future. Features like Agent Manager and Browser Agent, if refined and secured, could significantly reduce the time and effort required to build complex applications. The generative UI api with Thesys is also a game changer. Also I think it is important to note that the Thesys generative UI api is what is powering anti-gravity. I think these integrations with companies, might be an advantage that anti-gravity and bubble or zapier have that lovable doesn’t.

    The Takeaway:

    Keep an eye on AntiGravity’s evolution. Even with its current drawbacks, it represents a significant step towards AI-assisted development and is worth watching for its potential impact on the no-code/low-code landscape.

    Link: https://antigravity.google/

  • 15 Docker Containers That Will Instantly Improve Your Home Lab (2025 Guide)



    Date: 11/24/2025

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    Alright, welcome back to the channel! Today, we’re diving into how to supercharge your home lab. I’m talking about 15 Docker containers that will instantly make your life easier and your lab more powerful, even in late 2025.

    We’re covering everything from monitoring and automation to networking, security, backups, dashboards, and even DevOps. We’ll be looking at awesome tools like Dozzle, Watchtower, Pulse, Komodo, Netdata, Uptime Kuma, Bitwarden, Homer, Mailrise, NetBox, and a whole lot more. I’m going to show you how they all work together to build a killer home lab stack, whether you’re running Proxmox or any other Docker host.

    Before we jump in, I want to remind you about the big home lab share and giveaway! Head over to the VHT forum (link below) and share your 2025 home lab build for a chance to win a surprise giveaway before the end of the year. I want to see what you guys are working on! The forum post with the details is at virtualizationhowto.com/community/home-lab-pics/best-home-lab-server-pics-and-gear-in-2025/.

    Okay, let’s get to those containers! Here’s a quick rundown of what we’ll cover (with timestamps so you can jump around):

    • 0:00 Intro and what this video covers
    • 0:56 2025 home lab share and giveaway details
    • 1:24 Dozzle real time Docker log viewer
    • 2:09 Watchtower automatic Docker container updates
    • 3:14 Pulse monitoring for Proxmox and Docker in one place
    • 4:03 Komodo all in one Docker management and observability
    • 4:48 Netdata zero touch monitoring and cloud console
    • 5:54 Uptime Kuma simple up or down checks and status pages
    • 6:38 Bitwarden self hosted password and secrets manager
    • 7:12 Homer home lab start page and launcher dashboard
    • 7:51 Mailrise SMTP to modern notification bridge with Apprise
    • 8:35 NetBox source of truth for racks, IPs, VLANs, and devices
    • 9:13 Nginx Proxy Manager easy reverse proxy and HTTPS for containers
    • 9:41 phpIPAM IP address management for home lab networks and VLANs
    • 10:14 Duplicati backups for Docker volumes and lab data
    • 10:41 Pi-hole DNS level ad blocking, telemetry filtering, and malware protection
    • 11:17 Gitea self hosted Git, DevOps workflows, and future native CI
    • 11:59 Building a complete home lab stack with these containers
    • 12:52 Final thoughts and what to try next in your lab

    (Then go into detail about each container)

    So, as you can see, these containers cover a wide range of home lab needs. By combining them strategically, you can build a robust, automated, and well-managed home lab environment. Don’t forget to check out the blog post linked below for more details and configuration tips. And most importantly, share your 2025 home lab builds in the forum for a chance to win that giveaway! Thanks for watching, and I’ll see you in the next video. Don’t forget to subscribe and hit that notification bell!

  • New Gemini 3 Antigravity – My New IDE



    Date: 11/23/2025

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    Okay, buckle up, no-code pioneers, because this week we’re diving headfirst into the deep end of AI-powered development with Google’s Gemini 3.0! I know, I know, Google drops another AI, but trust me, this one’s a game-changer.

  • Rize 2.3.4 Release Video



    Date: 11/21/2025

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    Okay, this Rize 2.3.4 update is exactly the kind of thing I’ve been diving into lately! Essentially, it’s a time-tracking tool leveraging AI, and this update is all about making that AI smarter and more customizable. They’ve upgraded to GPT-5, squashed some annoying bugs, and, crucially, given you a ton of control over how the AI generates time entry suggestions. We’re talking custom instructions, language tweaks, and the ability to prioritize certain projects.

