Coding agents increasingly undertake development tasks in mature enterprise repositories, yet existing benchmarks offer limited insight into whether they fulfill complete Product Requirement Documents (PRDs) and where delivery breaks down. Issue resolution and development from scratch leave incremental PRD fulfillment underexplored, while isolated tests provide incomplete evidence of business and integration requirements. We introduce PACE, a benchmark of 43 enterprise tasks with 750 expert-audited Code Points. It combines requirement reconstruction, criterion construction, and evidence-based evaluation to measure PRD fulfillment and connect delivery gaps to agent behavior. Across 11 model--scaffold configurations, most scores fall between 52.1 and 78.1; GPT-5.6-Sol achieves the highest complete-delivery rate of 14.0\%. Incomplete implementation and missing integration are the principal bottlenecks: producing individual components does not ensure a complete delivery. Evaluation achieves 95.2\% agreement with expert consensus, with lower case-level variation across judging records than repeated executions. Beyond model comparison, the benchmark provides actionable feedback for harness refinement: diagnosis guides targeted improvements, and successive harness releases raise mean performance from 59.4 to 63.0 using the same model and task suite. Code is available at https://github.com/TianqiLiu1/PACE-Bench.

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