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Tag: ai

  • ChatGPT Agent Just Went Public—Here’s My Honest Reaction

    News: 2025-07-26



    Date: 07/26/2025

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    I spent some time testing the new ChatGPT Agent, which is now available to all Plus subscribers. My goal was to see if it could handle the kind of multi-step, real-world tasks we often build complex automations for. I challenged it with everything from researching products and comparing travel options to compiling content for a newsletter.

    The agent shows a fascinating glimpse into the future of autonomous workflows, successfully navigating multiple browser tabs and synthesizing information from a single prompt. However, it’s still very much a first version, with noticeable quirks and limitations you need to be aware of. For anyone building with no-code tools, this is a must-watch to understand where AI agents are today and where they’re heading.

  • Qwen 3 2507: NEW Opensource LLM KING! NEW CODER! Beats Opus 4, Kimi K2, and GPT-4.1 (Fully Tested)

    News: 2025-07-26



    Date: 07/26/2025

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    Alibaba just dropped a new open-source model, Qwen 3-235B, and it’s a game changer for those of us who need high-performance AI without the closed-source limitations. I’m gonna dive into why this model is a serious contender, comparing it directly to the likes of GPT-4.1 and Claude Opus, which are still behind paywalls.

    If you’re working with no-code or low-code tools, you’ll appreciate the model’s agentic skills. It can reason, plan, and use tools, which means you can build more sophisticated automations. Plus, the massive 256K context window? That’s a whole new level for workflows that need to handle large amounts of information.

    This isn’t just another update; it’s a robust new tool that brings state-of-the-art capabilities within reach of more creators and small teams.

  • ChatGPT Agent Just Went Public—Here’s My Honest Reaction

    News: 2025-07-26



    Date: 07/26/2025

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    OpenAI’s new ChatGPT Agent is finally here, promising to turn a single prompt into a multi-step research and execution plan. This hands-on review tests its capabilities with practical, real-world tasks, from comparing travel options to gathering content for a newsletter. For those of us building structured automations in tools like n8n, this is a fascinating look at a different paradigm: prompt-based automation, where the AI generates the workflow on the fly from a natural language goal. While the results show it’s not without its quirks, the potential for automating complex research is undeniable. It’s an early but exciting glimpse into how we might soon kick off entire projects with just a single sentence.

  • Qwen 3 2507: NEW Opensource LLM KING! NEW CODER! Beats Opus 4, Kimi K2, and GPT-4.1 (Fully Tested)

    News: 2025-07-26



    Date: 07/26/2025

    Watch the Video

    Alibaba just dropped a new open-source model, Qwen 3-235B, and it’s a serious contender for the top spot, even against the closed-source heavyweights. There’s a great video that breaks it all down, comparing it directly to models like GPT-4.1 and Claude Opus. The big takeaway for anyone building with AI is its impressive performance in agentic tasks—think reasoning, planning, and tool use. This is crucial for creating more sophisticated automations.

    The video also dives into its massive 256K context window, which is a game changer for handling complex, multi-step workflows. What I really appreciate is the emphasis on running this model locally or accessing it through free APIs. This opens up the possibility of building powerful custom solutions without being tied to those expensive, proprietary systems.

  • Claude Code Agents: The Feature That Changes Everything



    Date: 07/26/2025

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    Okay, so this video about Claude Code’s new agents feature is seriously exciting for anyone diving into AI-enhanced workflows. Basically, it’s a deep dive into how you can build custom AI agents (think souped-up GPTs) within Claude Code and chain them together to automate complex tasks. The video shows you how to build one from scratch with the dice roller and then it ramps up. I am now using that YouTube outline workflow myself!

    Why is this valuable? Well, for me, the biggest draw is the ability to automate multi-step processes. Instead of just using an LLM for a single task, you’re creating mini-AI workflows that pass information between each other. The video nails the importance of clear descriptions for agents. It’s so true–the more precise you are, the better the agent will perform. This directly translates into real-world scenarios like automating code reviews, generating documentation, or even building CI/CD pipelines where each agent handles a specific stage.

    Honestly, what makes this video worth checking out is the practical, hands-on approach. Seeing the presenter build an agent from scratch and then apply it to something completely outside of coding (like video outlining) is inspiring. It highlights the versatility of these AI tools and hints at the potential for truly transforming how we work. I’m going to explore how I can use these agents to help automate new feature implementations and it will be a game changer.

  • Google Just Released an AI App Builder (No Code)



    Date: 07/25/2025

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    Okay, so this video is packed with exactly the kind of stuff I’ve been geeking out over: rapid AI app development, smarter AI agents, and AI integration within creative workflows. Basically, it’s a rundown of how Google’s Opal lets you whip up mini AI apps using natural language – like, describing an AI thumbnail maker and bam, it exists! Plus, the video dives into how ChatGPT Agents can actually find practical solutions, like scoring cheaper flights (seriously, $1100 savings!). And Adobe Firefly becoming this AI-powered creative hub? Yes, please!

    Why is this gold for a developer transitioning to AI? Because it showcases tangible examples of how we can drastically cut down development time and leverage AI for problem-solving. Imagine automating routine tasks or creating internal tools without writing mountains of code. The idea of building a YouTube-to-blog post converter with Opal in minutes? That’s the kind of automation that could free up serious time for more complex challenges. It’s not about replacing code, it’s about augmenting it.

    What really makes this worth a shot is the sheer speed and accessibility demonstrated. The old way of doing things involved weeks of coding, testing, and debugging. Now, we’re talking about creating functional apps in the time it takes to grab a coffee. This is about rapid prototyping, fast iteration, and empowering anyone to build AI-driven solutions. It’s inspiring and something I will be exploring myself.

