How I Use n8n for GenAI, Prototyping, and Automation

I didn’t “adopt a tool”; I have found an engine - I am hooked, and a Fan!

n8n has become the glue between my ideas and production. Simple, fast and visual when I need speed, code-friendly when I need power. It lets me ship GenAI workflows, automations and even guilt invoking messages to myself - Jason, go run!

After 3+ years of Retool for rapid prototypes and CMS back-office, n8n completes the stack. If those two ever merged, it’d be chef’s-kiss perfection. 👨‍🍳

Why n8n clicked for me

• Fun: Like Lego levels of almost illegal Fun!
• Visual: Incredibly easy to show off as a flow-chart with clear steps, loops and boundaries.
• Built in CRON Server: For any automation, setting off a web-hook, or vice-versa, it's there, ready - and the rest of my code stack can exist within Serverless awaiting a wake-up call.
• AI Agents: Almost too easy to orchestrate, prompt and deploy, very fast iterations and feedback cycles. And cheap too!
• Builder speed: Drag-drop for flow, loads of connections to established API's, JS/Python nodes for the hard(er) bits.
• Own your stack: Self-hostable, you control the updates. I am using Hostinger
• Composable: Webhooks, queues, DBs, files, CMSs, Slack, email—everything snaps together.
• Safe by default: Retries, error branches, and circuit-breaker patterns are easy to implement.

Flagship automations I run with n8n

• AI article pipeline from Reddit (e.g. /r/progresspics): Crawl posts + comments → score “most valuable” insights → prep data in comprehend-able format → prompt an LLM Agent → publish to Contentful → approve in CMS → live. It’s my “research → write → ship” robot.

AI Generated Article: From Stalled to Strong

• Crucial Emails → Telegram: Some emails, I want immediate awareness in the form of a push notification. For instance "You have won the Euro Lottery!!" (would be odd as I don't play it)
• Flight price tracker → chart: Daily fetch → diff prices → produce a time-series JSON → render a line graph for alerts/decisions.
• Strava-style motivation nudges: If I haven’t run in 10 days: compute streaks → generate a playful AI nudge → DM me on Slack with a mini dashboard image.

My GenAI WorkFlow

I find the SubReddit /r/ProgressPics so inspiring. A community of 2.4m that shows before and after pictures, where 3,100 posts are created every week and 176k weekly visitors, its a massively busy space, with so much great upvoted content to inspire.

That being said, what is the secret sauce? What are the commonalties in the stories, that you can use for your own mission toward your own health goals. And this is where I set to work in experimentation. The short version being, that I collect 100 of the most upvoted posts in the last week, and find the OP's corresponding replies and comments to the inevitable question of "How did you do it?". This being stored in a database temporarily to avoid overloading the workflow with context. Prepare the data in a flat and relevant means, making sure to take into account strong upvotes and scoring metrics, and present this in a format that one of the AI models can comprehend and create an article. Initially I'd send this context to Slack for lift-and-shift, but as my personal website uses Contentful, I went deeper, and had the content prepared to be pushed in the "Rich Text" format required (not as easy as expected - and this is where it would be cool if n8n allowed for transformations-as-a-node where you could have your own bespoke option to reuse). With that done the push to Contentful was straightforward enough with REST - I await this to be added to the Node (for now you can pull content).

And the proof point with the first go: Article #1 - And what did it cost? About 1 US cent!

Just one example, from a niche, where maybe, there are many other interesting pieces of gold with Reddit and otherwise. Topics and Comments that could substantiate a business need, or warrant a product - the opportunities, perhaps endless, if you're imagining hard enough.

Keeping Actively 🏃 Accountable

I am always trying to keep fit - who isn't - and Strava is great, but it doesn't quite have that DuoLingo streak effect dialled in. That accountability partner you need when you least want it.

This workflow wasn't hard to do, I made a strava schema with activities of my own and connected to the Strava API which is a privilege of paying for the "premium". So there are so many interesting takeaways in this database, for instance how infrequently I have been indoor-cycling after Covid, vs. the impressive amount I was during Covid. Maybe I don't need that Zwift subscription anymore, or maybe I just need to use it more as the winter approaches - I now have that data to back up a decision or indecision. I digress - for this example, I have used that very database for the last months worth of activities, and as you can see below, it's tracking and illuminating how many KM's I am moving per day (Black Line), and the amount of time I am running or walking or even hitting the gym (Bar graphs).

This beautifully simplistic graph gets sent to my Telegram account each day (easy to setup), and now gets pushed to me consider... just in time, to get that "run" in. 🏃

Tracking Flight Prices Visually

Over the past few weeks (hours) I’ve been tinkering with something that scratches both my automation itch and my travel bug: a flight price tracker that turns messy email alerts into clean, visual graphs straight to my Telegram App.

Here’s how it works:

1. Source of truth – my inbox Google Flights sends me price alerts whenever a tracked route changes. Those alerts land in my email, filled with HTML tables, snippets, and prices. Normally, they just sit there.
2. Enter n8n Using an n8n workflow, I parse those emails, extract the key data points (route, dates, trip type, passengers, old vs new price, and the tracking link), and push them into a Postgres table. Each alert becomes structured data, ready to query.
3. From alerts to itineraries Multi-city routes, round trips, and one-ways get normalized. Origins and destinations are split, dates are parsed into proper YYYY-MM-DD fields, and duplicates are filtered out. This means my database holds a clean timeline of how prices shift over time for the same trip.
4. Automation that compounds I can set up this job to run daily, so every new Google Flights alert I track automatically gets ingested and visualized. No setup required beyond tracking the flight in Gmail — it’s essentially another way to read my data in a constructive way. The system builds itself as I go.
5. Visualization Here’s where it gets fun. With n8n’s Code nodes and QuickChart, I generate line graphs that show the price fluctuations for each itinerary. The charts are labelled with the route and travel dates, so it’s instantly clear what you’re looking at.Example: Berlin → Málaga (Dec 26 – Jan 3) You can see at a glance how the fare has bounced up and down over weeks of alerts.

Why Bother?

Airlines play games with pricing. By storing and visualising alerts, I can spot patterns: dips in off-peak days, weekend surcharges, or that one week where prices crashed €200 before bouncing back. And perhaps next year, this will give me the confidence to pick my booking dates better, timing purchases to save money rather than guessing.

Closing

n8n is where my ideas meet execution. It’s not just workflow automation; it’s a creative rig for GenAI, data, and product. I use it to prototype, to ship, and—most importantly—to learn faster than my problems evolve.

Of course I can put a lot of these functions into my own code stacks, and I do - but for the sake of expedited experimentation, and having automation that I can just leave to do its thing, I don't even need to "graduate" everything to the "old" way of thinking.

If this resonates, or perhaps it doesn't, but you have ideas, get in touch - I love solving problems.