Date: 12/05/2025
Dive into Softr’s Vibe Coding Block! JJ walks you through building interactive components with AI, creating dynamic forms, and customizing your Softr apps like never before. Unleash the power of no-code with conditional filters, user permissions, and version control! Perfect for anyone looking to level up their Softr skills.
Date: 12/04/2025
Okay, here’s a script based on that content for the Alfred Nutile podcast, keeping in mind the preferred style and focus:
(Intro – Upbeat music fades)
Hey everyone, welcome back to the show! Alfred Nutile here, and this week we’re diving deep into a challenge that every builder faces when connecting AI to real-world data: getting LLMs to work with structured data, like databases, reliably.
(Transition – Sound effect or short music sting)
We’ve all heard the promises of AI agents answering questions from your databases. But let’s be honest, vector stores alone often fall flat, especially when you need accurate answers based on relationships within your data. That’s where Natural Language Query (NLQ) comes in, letting you ask questions of a database in plain English.
Now I came across a great video from The AI Automators Community. That show you five practical ways to connect AI agents to your databases using NLQ instead of relying solely on vector stores.
(Link to the video is in the description below)
(Main Content – Talking points based on the YouTube video outline)
The video covers a lot, but here are some key takeaways:
The Problem with Vector Stores: They’re great for semantic search, but struggle with precise relationships in structured data. You get hallucinations, wrong answers, and frustrated users.
Building a Self-Improving SQL Agent: The video explains how to create an agent that learns from past successful queries. It’s brilliant! The agent gets smarter over time, improving accuracy and efficiency.
Five Database Connection Patterns:
Security is Paramount: The video stresses essential security practices: Row-Level Security (RLS), least privilege, and safe CRUD access. If you’re building anything that touches sensitive data, don’t skip this.
(Transition – Quick sound effect)
Here’s what I like about this video:
(Why It Matters – Connect to broader trends)
This matters because, finally, we’re seeing concrete strategies for building AI-powered applications that can reliably interact with structured data. I’ve said for a while now this is the key to the future. This unlocks so much enterprise workflow automation. Imagine giving your users secure, natural language access to the data they need!
(Call to Action)
So, check out the video from The AI Automators Community. (link in the description!)
Are you building database-driven apps? What challenges are you facing? Let me know in the comments!
(Outro – Music fades in)
That’s all for this week! Don’t forget to subscribe, hit that notification bell, and share this episode with your fellow builders. I’ll see you next time with more no-code, low-code, and AI news!
Date: 12/03/2025
Alright, let’s dive into some game-changing AI coding news!
First off, I have to give a shout-out to Docker for their innovative approach to the Model Context Protocol, or MCP. They have a free catalog to check out here. Now, for those who aren’t familiar, MCP is how AI agents can access and use tools. But the problem has been that loading up every possible tool into the agent’s context window eats up resources and makes things slow.
Docker’s dynamic MCP is a total paradigm shift. Instead of giving your AI agent a massive toolbox filled with stuff it might never use, it only loads the tools it needs, when it needs them. This means:
But it doesn’t stop there. This dynamic MCP approach is unlocking a whole new wave of AI coding capabilities.
We’re talking agents that can write clean code, execute it securely in sandboxes, persist state, and even chain MCP servers together to create powerful workflows.
Think about it: your AI agent could build its own custom tools on the fly, without ever touching your core system. Imagine a GitHub search pipeline or a Notion database writer, all powered by AI that can dynamically adapt to the task at hand.
We’re seeing demos of GitHub MCP, dynamic tool selection, and even code-mode tool creation, where AI calls tools inside of tools while preserving context for reasoning. It’s mind-blowing stuff!
Whether you’re a webdev enthusiast experimenting with your first AI script or a power user connecting multiple MCP servers, dynamic MCP is a game-changer. It’s the blueprint for the future of coding with AI.
So, what do you think? Are you excited about dynamic MCP? Let me know in the comments below! And don’t forget to check out the Docker catalog (here) to start experimenting with these technologies yourself. The future of AI coding is here, and it’s dynamic!
Date: 11/30/2025
(Upbeat intro music fades slightly)
Hey everyone, Alfred Nutile here, and welcome back to the channel! Today we’re diving into GitHub Trending – it’s episode #11, and we’re sifting through the hottest 25 projects that developers are starring and forking right now. Think of this as your curated cheat sheet to what’s bubbling in the open-source world. We’ll be looking at what’s useful for our community, folks building no-code/low-code solutions and experimenting with local LLMs. Let’s jump in!
(Transition music, short)
First up, we have SyncKit. This project looks like it’s aiming to simplify background task management for iOS and macOS. It makes synchronizing data easier. Not exactly no-code. But if you’re using something like SwiftUI to build a front end and need to handle complex background tasks, tools like this can be a lifesaver.
