Tag: n8n

Date: 09/13/2025

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Okay, so this video is all about bringing human oversight into your AI and automation workflows, specifically within n8n. Till Simon from gotoHuman chats with Max from theflowgrammer, and they demo how gotoHuman lets you inject human review steps right into your n8n flows. Think of it as a “pause” button that sends data to a real person for a sanity check or approval before it gets processed further by your automation.

This is gold for us as we’re leveling up our AI game. We’re building increasingly complex LLM-powered workflows, and the thought of letting those run completely unsupervised can be terrifying. Imagine an LLM generating content for a client’s website – without human review, you could end up with some serious brand damage. This video shows a practical way to mitigate that risk. It’s about responsibly integrating AI, acknowledging that sometimes a human eye is still crucial, especially when dealing with sensitive data or critical decisions. Plus, the fact that Till built the n8n node himself highlights how accessible building integrations and tools is becoming!

The real power here is the ability to create guardrails for our automations. We could use gotoHuman to review AI-generated code before deployment, approve financial transactions based on AI predictions, or even just QA content before it goes live. It’s a game-changer for building truly reliable and trustworthy AI-driven systems. Honestly, seeing how easily it integrates with n8n makes me want to spin up a demo flow right now and start experimenting. It feels like a crucial piece of the puzzle for anyone trying to bridge the gap between cutting-edge AI and real-world business needs.

Date: 09/09/2025

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Okay, so this video is all about leveling up your RAG (Retrieval Augmented Generation) game using n8n. It tackles the common frustrations we’ve all experienced: RAG falling short because it misses context, fails to connect related ideas across documents, and lacks the smarts to really understand what you’re asking. It’s not just another “how-to” – it’s a “how-to make RAG actually useful.”

This video is gold for anyone transitioning to AI-enhanced workflows because it introduces three powerful strategies that address the core problems with traditional RAG. Agentic Chunking ensures context isn’t lost when documents are split. Agentic RAG gives the agent the ability to intelligently explore your knowledge base. And finally, Reranking refines the search results for precision. Imagine using this to build a support bot that doesn’t just regurgitate snippets but actually understands the user’s problem and provides comprehensive, connected solutions.

What I find really exciting is the “agentic” approach. It’s like giving your RAG setup a brain, allowing it to reason and make decisions about how to best extract information. I’m keen to experiment with the n8n template to automate tasks like onboarding new employees with personalized knowledge delivery, or even building a custom AI assistant for complex data analysis. The promise of a RAG system that truly understands the data is a huge leap forward, and definitely worth diving into.

Date: 09/08/2025

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Okay, so this video on integrating DeepEval with n8n is seriously inspiring, especially if you’re, like me, diving deep into AI-powered automation. It shows you how to move beyond “vibe testing” your AI agents in n8n and start using a proper, metric-driven evaluation framework. We’re talking about setting up a real testing system with datasets, metrics, and automated runs, all powered by DeepEval, a leading open-source AI evaluation tool.

What makes this valuable is that it addresses a huge pain point: how do you know if the tweaks you’re making to your AI models are actually improving things? The video demonstrates how to deploy DeepEval (even on a free tier!), connect it to n8n via API, and then run tests using a bunch of built-in metrics like faithfulness and relevancy. You can even define custom metrics for specific domains and generate synthetic test cases. Imagine being able to automatically log all of this in Airtable!

For me, the real kicker is the shift from gut feeling to hard data. I’ve spent way too long tweaking prompts and hoping for the best. The idea of using DeepEval within n8n to objectively measure performance – generating test cases from documents and tracking things with metrics like faithfulness and contextual relevancy – is revolutionary. I’m excited to experiment with the DeepEval wrapper and see how much more robust I can make my LLM-powered workflows. No more whack-a-mole, just solid improvements!

Date: 08/25/2025

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Okay, this n8n AI Assistant Builder video is seriously inspiring for anyone diving into AI-assisted automation. It showcases how you can literally type a prompt and n8n spins up a workflow, handling everything from architecture to node wiring. Think Calendly leads going to GoHighLevel, analyzed by OpenAI, and then personalized follow-ups. I’ve been wrestling with similar pipelines using a mix of custom PHP and brittle API integrations for years. This video shows a path to build the same, or better, in minutes, not days.

What’s really got me excited is the LangChain multi-agent example. I’ve been experimenting with autonomous agents, but the configuration overhead is a killer. The video demonstrates how n8n streamlines this, letting you define a “content swarm” where agents collaborate, using each other as tools. Imagine the possibilities for content creation, data enrichment, or even complex business logic, all orchestrated with a simple prompt. The presenter also shares how to fix common errors and iterate quickly using the sidebar co-pilot, which is golden. For me, it’s a clear signal that the future of development is about orchestrating AI, not writing endless lines of code. I’m definitely spinning up n8n and giving this a shot. That promise of going from idea to working automation without the usual JSON spaghetti is too good to ignore.

Date: 08/15/2025

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Okay, this video from Nate Herk is gold for devs like us who are diving headfirst into AI-powered workflows. Essentially, he’s giving away the blueprint for an “Ultimate Media AI Agent” built on n8n, a no-code automation platform. This agent isn’t just a simple task runner; it’s a full-fledged digital assistant that handles everything from email management and content creation (images, videos!) to social media posting and even web scraping for research. What’s really exciting is the activity logging – crucial for debugging and understanding how your AI is actually performing.

