We fix the reported findings, but similar issues keep returning.Each test feels like starting over again.I’m trying to understand why progress feels stalled.
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An LWC works perfectly in sandbox, but in production it occasionally fails without showing meaningful errors. Users just see a broken component or missing data. Debugging is difficult because there’s no visible stack trace. I’m trying to understand why this ...
I’ve already removed SOQL queries and DML operations from loops in my Apex code. Despite that, I’m still hitting limits in real production scenarios with large datasets. The logic itself isn’t very complex, but the limits seem easy to hit. ...
Everyone is alerted quickly, but actual remediation takes longer than expected.Decisions feel slower and coordination breaks down under pressure.I want to understand what usually causes this and how teams improve response speed.
We started with a few simple record-triggered Flows, and they worked well initially. Over time, more conditions, paths, and updates were added to handle new requirements. Now debugging and updating these Flows feels risky and time-consuming. I’m trying to understand ...
Security feels manageable with a few APIs, but issues grow as services multiply.Different teams implement controls differently.I’m trying to understand how organizations keep API security consistent at scale.
I trained a Keras model that gives good validation accuracy.After saving and loading it, the predictions become completely wrong.Even training samples are misclassified.Nothing crashes, but the outputs no longer make sense.
Overall metrics look acceptable.But certain users receive poor predictions.The issue isn’t uniform. It’s hard to detect early?
Tests pass, but production fails. I want to understand why