Category: Try

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.

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.

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.

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.

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.

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.

Date: 06/19/2025

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Okay, so this video is all about Hailuo 02, an AI video generator that’s apparently making waves. It walks you through how to use it, compares it to other tools like Veo3 and Kling, and puts it through its paces with various prompts – from physics simulations to 3D Pixar styles. In essence, it’s a deep dive into the capabilities of this AI for creating video content.

Why is this valuable for us as developers transitioning into the AI space? Well, think about it. We’re always looking for ways to automate content creation, whether it’s for marketing materials, explainer videos, or even just prototyping UI animations. This tool could potentially replace hours of manual video editing and animation work. Imagine using it to quickly generate video mockups for client presentations or even creating training content for new team members. Plus, the video covers prompt engineering, which is becoming a core skill in our new LLM-driven world. Understanding how to get the AI to do what you want is half the battle!

Honestly, the part that has me most excited is the potential for rapid prototyping and experimentation. How cool would it be to quickly visualize a complex system or process using AI-generated video? I’m definitely going to give Hailuo 02 a spin, especially since it offers a free trial. Seeing how it handles different prompts and complexities will be key to figuring out how it fits into our development workflow. Maybe we can even integrate its API into our existing Laravel applications for dynamic content generation. The possibilities are pretty inspiring.