Next, RepoMind. This is more interesting. It appears to be focused on analyzing GitHub repositories using AI. This is how you can find the projects that are built using AI. They use embeddings, a great technology to look at.
Vex is a cross-platform terminal file explorer. This isn’t a no-code solution per se, but it’s relevant. Imagine wrapping a powerful command-line tool like this into a no-code workflow.
Now, this is interesting! runprompt is a tool that helps you test and refine your LLM prompts. You can experiment with different models and see how your prompt performs. If you’re building agents or applications using local LLMs, a tool like this is absolutely essential.
Markdown viewers are crucial. You have to remember that if you are building documentation or just working in general.
Beads Viewer. Not sure what this does.
Doraemon Paper Comicizer. This one is fun. Transforms pictures into comic book pages.
Pulse is an animation app for mobile. Another way to make it a little easier on yourself if you use animation in your low code projects.
Claude Usage Tracker – Perfect for those of you who are working a lot with Claude for LLMs.
This is for the mac but lets you create montages easily. It’s good for social media and marketing.
MinerU-HTML lets you extract structured data out of websites.
This decodes your web3 transactions
podcast-server lets you create your own podcast server. Nice!
Voxel4D is a cool project. We should highlight that one!
LatentMAS is an agent project that is interesting.
DSpico hardware is hardware for audio
FastRL is reinforcement learning code.
SteadyDancer makes videos and is worth taking a look at.
This helps you visualize your go code.
This is another animation project
Urlvy can shorten your urls
Sip can help you with your website.
Agent Commands is worth a look.
If you want to build a honey pot this tool can help!
Makes your graphics look smooth
(Transition music, short)
And that’s a wrap on GitHub Trending #11! Hopefully, you saw a few projects that sparked some ideas. Remember, the goal here is to see what’s possible and how these tools can fuel your own no-code/low-code builds, and your local LLM experiments.
(Call to Action)
Don’t forget to like this video if you found it helpful, and subscribe to the channel for more news, reviews, and tutorials on the world of no-code, AI, and building for the future. And if you really want to support the channel, consider joining as a paid subscriber! You can find the link down below: https://www.youtube.com/channel/UC9Rrud-8CaHokDtK9FszvRg/join Your support helps me bring you this content every week.
Thanks for watching, and I’ll see you in the next one!
(Outro music fades in and plays)
Date: 11/30/2025
Okay, here are some potential news segments based on the provided AI news video, tailored for the Alfred Nutile channel, focusing on low-code/no-code applications and local LLM implications. I’ll keep it concise and Alfred-esque!
Start with Ad Read
HubSpot’s Free Guide: Before we dive in, quick shoutout to HubSpot! Grab their free guide, “5 AI Tools to Make Your First Million.” Link in the description. Lots of opportunity out there for folks looking to build.
(Transition Music sting)
Local LLM NEWS
1. Hunyuan OCR – Smarter Image Scanners:
2. Fara-7B – Agentic Computer Model
3. DeepSeek Math V2 – Local Math Whiz:
General AI News to Note:
4. Flux2 – UI
5. Claude Opus 4.5 – Faster, Smarter Claude:
(Outro Music Sting)
Date: 11/28/2025
Alright, let’s dive into some news from the backend world, specifically for those of us building with no-code or low-code. Xano, a name you’ve likely heard if you’re in this space, just launched Xano 2.0.
Date: 11/28/2025
Alright, let’s dive into this week’s GitHub Trending, where we’re spotlighting 23 repos you should absolutely bookmark. I’m seeing a lot of interesting stuff here that could be real time savers or game changers for builders.
[Read through each repo]
Okay, some quick thoughts on a few of these that stood out to me:
Don’t forget to like the video and subscribe to the channel.
Date: 11/27/2025
Okay, team, let’s dive into some trending GitHub projects this week! I’m your host, Alfred Nutile, and this week, we’re tackling 24 of the hottest open-source projects that are making waves in the GitHub community. Remember, understanding these tools gives you the edge in building smarter and better for your customers.
Date: 11/26/2025
Alright, let’s dive into some local LLM news, and this one is a big one: Liquid AI just dropped LFM2-VL! This feels like a real turning point for local AI.
Summary: Liquid AI has released LFM2-VL, touted as the world’s fastest and best-performing open-source small foundation model. The key point here? It’s designed to run directly on your phones, laptops, even wearables.
Key Points:
Why It Matters:
LFM2-VL isn’t just another model; it’s proof that advanced multimodal AI (we’re talking vision and language) can now run offline, privately, and efficiently on the devices people already own. This is what we’ve been waiting for! The potential applications are enormous: smart cameras, offline assistants, and so much more, all without relying on the cloud. This release from Liquid AI could really shift the AI industry off the cloud and into our pockets. This is amazing news for no-code builders looking to embed AI directly into user experiences.
