Requirements and user stories rarely capture daily frustrations or informal workarounds.Many inefficiencies only become visible when watching users perform real tasks.Skipping this step often leads to solutions that look right but feel wrong.
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In single-org projects, small shortcuts often feel harmless and efficient.When the same solution must work across many orgs, those shortcuts quickly become liabilities.This transition forces a deeper level of architectural discipline.
Early-career professionals often see limits as frustrating restrictions.There is a tendency to bypass or work around them to meet short-term goals.Over time, this approach can lead to brittle and hard-to-scale systems.
Support agents often deal with varying products, warranties, SLAs, and entitlements.Hard-coded logic quickly becomes unmanageable as combinations increase.This slows resolution and increases agent dependency on tribal knowledge.
My language model produces fluent responses.Even when it does not know the answer, it sounds confident.Users sometimes trust incorrect replies.There is no indication of uncertainty.
My LWC works smoothly when testing with small datasets, but performance drops noticeably with real production data. Page loads become slower and interactions lag. I’m not doing anything obviously heavy on the client side. I’m trying to understand where the ...
