Category: Try

Date: 02/07/2025

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Okay, so this video’s about setting up an open-source alternative to OpenAI’s “Deep Research” using tools like OpenAI’s Mini3 and Docker. It’s aimed at getting PhD-level research done with AI in minutes, without breaking the bank with OpenAI’s hefty $200/month price tag. It provides a guide to implement deep research yourself, and compares open source AI research tools to OpenAI tools.

As someone knee-deep in transitioning from traditional Laravel development to leveraging AI, no-code, and LLMs, this is *exactly* the kind of thing that gets me excited. We’re talking about democratizing access to powerful AI research capabilities. Instead of being locked into expensive proprietary platforms, this video shows how to build a custom research environment. Using this in the real world, I can see myself using it to automate market research, analyze competitor strategies, or even pre-validate new feature ideas.

What makes this video truly worth experimenting with is the potential for cost savings and increased control. Sure, OpenAI’s Deep Research might be slick, but the video highlights the benefits of slower, more detailed AI research, and gives you more control over the data. Plus, the thought of having an AI research assistant at my beck and call, fueled by open-source tools, is too good to pass up. I’m gonna give this a shot this week, starting with integrating it into our content summarization workflow.

Date: 02/07/2025

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Okay, so this ToolJet 3.0 video is all about leveling up internal tool development, and it’s *definitely* worth a look for those of us diving into the AI-assisted, no-code world. Basically, they’ve revamped their platform to make building internal apps way faster and more intuitive. They’re talking a 10x speed increase in the app builder – that’s huge! Plus, they’ve doubled down on security, expanded their integrations, and baked in AI capabilities through Portkey, OpenAI, and Pinecone. In essence, they are aiming to streamline your development lifecycle.

Why is this exciting for us AI-focused developers? Well, the faster app builder means less time wrestling with UI components and more time experimenting with AI workflows. The AI integrations, in particular, are interesting. Imagine building a custom CRM that uses OpenAI to automatically summarize customer interactions, or an internal dashboard that leverages Pinecone to provide intelligent search across your documentation. I can see this being useful in so many different projects.
These internal tools, if built properly, could also be used as effective ways to test models and automations internally, with a dedicated GUI.

For me, what really grabs my attention is the focus on automation and AI. This isn’t just about slapping an AI chatbot onto an existing platform; it’s about embedding AI throughout the entire development process. It’s worth experimenting with because it could significantly reduce the time and effort required to build and maintain internal tools, freeing us up to focus on more complex, strategic projects. Honestly, who wouldn’t want to explore a platform that promises to make internal tool development faster, smarter, and more secure? It’s about making our lives easier, one internal tool at a time!

Date: 02/05/2025

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Okay, so this video is all about leveraging DeepSeek AI and other AI tools to build a profit-generating website from the ground up, even if you’re starting with just basic hosting. It’s basically a step-by-step guide, and they’re using tools like DeepSeek R1, Notepad, and even ChatGPT for image creation. The goal? To show you how to combine different AI models to create a real, working website that makes money.

Why is this valuable? Because it’s precisely the kind of thing I’m diving into! As a seasoned developer, I’m actively looking for ways to replace tedious tasks with AI-driven solutions. This video offers a practical, real-world application of AI coding, no-code principles, and LLM workflows. Instead of manually coding everything or relying on complex frameworks for basic sites, we can use AI to rapidly prototype and deploy a fully functional website. That’s a game-changer for productivity.

Think about it: we could apply these concepts to quickly build landing pages for marketing campaigns, create niche websites for affiliate marketing, or even automate the creation of internal tools for our teams. The key is to experiment and see how these AI tools can streamline the development process. For me, this is absolutely worth exploring. Combining different AI models to achieve a specific business goal? I’m definitely trying that out!

Date: 02/05/2025

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Okay, this Ultravox video is seriously inspiring for anyone diving into AI-powered automation, and here’s why I think it’s worth your time. The video is essentially a head-to-head comparison between OpenAI’s Realtime API and Ultravox, an open-source speech-to-speech model. Ahmed shows how you can build AI voice agents, specifically for querying SQL databases, and the results are surprisingly similar, but at a fraction of the cost (like 5 cents a minute!). He even dives into cool features like Call Stages, AI voice cloning, function calls and WebRTC integration that can help improve latency.

Why is this crucial for us? Well, as we move from traditional PHP/Laravel development to incorporating LLM-based workflows, the cost and control over our AI tools become paramount. Instead of relying solely on proprietary APIs, Ultravox presents a viable alternative. We can host it ourselves, tweak it to our specific needs, and potentially save a boatload of money in the process. Think about automating customer support, building internal data querying tools, or creating voice-activated interfaces for existing applications – all things we can potentially do without breaking the bank.

From my experience, experimentation is key. I’ve been burned by vendor lock-in and unpredictable API costs before. Ultravox offers a chance to build robust, cost-effective AI voice solutions. The demo in the video, especially the SQL query example, immediately sparked ideas for automating some of the tedious reporting tasks in my current projects. It’s time to roll up our sleeves and explore what we can build by bringing the power of open-source to our toolchain.

Date: 02/05/2025

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Okay, so this video about “ugly websites” making serious money is right up my alley. It’s basically diving into the business models of sites like TractorData.com, DiskPrices.com, DrudgeReport.com, and Craigslist.com to show that you don’t need a fancy design to rake in cash, especially with display ads. For someone like me, who’s been moving towards AI-driven development and no-code solutions, it’s a reminder that functionality and niche focus can be way more important than pixel-perfect aesthetics.

What makes this valuable is the validation it provides for building simple, effective solutions using modern tools. I mean, think about it: we can use AI to generate content, automate link building (like with Link Whisper, which is mentioned), and even create entire workflows without obsessing over every design detail. This video highlights that focusing on delivering value to a specific audience and monetizing effectively is where the real win is. We can use no code tools like Bubble or WeWeb paired with backend functionality from Laravel to get a beautiful mix of scalability and speed!

This concept is super applicable to real-world projects. Imagine using an LLM to generate targeted content for a niche site, then deploying it quickly with a simple no-code front end. You could test and iterate rapidly without getting bogged down in design debates. Personally, the idea of building a profitable side project by prioritizing functionality and leveraging AI tools is incredibly inspiring. It’s a nudge to experiment, to stop chasing perfection, and to start delivering real value quickly, without all the bloat.

Date: 02/04/2025

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Okay, this Matthew Berman video on “Deep Research” with Chatbase is seriously up my alley. Essentially, it’s about leveraging specialized AI agents (o3 Agents) to do deep-dive research for you. Think about it: instead of spending hours sifting through documentation, Stack Overflow, or trying to piece together different API functionalities, you can have an AI agent do it for you, summarizing key points and even providing code examples.

For developers like us who are transitioning into AI-enhanced workflows, this is huge. We’re constantly looking for ways to automate the tedious parts of our jobs. Imagine using this for quickly understanding a new Laravel package, figuring out the optimal way to implement a complex algorithm, or even researching the latest security vulnerabilities. The ability to have an AI agent dedicated to research drastically reduces the learning curve and frees up time for actual coding and problem-solving.

What makes this particularly exciting is the potential for real-world applications. Think about automated report generation, dynamic documentation creation, or even building AI-powered debugging tools. The promise of having these agents working to gather data, analyze it, and present it in a coherent manner is incredibly appealing. I’m especially eager to experiment with integrating this into my Laravel projects to automate tasks like dependency analysis and code optimization recommendations. It’s definitely worth the time to explore; the productivity gains could be massive.