No synthesis yet. Place papers in this thread, then click Update synthesis.
Replacing the orchestration harness alone, while holding models and tasks constant, cuts enterprise agentic AI token spend by 38% and cost per task by 41%, with task-completion quality holding at parity or improving.
Blended across six models: cost per task fell 41% ($0.21 to $0.12), median wall-clock fell 44% (48s to 27s), tokens per task fell 38% (14.2k to 8.8k). Quality per dollar rose 82%; task-completions per million tokens rose from 54.9 to 92.0 (+68%). Per-model cost reduction ranged from 33% (Gemini 3.1) to 61% (Gemini Flash 3.5), with no model showing a cost increase. Headline quality was 0.78 to 0.81 (not statistically significant at n=22). All 7 quality regressions were on the three smaller/weaker models, concentrated in orchestration-heavy tasks. Harness leverage (quality gain correlated with baseline model strength) was r=0.99 across n=6 models.