For agentic code generation, invest in reasoning capability and effort rather than external tools—stronger models and higher reasoning settings prevent failures at their root, while testing tools don't catch the reasoning errors that actually cause failures.
This study evaluated 90 runs of an agentic coding assistant building the same application, testing whether extra tools and prompts improve code quality. Results show that increased reasoning effort (not testing tools) dramatically improved first-try reliability, raising perfect runs from 28% to 89%, while a testing tool added 42-68% cost with no functional benefit.