Building in Public: What I Learned Building Workflow 1 of My AI Content Pipeline
June was a blur. Birthdays, Father’s Day, a family vacation. Life happened, and posting took a back seat. But here’s the thing about building something in public: the gaps are part of the story too. And the gap gave me time to actually finish something worth writing about.
Workflow 1 of my AI content pipeline is built, tested, and running. It finds blog topic ideas automatically for The Educating Entrepreneur, and it is by far the most complex of the four workflows I am building. Here is what I actually learned while building it.
Picking the Right AI Partner Matters More Than I Expected
I started with Gemini using Canvas. After some back and forth, I switched to Claude Cowork. The reason: revision.
When you are building something you have never built before, you will change direction a lot. The AI helper you choose needs to handle that gracefully. Gemini kept trying to reconcile my earlier instructions with my updates, which were often pointing in opposite directions. It got confused. The further we went, the more it drifted.
Claude Cowork pushed back when something did not make sense, and revised cleanly when I changed my mind. That combination was exactly what a work-in-progress build needed. The lesson: if you already know exactly what you want and have a tight prompt, most AI helpers will do fine. If you are figuring it out as you go, pick one that handles ambiguity and revision well.
Outdated Documentation Is a Real Problem
Some of what Claude suggested came from older documentation. And it was not just Claude – when I hit errors and turned to n8n’s own help resources, I found outdated information there too.
The fix was usually straightforward once I found the current answer, but finding it took time. This is one of those things that sounds obvious in hindsight: the tools you are building with are moving targets. Documentation that was accurate six months ago may not be accurate today. Build time for that into your expectations.
The Credential Issue I Stopped Troubleshooting
I ran into a recurring issue where credentials I created in n8n‘s credential manager would not show up in the node I was working on. My first instinct was to troubleshoot it. Then I realized it was faster to just rebuild the credential directly inside the node.
That is a small but useful mindset shift when you are building: not every problem is worth fully solving. Sometimes the workaround is the right call. Know when to debug and when to move on.
One Email Per Topic Beat One Big Email
This was the biggest design decision I made while building Workflow 1, and I am glad I thought it through carefully.
The workflow generates 8 to 10 topic ideas per run. My first instinct was to bundle them into one email so I could approve or reject everything in one shot and keep my inbox clean. Clean inbox, efficient review. Made sense.
But when I thought about what a real review of each topic looks like, the batch approach fell apart. To actually evaluate an idea, I need to read the angle, think about my audience, and decide whether it is worth pursuing. Doing that for 10 topics in a row, in one sitting, is exhausting. I would rush through the end, or leave the email flagged and forget where I was.
One email per topic means I can review one now, stop if I need to, and pick up exactly where I left off next time. No flagging, no losing my place. A slightly messier inbox is worth it.
Why I Scrape Specific Sites Instead of the Open Web
Workflow 1 pulls content from a curated set of sites and subreddits – including r/smallbusiness, r/Entrepreneur, Entrepreneur.com, Smart Passive Income, and Side Hustle Nation – rather than searching the open web. Two reasons.
First, consistency. This is a new build with a lot of moving parts. The fewer variables, the easier it is to spot what is working and what is not. Limiting the sources gives me more predictable input, which means more predictable output.
Second, relevance. The sites I chose are places where people who want to learn about entrepreneurship are already showing up. That means the questions being asked and the topics being discussed are already filtered toward my audience. The signal-to-noise ratio is much better.
What’s Next
Workflow 2 is the verification step. Once I approve a topic idea in Workflow 1, Workflow 2 searches the web to check whether the claims behind the topic actually hold up. It distinguishes between ideas backed by real data and ideas that are just someone’s opinion on the internet. That matters for a blog that is supposed to teach real, reliable fundamentals.
I will write about that build next. Life has slowed down, and I am back to posting consistently. Thanks for following along.