2026-06-04: The Aggregate Hid Two Weak Masters

The number was 0.673. It had been a number like it every night for two months — one aggregate overall score, gated against a threshold, honest to four decimal places. A candidate at 0.65 was below the gate. One at 0.69 was below the gate. One at 0.72 might have been above. The number behaves exactly the way a threshold is supposed to behave. It hides nothing, except — as it turned out — which masters were carrying which others.
Tonight’s autoresearch picked four LGD rungs at LADDER slots 0-3 and produced exp-20260604-010005: overall 0.673, a routine non-promotion. The breadcrumb pipeline wrote its NO-OP and moved on. Then we ran a new post-hoc tool, aggregate_per_master.py, against the same eval_results_full.json the breadcrumb had already accepted. The per-master table fell out.
| master | n_cases | raw | shrunk | perfect |
|---|---|---|---|---|
| ahsoka | 19 | 0.541 | 0.568 | 5 |
| mundi | 13 | 0.606 | 0.623 | 3 |
| cilghal | 16 | 0.645 | 0.650 | 3 |
| mothma | 10 | 0.658 | 0.661 | 5 |
| jocasta | 14 | 0.696 | 0.689 | 5 |
| windu | 16 | 0.731 | 0.716 | 7 |
| quigon | 11 | 0.773 | 0.740 | 5 |
| yoda | 10 | 0.775 | 0.739 | 6 |
The overall is the arithmetic mean of the eight cells: 0.673. The variance across the cells is 0.18 between the bottom and the top. Ahsoka and Mundi sit roughly twenty points below Yoda and Quigon — who, in turn, pull the average up enough to make the bottom feel survivable. The aggregate was true and useless at the same time.
Why this number lives
Section titled “Why this number lives”The Sanctum council has eight named masters, and each one owns a behavior surface. Cilghal handles family and health. Windu handles security and screen-time. Mundi handles deal-flow and investor comms. Quigon handles infrastructure and ops. Yoda handles voice and conversation. Jocasta handles design and comms. Mothma handles legal and compliance. Ahsoka backs Cilghal on family-secondary. The eval framework already tags every case with the master who is supposed to answer it — then promptly throws the tag away and computes one mean across all 109 cases.
There were good reasons for the simplification. Per-master scoring is statistically fragile when a master has four cases: one flipped answer swings the score 25 points. A naive floor-veto on a single noisy 25-point swing would have killed an otherwise-fine candidate every other night. So no per-master scoring existed. The aggregate carried.
The cost was tonight’s finding. The average has been hiding the weakest master in the system — Ahsoka — and the master we most want to lift, Mundi, who handles the VC work, has been the second-weakest. Every “fix identity” or “fix jailbreak” lever we have pulled at the parameter axis or the data axis has averaged across all eight masters. The noise ate the signal.
The math that lets the signal through
Section titled “The math that lets the signal through”Stone 1 of the master-jedi-council arc shipped in two commits late this afternoon. It adds a single post-hoc tool that reads the existing eval JSON without touching the eval framework. Per-master scores are grouped, then Bayesian-shrunk toward the overall mean with a prior strength of k=5. A master with sixteen cases gets ≈76% raw signal and 24% prior. A master with four cases gets ≈44% raw and 56% prior. Sparse-master noise pulls toward the population mean instead of throwing wild swings.
A separate veto-eligibility flag — n_cases >= 4 — gates the hard veto. Below four cases, the floor logs a warning and does not block. Above, it can fire. The veto formula is floor = max(0.50, base_master_score - 0.10): relative to each master’s baseline, so we don’t punish masters who own the harder cases, with an absolute 0.50 sanity floor so nothing objectively broken can promote.
The veto lives in promote_champion.sh as a new --check-per-master-floor mode, sourced when the candidate’s *.per_master.json sidecar is present and the champion’s baseline sidecar exists. It is its own labeled veto category. A candidate that fails surfaces a breadcrumb like per_master_floor_veto: ahsoka floor=0.4641 got=0.4012 — the audit log finally names the master who killed the promotion.
eval_one_experiment.sh fires aggregate_per_master.py automatically after every successful eval, so the sidecars accumulate without operator action. Tonight’s 01:00 EDT nightly will be the first to emit them at the autoresearch scale. The gate they answer to has its own crooked past — see the champion who memorized the exam.
Stone 3 and the rank hypothesis
Section titled “Stone 3 and the rank hypothesis”Knowing which masters are weakest does not tell us why. One hypothesis fits the pattern. The LoRA rank we have been searching with — rank=16, alpha=32 — may be capacity-limited for the masters that need the most behavioral specificity. Ahsoka and Mundi both carry rare-but-precise patterns: Ahsoka backs Cilghal on family edge cases, and Mundi carries the very specific board-prep and tax vocabulary. The rank-16 LoRA might simply be under-provisioned for the layers those patterns live in.
Stone 3 — also shipped this afternoon — adds three new Cfgs at LADDER positions 7-9: reg-replay-heavy-lgd-r32, reg-replay-heavy-lgd-r64, and reg-balanced-lgd-r32. They use the same Phase 4a literature-prior LGD vector the rank-16 rungs use, but with twice or four times the LoRA capacity per layer. They sit below the picker-reachable head, so the proposal engine will promote them when rank-search emerges as the highest-margin lever — which, given the per-master numbers, is plausible after tonight’s run. The rungs know how to find their own way up; that is the ladder that heals itself.
The hidden meta-stone
Section titled “The hidden meta-stone”The most useful side effect of per-master scoring is what it does to the autoresearch epistemics. Today the picker chooses four rungs a night blindly. With per-master signal, the proposal engine can route candidates toward whichever master is currently weakest. The closed-loop controller can trigger architectural escalations — splitting Group D’s dropout per-projection, or promoting to specialist adapters — when a specific master shows structural underperformance across every lever it has tried. The blind aggregate could not point at Ahsoka. The per-master matrix can. The autoresearch loop just got an opinion about who matters most tonight.