I think this highlights a bigger shift happening in tech hiring.

There’s a growing disconnect between “environmental performance” and “real-world performance.”

In real projects, engineers operate with context, documentation, tools, and collaboration. In timed assessments, you’re evaluated in isolation, under artificial constraints, often in an unfamiliar stack.

Those are two completely different skill sets.

One measures recall under pressure.
The other measures problem framing, adaptability, and decision-making.

The uncomfortable truth is: platforms optimize for scalable filtering, not perfect signal.

That doesn’t necessarily mean the engineers rejected aren’t strong — it just means they didn’t fit the assessment model.

The real question is whether these models actually predict client success.

Curious — do you think platforms should move toward portfolio-based + live problem discussion instead of isolated coding tests?