Two Weeks of Shipping n8n AI Workflows in Public: 11 Posts, 200 Views, and What the Tests Taught Me

Two weeks ago I wrote a 14-day calendar for this account: one post per slot, all about building AI workflows in n8n, and a rule that every tutorial had to be tested on a real n8n install before it went out. Today is the last day on that calendar, so this is the scorecard.

Views, reactions and comments as shown on my dev.to dashboard on 30 Oct, sorted by views:

A few honest caveats: the newest posts have had less time to collect views, the numbers are tiny so one share can flip the order, and I don't know how much of this traffic came from search versus the dev.to feed.

The calendar had 14 slots. Three of them (From Scratch #1, a post about running workflows on a 1.5B local model, and From Scratch #2) never went out. I didn't have them tested in time, and I'd rather skip a slot than publish a tutorial I hadn't run. One post (From Scratch #4) went out about six hours late because the first attempt failed before publishing.

The headlines changed too, and every time it was because of the test:

If I'd written these from memory, every one of those posts would have had a made-up number in it.

1. Failure stories beat tutorials, at least for a new account. The top four posts by views are a checklist, a list of failures, an opinion post and a test that failed. The two "From Scratch" tutorials I published have 2 and 4 views. My guess is that people click on "here's what broke" faster than "here's how to build X", but with these numbers it's a guess, not a finding.

2. Real test numbers are the content. The posts that got comments all had a concrete, slightly embarrassing number in them. "48 of 48 replies started with 'Thank you for'" is more interesting than "here's a review-reply bot".

3. Small local models are great for testing. I ran most tests on Qwen 1.8B in Ollama. It fails often, which is exactly what you want when you're testing the guard rails around a model. I haven't tested the same workflows on a big hosted model, so I can't tell you how much less often they'd fail.

4. "Green" doesn't mean "worked". This came up in almost every test: a workflow that finishes successfully but didn't post the Slack alert, a checker that passes a post that says the opposite of the blog, a webhook that returns HTTP 200 with an empty body. Check the output, not the status.

5. #discuss posts need an audience first. My "most boring task you've automated" post got 4 views and 0 replies. On a brand-new account, nobody's there yet to discuss with.

6. Not everything I built is good enough yet. I also submitted templates to the n8n Creator Hub. One was published and two were rejected as "too basic". Fair. The next ones need to do more.

Several of the improved workflows from these posts (the setup guard from the import test, the hardened email triage, the validated blog-to-social workflow, the owner-voice review replies) are shown as code inside the articles but aren't in the GitHub repo yet. That's the first thing on my list.

Based on the numbers above, the plan for the next two weeks is fewer posts, each one built around a real test with a real number in the title, and fewer pure tutorials. If a tutorial goes out, it'll start with what broke.

My free n8n AI workflows are in arkintof/n8n-ai-agent-workflows.

If you've grown a technical blog from zero: what actually moved the needle for you in the first month? And which of the tests above would you want to see repeated with a bigger model?

Written with AI assistance; workflow built and tested by me.