    Why is this cool for us developers exploring AI workflows? Well, think about it: automating time tracking is a HUGE pain point. I mean, who actually enjoys meticulously logging every minute? By giving us control over the AI that’s doing this, Rize lets us tailor it to our specific coding habits, project structures, and even the way we phrase our tasks. The “Custom AI Instructions” feature is particularly exciting – imagine teaching the AI to recognize specific code patterns or naming conventions and automatically tag time entries accordingly! This moves beyond generic AI and into something truly personalized and efficient.

    I see huge potential in combining Rize with other AI-powered tools I use. For example, I could feed Rize data generated by my code analysis tools to get even more granular time tracking. The ability to adjust time entry durations and disable unwanted suggestions is a game-changer. It’s not about blindly trusting the AI; it’s about collaborating with it to create a workflow that actually works for me. I am definitely going to experiment with integrating this into my workflow, especially with LLM’s getting better all the time. It could free up a lot of mental space for the real problem solving!

  • Introducing Manus Browser Operator : An AI Agent that Browses For You?



    Date: 11/21/2025

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    Okay, this Manus video is seriously interesting, and it’s right up my alley as I’m diving deeper into AI-assisted development. It shows how you can automate web-based tasks by leveraging your existing logged-in sessions. Think auto-filling forms, scraping data from multiple sites, and chaining together complex workflows, all running in your browser. It’s like giving your browser an AI co-pilot to handle the boring, repetitive stuff.

    What makes this valuable for us developers is the potential to automate so many tedious tasks. Imagine automatically pulling data from APIs, transforming it, and then using it to update your application—all orchestrated through the browser. We’re talking about automating testing workflows, data entry, and even generating content for CMS systems. Instead of writing custom scripts and APIs, Manus seems to let you define these workflows visually and then let AI handle the execution.

    It’s definitely worth experimenting with because it’s a potential game-changer for productivity. Instead of spending hours on manual tasks, you could be focusing on higher-level design and problem-solving. The key is figuring out how to integrate it seamlessly with existing Laravel projects and workflows. But if it works as advertised, it could free up a significant amount of time, making it a tool I’d gladly add to my arsenal.

  • Google’s Cursor Killer – Anti Gravity IDE First Look (It’s Good)



    Date: 11/19/2025

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    Okay, this video showcasing Google’s AntiGravity IDE and Thesys for Generative UI is right up my alley! It’s basically about building AI agents with visual interfaces, and the focus on using AI to create UIs for those agents. That’s a game-changer for me, especially as I’m trying to streamline the whole process of building LLM-powered applications.

    The value for us, as developers moving toward AI-enhanced workflows, is clear: It shows how to quickly prototype and build interactive AI tools. AntiGravity seems to offer a solid environment for managing agents and workflows, and Thesys looks like it could seriously cut down on the time spent wrestling with UI code. Imagine being able to build a functional UI by simply describing what you want – that’s the promise here. Think about automating internal tools, client dashboards, or even complex data analysis interfaces. Instead of days or weeks of development, we could potentially have something usable in hours.

    Honestly, what makes this inspiring is the potential for rapid iteration. The ability to quickly test and refine agent behavior with a live UI means faster feedback loops and a more intuitive development process. I’m already picturing using Thesys to quickly build frontends for my existing Laravel applications that leverage LLMs for enhanced features. Worth experimenting with? Absolutely! Anything that speeds up the UI development side of AI-driven projects is gold in my book.

  • Welcome to Google Antigravity 🚀



    Date: 11/18/2025

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    Okay, so this Google Antigravity thing looks seriously interesting. From what I gather, it’s essentially trying to level up the IDE into an agent-driven environment. Instead of just writing code line by line, you’re setting agents loose to tackle higher-level tasks. Imagine an agent handling everything from writing tests to deploying a feature, while you oversee and guide the process from a familiar IDE. That’s the promise, anyway.

    Why is this relevant to my (and hopefully your) AI-enhanced workflow journey? Because it addresses a huge pain point: orchestrating all these amazing AI tools. We’ve got LLMs for code generation, no-code platforms for rapid prototyping, but getting them all to work together seamlessly? That’s still a challenge. Antigravity seems to be aiming to provide that orchestration layer, letting agents act across different environments like the editor, terminal, and browser. Think automated refactoring, or even building entire microservices with minimal direct coding.

