Claude Code vs Codex vs Pi: Which Coding Agent Wins?

https://arena.ai/agent Could your coding agent cost twice as much for almost the same results? Melissa Pan, a PhD candidate at UC Berkeley's Sky Computing Lab, explores the hidden “harness tax”: how the system around an AI model affects its cost and performance. Comparing Claude Code, Codex, and Pi, she shares three findings: harness choice affected cost more than accuracy in these benchmarks, a simple four-tool harness remained competitive, and models performed well outside their own provider’s tools. She walks through the results and explains what it means for building useful coding agents on a realistic budget. Review the findings: https://arena.ai/blog/coding-agents-harness-tax 00:00 The hidden harness tax 00:41 Finding 1: Cost changes more than accuracy 00:54 Comparing cost and task success 01:33 Pi vs. Codex vs. Claude Code 02:06 Finding 2: Four tools can be enough 02:51 Finding 3: Models work across harnesses 03:16 Why harness research still matters 03:45 Making your AI budget go further #CodingAgents #AgenticAI #AIResearch