Hiring is hard. With hundreds of applications per role, organizations need efficient screening. LeetCode interviews offer appealing objectivity and scalability.

But they optimize for the wrong signals—systematically excluding capable engineers while rewarding interview optimization over actual job performance.

Why This Fails

Narrow measurement: Algorithm puzzles test one skill while ignoring the multidisciplinary reality of software engineering—system design, debugging, collaboration, business understanding.

Pattern matching ≠ understanding: Memorized solutions masquerade as algorithmic thinking. Regurgitating patterns under time pressure doesn’t correlate with architecting systems, debugging production issues, or working with product teams.

The irony: When performance optimization actually matters, it’s at the system level—database queries, caching strategies, network architecture. Not algorithmic complexity of isolated functions.

What Actually Matters

Real software engineering requires:

• System design thinking
• Production debugging skills
• Cross-functional collaboration
• Business context understanding
• Code review and mentorship
• Trade-off evaluation

LeetCode interviews measure none of this.

For Engineers

Build your algorithmic foundation—it’s genuinely important. Understand data structures and complexity analysis.

But recognize that grinding LeetCode is interview preparation, not professional development. The complex, collaborative work of building production systems requires different skills entirely.