- Are you sure that temperature and other nondeterminism isn't affecting your output?
- Are you sure you're not being routed through an A/B test at this moment?
- Are you sure there's not a bug affecting the model at this moment?
- Are you sure that you picked the right model and effort level?
- Are you sure that your result generalizes across providers?
- Are you sure that you set up the correct level of sandboxing and the agent can't e.g. look at a sister directory or git history in the current directory for answers?
- Are you sure that the agent isn't leaking answers in memory or its conversation history?
- Are you sure that tool calls aren't somehow affecting results?
- Are you sure that your results are robust, i.e. you see the same results with mild tweaks to the prompt?
- Are you comfortable keeping your blog post live when your results are invalidated next week with the next model launch?
And that's just a quick list off the top of my head.
I personally decided that it wasn't worth it, I'm glad that Dan decided to publish his. Frankly I think we could use a lot more of these "I ran these 2 techniques side by side and here's what I saw" anecdata, because most people who promote prompt techniques can't produce a single prompt they ran twice because they never actually tested it per se.
Edited to add: formatting + the word "promote"