Exercise 1: What Made Ticket 1 Recognizable as N+1 Before Checking Logs — Possible Solution
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WHAT THE SYMPTOM PATTERN WAS
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Per this chapter, "load time scales with a specific count (organization
size), not with overall traffic or time of day." The dashboard was
instant for small organizations and took 12+ seconds for organizations
with hundreds of users - load time tracked directly with a count
specific to each organization.

WHY THIS MATCHES CHAPTER 6's OWN REASONING
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Per Chapter 6's own worked example (the order history page), "a single
slow query wouldn't care how many orders a particular user has," while
"an N+1 pattern would scale exactly this way" - proportional to how
many items are being iterated over. Chapter 1's scoping instinct in
this capstone is a direct reapplication of that exact logic: since load
time scaled with organization size (the number of users being iterated
over), and a single slow query wouldn't produce that specific
correlation, N+1 was the far more likely explanation before any log was
opened.

WHY RECOGNIZING THIS FIRST WAS VALUABLE
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Forming a specific, testable hypothesis (N+1, not a single slow query)
before checking the query log meant the query logging step was used to
confirm a theory already narrowed down, rather than searching broadly
with no starting expectation - the same efficiency gain Chapter 6's own
worked example demonstrated.

WHY THIS WORKS AS AN ANSWER
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It identifies the specific symptom pattern (load time scaling with
organization size) and explicitly connects it to Chapter 6's own stated
reasoning for why that exact pattern points toward N+1 rather than a
single slow query.