12 tasks, 7 domains, 3 execution modes — with a human baseline
The falsifiable questionDoes orchestrated multi-agent execution actually beat a single agent — and a human — on real initiative-level work, measured the same way every week?
External validation withheld until judges or reproductions come from outside the project.
Baseline
Two baselines, run through the identical harness: a single agent with the same tools, and a human doing the same task. Most agent demos compare against nothing.
Method
A public benchmark repo (useorgx/autonomous-initiative-benchmark): a 15-task catalog across three tiers, 12 tasks live across 7 domains, each run in 3 execution modes. Bundle validator and scorecard recompute keep results honest; methodology is published, with the literature it builds on cited.
Measured result
59 result bundles committed with numeric per-task scores. A verified gpt-5-nano run completed 12/12 tasks through the bundle validator. Instrumented-worlds eval: pass^k = 1.0 on 4 of 5 worlds, including an 8/8 on the six-trap arithmetic world.
Where it broke
Catalog coverage was 12/15 at the June gap analysis — three tier-3 tasks were specified but not yet runnable. And 1 of 5 instrumented worlds did not hold pass^k = 1.0. Both gaps are documented in the repo, not smoothed over.
Updates
- Published to the ledger.
Next test
Independent judges scoring runs they did not build — then the E column gets earned.