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.
Short version:
- 11 posts are live on this account (one went out the day before the calendar started). From the 13 calendar slots before today, I shipped 10, skipped 3, and published 1 late.
- They've had about 200 views in total, 10 reactions and 7 comments. That's small. I'm writing it down anyway, because "small" is what week two of a new account actually looks like.
- The posts about something going wrong did best. The silent-failures post got 6 of the 10 reactions and 3 of the 7 comments. My step-by-step tutorials got the fewest views.
- The testing was the most useful part. Almost every tested article ended up with a different headline number than the one I planned, and one ended up with a better number than I expected (3 failures, not 4).
The numbers
Views, reactions and comments as shown on my dev.to dashboard on 30 Oct, sorted by views:
| Post | Views | Reactions | Comments |
|---|---|---|---|
| Workflow or AI Agent? The 5-question test | 50 | 0 | 0 |
| 7 silent failures in n8n AI workflows | 41 | 6 | 3 |
| When should you NOT use an AI agent in n8n? | 32 | 0 | 0 |
| I import-tested 10 of my own workflows. 3 failed | 30 | 0 | 0 |
| I sent 20 prompt injections to my email triage bot | 22 | 2 | 1 |
| Build an AI lead qualifier in 15 minutes | 12 | 0 | 0 |
| What's the most boring task you've automated? (#discuss) | 4 | 0 | 0 |
| 8 blog posts into 120 social posts (From Scratch #4) | 4 | 1 | 2 |
| 10 LLM agents for small businesses | 2 | 0 | 0 |
| Review-reply bot opened 48 of 48 replies the same way (From Scratch #3) | 2 | 1 | 0 |
| My lead qualifier scored an SEO spammer 85/100 | 1 | 0 | 1 |
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.
What I planned vs. what I shipped
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:
- I planned "my lead qualifier scored a spam bot 9/10". The real test scored an SEO spammer 85/100, so that became the title.
- I planned "I import-tested 10 workflows, 4 failed". On a fresh install, 3 failed: two posted to a placeholder Slack URL that redirects to Slack's docs and shows up as a green "success", and one used an RSS feed my test machine couldn't reach.
- I planned "hardening an LLM node that reads customer emails". The test found that 12 of 20 injection emails worked on the naive version, and the "safer" prompt let 13 through. Moving the decisions into code took successful injections to 0 out of 60 runs, but that version also stopped paging the one real outage email.
- I planned "one blog post into 5 social posts". The naive version left the link out of 93 of 120 posts, and when I read the "ready" posts from the validated version myself, 10 of 21 got the blog post wrong.
If I'd written these from memory, every one of those posts would have had a made-up number in it.
Lessons
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.
What's still unfinished
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.
What's next
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.
Top comments (1)
The rule that every tutorial had to run on a real n8n install before publishing is the part I'd keep no matter what the views do. It's also why the "3 failures, not 4" correction happened at all. Posts about something breaking getting the most reactions matches what I've seen too: people search for the error they're stuck on, not the happy path. For the next round, would you consider ending each tutorial with the one failure you hit while testing it? That's often the part readers bookmark.