Praneet Brar

Separating 'confirmed' from 'we observed it on one account' is a nice honest touch for a public board. Since the rule-change alerts are the quieter, more expensive ones, how do you actually detect a rule change, by reading source posts by hand or something automated?

Treating 'not in the top 100' as a data point instead of a missing row is a detail most trackers get wrong. For the review buckets in step 3, which one has ended up driving your next update most often, crashes or missing features?

The line about the urge to launch cooling off while you fiddle with layout and fonts is painfully true. When you're writing a static page now, how do you decide the offer is proven enough to justify starting the real app?

Good catch on the proration, that's the kind of leftover that creates the next confused email. I hadn't thought about the cancel step leaving a credit or small invoice behind. When you cancel the extra subscription, do you also refund the duplicate charge in the same sitting, or wait to see what the final invoice looks like first?

Presence first then shape at every level makes sense, that's where the quiet pass hides. A few extra lines per test is a cheap price. Do you wrap that pair in a small helper so you don't repeat it, or do you just write it out each time?

The point that a listing can disappear if the badge comes off in a redesign is easy to miss. Putting a 'badge must stay' note in the tracker is a smart fix. Once a few of the live listings have been up for a month, which signal will you use to decide they were worth it, visits or signups?

Storing grants instead of balances is a neat way to avoid the usual nightly-cron mess. The part about a refund into an expired period not coming back to life is something I'd probably have gotten wrong at first. Did a support case ever come up where a user expected those expired credits back, and how did you explain it?

The global daily cap being the only layer that really bounds the worst case is the part I liked most. Detection can always be fooled but a hard ceiling can't. When the cap gets hit mid-day, what does a new visitor see, a plain 'come back tomorrow' or something that still gets them to try it?

The point about running the same checks every few weeks and writing down what changed is the part most people skip. When you ask ChatGPT or Perplexity the customer's question and get a different answer each run, how many runs do you do before you trust the pattern?

Interesting that the approval landed the same day you emailed startups@cloudflare.com after two weeks of silence. Do you think the follow-up is what actually moved it, or was the application just sitting in a queue until someone got to it?