    This could translate to real-world time savings on complex projects. Instead of spending days manually setting up environments and writing boilerplate code, an agent could handle the grunt work, freeing you up to focus on architecture and solving the trickier problems. Look, I’m not expecting magic, and I know there’s likely a steep learning curve, but the potential here to boost productivity and finally start truly leveraging AI in our daily workflows is really exciting. Definitely worth checking out and seeing if it lives up to the hype.

  • GitHub Trending Today #8: TONL, tiny-diffusion, Trimmy, Chirp, IsoBridge, Sound Monitor, Camp



    Date: 11/18/2025

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    Alright, so this “GitHub Trending Today” video is basically a curated list of 22 open-source projects that are currently blowing up on GitHub. It’s like a shortcut to discover cool new tools and libraries you might otherwise miss. For someone like me (and you, hopefully!), who’s knee-deep in exploring AI coding, no-code, and LLM workflows, it’s a goldmine. Think of it as a discovery engine for tools that could streamline your AI integrations.

    The value here lies in exposure. You might stumble upon a library that perfectly solves a pain point you’ve been wrestling with, or discover a new approach to RAG (Retrieval-Augmented Generation) like rag-chunk that sparks a whole new idea. Maybe tiny-diffusion could be the key to faster prototyping, or IsoBridge will solve some isolation issues for your next project. In the fast-moving world of AI and development, keeping a pulse on trending projects is essential for staying ahead of the curve and finding innovative solutions.

    Honestly, I think it’s worth experimenting with any of these, even if it just means spending a few hours poking around. You might find that “one weird trick” that saves you days of development time. Plus, contributing to open-source is always a good look! It’s how we all level up. So, let’s dive in!

  • I’m leaving the cloud! (…and why you probably should too)



    Date: 11/18/2025

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    Okay, so this video by Simon L is all about moving away from the cloud for SaaS infrastructure and embracing a self-hosted setup. He dives into his reasons, which are primarily cost optimization, control, and avoiding vendor lock-in. He outlines his own self-hosted setup and also clarifies what he still uses AWS for. He’s not advocating a complete cloud abandonment, but rather a strategic shift.

    For someone like me, deep into AI-driven development, this is gold. We’re constantly looking at ways to optimize infrastructure, and the cloud, while powerful, can be a black hole for resources. The insights into cost savings and greater control are particularly relevant. I’m especially interested in the points made regarding data ownership and the ability to fine-tune the environment for specific AI/ML workloads, something that can get expensive and restrictive in a purely cloud-based setting.

    Think about it: with the rise of on-prem LLMs and tools like Ollama, the idea of running some AI components locally is becoming more feasible. We could potentially build a hybrid setup – using the cloud for scalability and globally distributed services, but keeping the AI “brain” closer to home for data privacy and performance. It’s absolutely worth experimenting with because it challenges the default “everything in the cloud” mentality. Plus, the thought of optimizing infrastructure costs while also gaining greater control is something every developer should be exploring. I’m keen to see if moving some workloads in-house gives more granular control over GPU usage and can speed up development cycles.

  • Langflow Crash Course – Build LLM Apps without Coding (Postgres + Langfuse Setup)



    Date: 11/17/2025

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    Okay, this Langflow video is seriously inspiring for anyone, like myself, knee-deep in the shift towards AI-enhanced development. It essentially walks you through using Langflow, a low-code Python-based platform, to visually build LLM applications and AI agents without a ton of frontend coding. It covers everything from installation to creating flows, API exposure with authorization, custom components, Langfuse integration for monitoring, and even how to get it production-ready. That’s a lot!

    What makes this video gold for us is the bridge it builds between traditional coding and the world of LLM-powered apps. We’re talking about visually designing complex workflows, plugging in your own Python code where needed, and monitoring everything with Langfuse. Think about it: you can rapidly prototype an AI-driven chatbot, integrate it with your existing Laravel backend through the API, and then monitor its performance, all without getting bogged down in endless lines of React or Vue.js. Plus, the video shows how to add your own custom components, meaning you can really tailor the platform to your specific needs.

    I’m particularly excited about the production-grade setup section. Too often, these AI tools feel like toys, but this video tackles the practicalities of deploying something real. The promise of being able to “ship to customers” something built primarily visually, but backed by solid Python and API security, is huge. The video makes it worth experimenting with. I’m already thinking about how I can use it to automate some of my client’s customer service workflows!