The Future of AI Code Generation: Benchmarking Claude, GPT-4o, and Gemini 2.0

Evaluating Real-World Agentic Workflows

Evaluating coding LLMs solely on synthetic LeetCode problems fails to capture real-world engineering performance. When given complex 50-file codebases with inter-dependent module imports, agentic reasoning and self-healing error analysis differentiate true engineering assistants from simple auto-completers.