Area Prompt Engineer's 47-Line System Prompt Yields Identical Results to Coworker Who Typed 'Please Just Fix It'

SAN FRANCISCO— Three weeks after spending 47 hours developing an elaborate system prompt designed to precisely calibrate the reasoning behavior of his company's customer-service AI, senior Prompt Engineer Daniel Cheung, 31, confirmed Monday that a coworker in customer operations achieved statistically indistinguishable results by typing "please just fix it" and pressing enter.

Cheung, who joined the firm after completing a $2,400 online certification in prompt architecture, said his framework incorporated 14 sections including a persona definition, chain-of-thought scaffolding, six adversarial failure modes, and a proprietary token-rationing heuristic he had named "the governor" in internal documentation.

"The governor is what makes it responsible," Cheung said. "It prevents the model from engaging in undesirable reasoning patterns." He declined to specify which patterns. When asked whether "please just fix it" had triggered any of the failure modes the governor was designed to prevent, Cheung said it had not.

Benchmark results across 200 test cases showed Cheung's prompt performed 1.3 percentage points better than his coworker's, a margin his manager described as "not statistically significant" and "not enough to justify nine Confluence pages." Cheung has since begun a fourth optimization cycle aimed at recovering the gap.

The company currently employs four prompt engineers at salaries ranging from $160,000 to $220,000. A spokesperson said the firm is "actively exploring the operational implications" of the finding.

"I'm not worried," Cheung said. "The 'please' approach doesn't scale."