I recently got pulled into a freelance project involving n8n, a tool I’d honestly never used before. I was consulting on an automation build with a Telegram bot, working alongside a junior developer. While I can’t share the project specifics due to NDA, I wanted to reflect on the experience — both the technical learning curve and the real takeaway: how AI is changing how we approach engineering.
Walking into the Unknown (with Docs and Tutorials)
n8n is one of those tools I’ve seen pop up on dev feeds — a “low-code” automation platform that connects APIs and services using visual workflows. Cool idea. I skimmed the docs, followed a couple of tutorials, and started to get a feel for nodes, triggers, and how data moves between them.
But I’ll be honest — I didn’t have deep intuition for the tool. Unlike Next.js, React, or even scripting tools like Zapier, n8n felt unfamiliar. I hadn’t built anything substantial in it. That lack of reps made it harder to confidently guide the implementation.
The Challenge: Bulk Messaging via Telegram Bot
The core problem: how do you send a batch of messages to a Telegram bot using n8n? Simple idea. But when you don’t fully grasp how execution loops, JSON mapping, or Telegram nodes work — you start second-guessing every step.
I looked through examples and considered different node setups, but my flow wasn’t producing results. Then the junior dev I was working with said something that changed everything.
“What if we just ask Claude?”
The Claude + Cursor Power Combo
Instead of brute-forcing node connections, we dumped the n8n JSON workflow file into Claude (Anthropic’s AI) and asked it:
“How can I implement bulk Telegram messaging in this workflow?”
Claude parsed the JSON, understood the flow, and suggested where to add loop nodes, where to inject variables, and how to structure the messages. We copied those ideas into Cursor, made adjustments, and like magic — it worked.
Why This Was an Important Moment
Watching this unfold reminded me of the future of engineering:
- It’s no longer just about how much you know — it’s how fast you can bridge the gap between what you don’t know and a working solution.
- Pairing junior-level intuition about a tool with AI-powered insight was the perfect blend.
- It’s less “let me memorize the platform” and more “let me co-pilot with AI and get this shipped.”
And while I still need to build more projects in n8n to really get comfortable, this experience reminded me: it’s okay to not know everything — as long as you know how to ask the right questions and iterate quickly.
Final Thought
n8n is a promising tool. I’m planning to keep experimenting with it — maybe build my own Telegram lead collector, content pipeline, or portfolio notifier. But more importantly, I’m doubling down on a workflow that embraces AI as part of the dev stack.
Forget gatekeeping. The smartest devs today are the ones who work with AI, not around it.