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A Few Months of AI Teaching Content: What Gets Traffic and What Doesn't

Traffic observations after a few months of AI teaching content — the lecture overflowed, the job-search demo got the most questions, the concept I thought mattered most pulled the least, and the Obsidian video went against the wind.


After a few months of making AI teaching content, lining up a few of those old notes side by side actually traces out a pattern: what gets traffic and what doesn’t often doesn’t line up with what I personally think matters.

The Demand for the Lecture Is Real

A free lecture went from 200 to 350+ signups. Sales reps, PMs, marketers, researchers, designers, accountants, engineers, cram-school owners — every profession showed up. They’re all asking the same thing: “Has AI changed the workplace? Am I ready?”

The Job-Search Demo Got the Most Questions

Cut out the AI job-search demo segment from the 5/10 lecture and put it on YouTube: https://youtu.be/HcADayRCJMg. Claude Code customizes resumes for six companies in one pass, saving five evenings of manual work. This was the most-asked segment from the live lecture.

The Thing I Think Matters Most Pulled the Least

But turn the camera to the video I cared about most, and the numbers drop.

The advanced concept I personally consider most important — “on-demand loading and indexing” — actually pulls less view count. Could be I didn’t explain it plainly enough; could also be that even though everyone knows quota matters, the video didn’t aggressively tie context management to quota. Context management saves more than tokens; it raises model performance too.

The One Against the Wind

There’s another kind of low traffic — not a failure to explain it well, but shipping it straight into the wind on purpose.

When a wave of folks recently championed HTML over markdown, I shipped an honest video about my own Obsidian knowledge base. Does that count as going against the wind? https://youtu.be/EhMKfG1dvnI


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