Five measured kernels.
One operator.
Operator-augmented Claude Code + Opus 4.7 measured against the Artificial Analysis Coding Agent Index field average. Seven-day window. Raw JSONL extraction across 98 session files and all subagents. MO§ES leads every measured economic category: cache discipline, compression cascade, token efficiency, throughput, and cost per line of code shipped.
Live HTML · all 13 published field models · full fidelity · open standalone ↗
Note · Numbers above reflect dashboard window (21 parent sessions). Revised kernels below reflect raw JSONL extraction across 98 session files including all subagents.
Raw JSONL · 98 session files · all subagents · 2 bars per chart · open standalone ↗
Token breakdown · field cross-cost · per-kernel significance · open standalone ↗
7,327 ÷ 5 turns/task = 1,465 tasks. $/LOC: AA = cost_per_task ÷ 20 LOC (industry SWE-Bench convention). MO§ES = $23.33/wk subscription ÷ 35,242 actual LOC = $0.000662. The convergence of leadership across both regimes, isolated benchmark runs and sustained product builds, is the structural result.
Field data extracted from artificialanalysis.ai/agents/coding-agents on 2026-05-14. MO§ES values measured from operator-reported 7-day window. Operator: DJM · burnmydays · Ello Cello LLC.