Why is this valuable? Because it’s a practical, real-world example of integrating AI into everyday tasks. We’re talking about automating content creation, social media management, and research—things that traditionally eat up a ton of developer time or require a dedicated team. It’s not just theory; Nate breaks down the cost and provides templates and workflows to get you started. Think about using this to automatically generate marketing materials for a new feature release or to monitor competitor activity and compile reports. The possibilities are huge!

Honestly, I’m pumped to experiment with this. The promise of automating social media content creation and research alone makes it worth exploring. Plus, seeing a concrete implementation of n8n with AI capabilities is super inspiring. The best part is the head start of getting templates. I have been looking into setting up n8n so this may be the final push I need to get going.

Date: 08/13/2025

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Okay, so this video is pure gold for us devs looking to level up our workflow with AI and automation. Basically, it’s a walkthrough of an n8n automation that lets you blast content to all your social media platforms—Instagram, TikTok, X, LinkedIn, Facebook, you name it—from one single spot. No more jumping between apps or wrestling with APIs! You dump your content into a Google Sheet, add a caption, connect your accounts via Blotato, and boom, you’re posting everywhere.

Why is this awesome? Because it’s a perfect example of how we can ditch tedious, repetitive tasks with no-code tools and automation. We can use this as a base, then pair it with an LLM-powered content creation workflow. Imagine: an AI drafts social media posts based on a topic you give it, then this n8n workflow automatically publishes it across all your channels. Think about the time that would save, and how much more effectively we can manage marketing for a client. It’s one of those things that really hits home to someone who’s written hundreds of http requests and OAuth integrations themselves.

Honestly, it’s worth checking out just to see how easily you can string together these powerful tools. The fact that the creator gives away the n8n template free is just icing on the cake. It’s a tangible, real-world example of how AI coding and no-code platforms can come together to seriously streamline your processes and boost your output. I’m already thinking about how I can adapt this for a client who is struggling with social media consistency.

Date: 08/06/2025

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Okay, this video on OpenAI’s new open-source model, GPT-OSS, is exactly the kind of thing I’ve been diving into lately! It’s all about setting up and using this powerful model locally with Ollama, and also exploring the free Groq cloud alternative—and then tying it all together with N8N for automation. Forget those crazy API costs!

Why is this cool? Well, for one, we’re talking about running models comparable to early frontier models locally. No more constant API calls! The video demonstrates how to integrate both local and cloud (Groq) options into N8N workflows, which is perfect for building AI agents with custom knowledge bases and tool calling. Think about automating document processing, sentiment analysis, or even basic code generation – all without racking up a huge bill. The video even tests reasoning capabilities against the paid OpenAI models! I’m already imagining using this setup to enhance our internal tooling and streamline some of our client onboarding processes.

Frankly, the biggest win here is the democratization of access to powerful AI. The ability to experiment with these models without the constant fear of API costs is massive, especially for learning and prototyping. Plus, the N8N integration makes it practical for real-world automation. It’s definitely worth setting aside an afternoon to experiment with. I’m particularly excited about the Groq integration – blazing fast inference speed combined with N8N could be a game-changer for certain real-time applications we’re developing.

Date: 07/29/2025

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Okay, this video on integrating n8n with Supabase for file uploads is seriously inspiring, and here’s why. It’s all about automating file management with a focus on the practical details that often get overlooked. The video dives deep into using n8n’s HTTP node to upload files to Supabase Storage, handling everything from authentication to generating signed URLs and dealing with errors. Crucially, it covers both public and private buckets, which is essential for any real-world app dealing with different levels of data sensitivity.

Why is this valuable for us as developers shifting to AI and no-code? Well, think about it: a huge part of AI workflows involves handling data, often files like images or documents. This video shows you how to build a robust, automated pipeline for managing that data in Supabase. It’s not just theory; it walks through the tricky parts, like dealing with binary data and setting up the HTTP node correctly. Plus, the examples of connecting Supabase real-time events to n8n for triggering automations? Gold! Imagine automatically kicking off an image processing workflow in response to a new file upload – that’s a game changer for efficiency.

For me, the most exciting part is the potential for real-world application. The video touches on use cases with mobile apps, web interfaces, and even image-to-insight AI workflows. I can immediately see how this could streamline data ingestion and processing in a ton of projects. I’m definitely going to experiment with hooking up n8n to a Supabase-backed app for automated image analysis. Being able to secure files while triggering automations? Sign me up!

Date: 07/28/2025

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Okay, so this video’s all about “Top 10 n8n Tools for 2025.” It gives a rundown of new nodes and apps to supercharge your n8n workflows, with a focus on AI tools. We’re talking things like integrating Google Gemini, AI voice with ElevenLabs, web scraping with Apify, and even AI-powered search using Perplexity. I’m seeing a lot of LLM integration, with things like Mistral and DeepSeek making an appearance too.

Why’s it interesting for us? Because it’s a direct look at how AI is being plugged into no-code platforms like n8n. Instead of building everything from scratch in Laravel or PHP, you’re orchestrating these AI services. I can immediately see using this to automate marketing content generation, improve data enrichment processes, or even build more intelligent customer support flows. Think about it: automating lead qualification using AI to analyze social media profiles scraped with Apify, then generating personalized outreach emails using an LLM through n8n. Boom!

I think what makes this video particularly worth checking out is how practical it is. It’s not just about the “what,” but the “how” of integrating these AI tools into your existing workflow. Seeing someone demonstrate how to connect these services in n8n sparks ideas for how I could apply them to projects I’m working on right now. Definitely giving this a watch and experimenting!