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Here's the most annoying thing I had to deal with when it comes to n8n: scraping data. And I'm not talking about 10 items or even 100. I'm talking about scraping 33,000 zip codes in the US. Now when I first received this project, I thought easy peasy. Use Apify, connect it with n8n and start scraping, right? How wrong I was. To lay out the scene. I built an entire system of 20 flows to scrape the data, clean it, process it, and deliver it in email form to the client. And it was working when I was scraping at a low volume. But once we increased it? Well, take a look at this. If you didn't know, each node in n8n will hold all the data until the entire flow is done. So when I brought in 1,000 rows of zip codes, that meant that every single node held 1,000 items in memory. But it got worse. For every zip code we could get anything from 10 results to 1,000 results. I should mention that we were not holding back at this point, because we were scraping all the details of every single business. So the first flow was holding at times 100,000 items in every single node, which meant that we ended up with so much data that my client's entire n8n would tank. So not knowing any better, I figured, well, let's lower the volume until it works. We kept lowering it, I redesigned the entire system until we could run 100 items each run. Which worked fine. Until he decided that he wanted to add another scraper for Instagram. I'll spare you the details on this one. But long story short, having two massive scrapers was not a good idea, and we could only run one full system at a time. After some deep digging into the issue and how to fix it, I soon realized that n8n is not built for this large-scale scraping. And even if you decided to upgrade to the best server available. It would have made no difference, and queuing with Redis would not have helped either. I mean, I had already created my own queuing system inside his cloud. The lesson I learned: use n8n for simple things, because it was not meant to handle large amounts of data. Think of n8n like Zapier or Airtable. You wouldn't try to scrape data with Zapier. So the better option is to use code, something like Python for example.

Let’s take it back to the very beginning... What was your very first experience using AI? Was it ChatGPT? Midjourney? Some random AI voice assistant you asked about the weather in 2021? Here are a few prompts to get you going: - What tool did you use first, and why did you try it? - What did you think was happening behind the scenes? - Were you blown away? Confused? Skeptical?

I’ve been getting this question a lot lately. With AI automations becoming easier to build with AI, and OpenAI releasing AgentKit, people are wondering if n8n is even worth learning anymore. But here’s the truth: if I had to start all over again knowing nothing, I’d still learn everything I could about n8n. Because when you learn n8n, you’re not just learning one tool, you’re learning how systems think. You start to see how triggers connect, how data flows, and how logic turns into results. And once you understand that, you can jump to any platform in the world and master it instantly. You become tool-agnostic, and that’s where the real freedom lies. When you learn how to build workflows yourself, you also learn lessons that can’t be taught through flashy AI demos. You start to see what automations can really do, how reliable AI actually is, and what’s possible when you combine logic with creativity. You learn how to build systems that save time, cut costs, and actually work in the real world, not just on paper. That skill separates you from everyone else trying to sell the same thing. Because when clients hire you, they’re not hiring you to drag nodes on a screen, they’re hiring you to think like an automator. They want someone who understands the logic behind the system, can identify what’s going wrong, and knows how to make it better. The people who skip this step, the ones relying entirely on “AI agents that build workflows for you”, are like someone trying to sell a cake after only seeing a picture of it. They don’t know the ingredients, how it was baked, or even the flavor. So when they try to explain it to others, they sound the same as everyone else. But when you’ve actually baked the cake yourself, you can describe the flavor, the texture, the process, and that builds trust. And in this space, trust is everything. Automation is one of the few skills in the world that directly compounds over time. Once you know how to identify bottlenecks, map processes, and connect systems, you can apply that skill to any business or industry. And the ROI is real, recent studies by Deloitte and McKinsey show companies that invest in automation see up to a 30% reduction in operating costs and often double or triple their productivity within months. The people who understand how to build and maintain these systems are the ones leading that transformation.

I scraped the date of 190 companies in the sector of medical engineering, so we can send them a advertising brochure next week. I will use Firecrawl in the future to scrape date of companies like I did it in this project or to get a summary of the website of our potential clients in the future.