  • ChatGPT Agent Just Went Public—Here’s My Honest Reaction



    Date: 07/25/2025

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    Okay, this ChatGPT Agent video is a must-watch if you’re trying to figure out how to integrate AI into your development workflow. The presenter puts the new Agent through a real-world gauntlet of tasks—from researching projectors to planning trips and even curating a movie newsletter. It’s a fantastic overview of what’s possible (and what isn’t) with this new tool.

    What makes this so valuable is seeing the ChatGPT Agent tackle problems that many of us face daily. Think about automating research for project requirements, generating initial drafts of documentation, or even scripting out basic user flows. Watching the Agent struggle with some tasks while excelling at others gives you a realistic expectation of what it can do. We could potentially use this for automating API research or generating boilerplate code based on specific requirements.

    What really excites me is the potential for no-code/low-code integrations using the Agent. Imagine feeding it user stories and having it generate a basic prototype in a tool like Bubble or Webflow. The possibilities are endless, but it’s crucial to understand its limitations, which this video clearly highlights. I’m definitely going to experiment with this—if nothing else, to save myself a few hours of tedious research each week!

  • Qwen 3 2507: NEW Opensource LLM KING! NEW CODER! Beats Opus 4, Kimi K2, and GPT-4.1 (Fully Tested)



    Date: 07/22/2025

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    Alright, so this video is all about Alibaba’s new open-source LLM, Qwen 3-235B-A22B-2507. It’s a massive model with 235 billion parameters, and the video pits it against some heavy hitters like GPT-4.1, Claude Opus, and Kimi K2, focusing on its agentic capabilities and long-context handling. Think of it as a deep dive into the current state of the art in open-source LLMs.

    For someone like me, who’s knee-deep in exploring AI-powered workflows, this video is gold. It’s not just about the hype; it’s about seeing how these models perform in practical scenarios like tool use, reasoning, and planning—all crucial for building truly automated systems. Plus, the video touches on the removal of “hybrid thinking mode,” which is fascinating because it highlights the trade-offs and challenges in designing these complex AI systems. Knowing Qwen handles a 256K token context is a game changer when thinking about the possibilities around document processing and advanced AI workflows.

    What makes it worth experimenting with? Well, the fact that you can try it out on Hugging Face or even run it locally is huge. This isn’t just theoretical; we can get our hands dirty and see how it performs in our own projects, maybe integrate it into a Laravel application or use it to automate some of those tedious tasks we’ve been putting off. For example, could it write better tests that I keep putting off or, even better, is it capable of self-debugging and auto-fixing things? I’m definitely going to be diving into this one.

  • Google Veo 3 For AI Filmmaking – Consistent Characters, Environments And Dialogue



    Date: 07/21/2025

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    Okay, this VEO 3 video looks incredibly inspiring for anyone diving into AI-powered development, especially if you’re like me and exploring the convergence of AI coding, no-code tools, and LLM-based workflows. It basically unlocks the ability to create short films with custom characters that speaks custom dialogue, leveraging Google’s new image-to-video tech to bring still images to life with lip-synced audio and sound effects. Talk about a game changer!

    The video is valuable because it’s not just a dry tutorial; it demonstrates a whole AI filmmaking process. It goes deep on how to use VEO 3’s new features, but also showcases how to pair it with other AI tools like Runway References for visual consistency, Elevenlabs for voice control (I have been struggling to find a good tool), Heygen for translation, Suno for soundtracks, and even Kling for VFX. The presenter also gives great prompting tips and also some cost savings ideas (a big deal!). This multi-tool approach is exactly where I see the future of development and automation going. It is about combining the best of breed tools to create new workflows and save time and money.

    For example, imagine using VEO 3 and Elevenlabs to quickly prototype interactive training modules with personalized character dialogues. Or, think about automating marketing video creation by generating visuals with VEO 3, sound effects with Elevenlabs and translating them into multiple languages. What I found to be very interesting is how it can be used to create story boarding content quickly. The possibilities are endless! I’m genuinely excited to experiment with this workflow because it bridges the gap between traditional filmmaking and AI-driven content creation. I am especially interested to see how the presenter created the short film, Hotrod. I want to see if I can create something similar.

  • Uncensored Open Source AI Video & Images with NO GPU!



    Date: 07/18/2025

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    Okay, this video on using Runpod to access powerful GPUs for AI image and video generation with tools like Flux and Wan is seriously inspiring! It tackles a huge barrier for many developers like myself who are diving into the world of AI-enhanced workflows: the prohibitive cost of high-end GPUs. The presenter walks through setting up accounts on Runpod, Hugging Face, and Civitai, renting a GPU, and then deploying pre-made ComfyUI templates for image and video creation. Think of it as a “GPU-as-a-service” model, where you only pay for the compute you use.

    This is valuable for a few reasons. First, it democratizes access to AI tools, allowing developers to experiment and innovate without a massive upfront investment. Second, it demonstrates how we can leverage open-source tools and pre-built workflows to quickly build amazing AI applications. I can immediately see this applying to content creation for marketing materials, generating assets for game development, or even automating visual aspects of web applications. Imagine feeding your existing product photos into one of these models and generating fresh marketing images tailored for specific demographics.

    What makes this video particularly worth experimenting with is the focus on ease of use. The presenter emphasizes that you don’t need to be an expert in ComfyUI to get started, which removes a huge hurdle. Plus, the promise of sidestepping content restrictions on other platforms is enticing. I’m definitely going to try this out. Renting a GPU for a few hours to prototype an AI-powered feature is far more appealing than purchasing dedicated hardware, especially given how quickly this space is evolving!