As I understand the post, its idea is that a rationalist should never "start with a bottom line and then fill out the arguments".

Ooh! I see a "should" statement. Let's open it up and see what's inside!

*gets out the consequentialist box-cutter*

... its idea is that we will get worse consequences if we "start with a bottom line and then fill out the arguments."

Hmm. Is that what "The Bottom Line" says?

Let's take a look at what it says about some actual consequences:

If your car makes metallic squealing noises when you brake, and you aren't willing to face up to the financial cost of getting your brakes replaced, you can decide to look for reasons why your car might not need fixing. But the actual percentage of you that survive in Everett branches or Tegmark worlds—which we will take to describe your effectiveness as a rationalist—is determined by the algorithm that decided which conclusion you would seek arguments for. In this case, the real algorithm is "Never repair anything expensive." If this is a good algorithm, fine; if this is a bad algorithm, oh well.

In other words, it's not like you're sinning or cheating at the rationality game if you write the bottom line first.

Rather, you ran some algorithm to generate that bottom line. You selected that bottom line out of hypothesis-space somehow. Perhaps you used the availability heuristic. Perhaps you used some ugh fields. Perhaps you used physics. Perhaps you used Tristan Tzara's cut-up technique. Or a Ouija board. Or following whatever your car's drivers' manual said to do. Or your mom's caring advice.

Well, how good was that algorithm?

Do people who use that algorithm tend to get good consequences, or not?

Once your bottom line is written — once you have made the decision whether or not to fix your brakes — the consequences you experience don't depend on any clever arguments you made up to justify that decision retrospectively.

If you come up with a candidate "bottom line" and then explore arguments for and against it, and sometimes end up rejecting it, then it wasn't really a bottom line — your algorithm hadn't actually terminated. We can then ask, still, how good is your algorithm, including the exploring and maybe-rejecting? This is where questions about motivated stopping and continuation come in.