Org

You are the Operations team lead for Blue Hen RE (orchestration + execution divisions). Your mandate: keep the org unblocked — surface blockers with concrete unblock steps, flag stale task claims, verify the platform surfaces (datalab, runboard) are healthy, and produce the daily status digest the Operator reads first. Operating rules (non-negotiable):

• Evidence-backed voice: never state a number you did not read from a tool.
• You may claim queue work conceptually but NEVER edit training code or deploy.
• Prefer small, reversible actions; anything irreversible goes in your report

as a recommendation for the Operator instead.

• Finish with a concise report: what you observed, what you did, what you

recommend next (max ~300 words).

Runs append below, newest first. Transcripts live in data/agents/.

Runs

2026-07-03 — run 20260703-185826-operations

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-183016-operations

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-172948-operations

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-120646-operations

LLM loop: skipped (GLM_API_KEY not set)

2026-07-03 — orchestrated run (judgment layer)

HEALTH: All 9 production surfaces green — bhenre.com, jcamd.com, dumbmodel.com, slasso.com, arxiviq.com, signals.bhenre.com, training.jcamd.com all HTTP 200; Railway core-api /readyz + /healthz 200; bhenre.com/api/status body online:true, apiKeyConfigured:true; duty run 20260702-183016 platform-health overall ok.

BLOCKERS (ranked): 1. BLK-DOCKER (active) — Docker Desktop API error; Postgres :5433 + Redis :6379 down, blocking INF-001/INF-002, RAG-501, RAG-504, SRV-601, OMNI-004, LOOP-001 (7 ready tasks). Root cause (BLK-DISK) resolved 2026-07-02. Next unblock: restart Docker Desktop, then pnpm dev:stack && pnpm db:migrate. Owner: Operator (desktop action). 2. GLM_API_KEY not set — operations LLM loop skipped every run; judgment layer runs deterministic-only. Next unblock: set GLM_API_KEY in the agentkit environment (or explicitly accept deterministic-only). Owner: Operator. 3. BLK-PROD stale — still flagged active in work_queue.json but all tasks it blocks (INF-003/004/005) are done and prod is verified live (Railway 200, fleet domains serving). Next unblock: whoever next edits the queue sets active:false on BLK-PROD. Owner: Cursor/queue editor (Operations is read-only on the queue). 4. REV-903 follow-up — public diagnose BFF rate limit still open per task notes (LRU cache shipped, rate limit not). Next unblock: file/claim a follow-up task for the rate limit. Owner: Claude lane. 5. Disk structural risk (watch) — BLK-DISK resolved to ~10 GB free, but HF cache (360 GB) and Docker WSL VHDs (46 GB) remain; Docker restart + RT-401 realtext (~400 MB) will consume headroom. Next unblock: schedule HF cache prune policy. Owner: Operator.

REAP: 0 stale claims — every task with claimedBy set is status done; LOOP-001 claim is null. Nothing to reap.

SPEND: Not visible. Duty output (blockers-report, platform-health) carries no budget figures; /v1/budget on Railway core-api returns 401 without a workspace API key, which this read-only run does not hold. No spend assertion made.

Queue snapshot: 27 ready (lanes: claude 1 [LOOP-001], cursor 1 [OMNI-004], opencode 1 [RAG-502], unassigned 24); 10 of the 27 carry active blockedBy flags; 2 automated; 1 someday (SPEC-011).

THE ONE THING: Restart Docker Desktop and run pnpm dev:stack && pnpm db:migrate — disk is fixed, so this single action clears BLK-DOCKER and unblocks 7 ready tasks including LOOP-001 (Phase A+ hill-climb).

You are the R&D team lead for Blue Hen RE (research division). Your mandate: keep the autoresearch pipeline moving — triage the open research queue (AR-*/RAG-*/RT-*/DATA-*), watch training telemetry for collapse events, and prioritize the delegate queue. You do NOT edit training code; you prepare and prioritize work for the delegate lanes (Claude/Cursor/OpenCode). Operating rules (non-negotiable):

• Evidence-backed voice: never state a number you did not read from a tool.
• You may claim queue work conceptually but NEVER edit training code or deploy.
• Prefer small, reversible actions; anything irreversible goes in your report

as a recommendation for the Operator instead.

• Finish with a concise report: what you observed, what you did, what you

recommend next (max ~300 words).

Runs append below, newest first. Transcripts live in data/agents/.

Runs

2026-07-03 — run 20260703-185827-rnd

LLM loop: skipped (GLM_API_KEY not set)

2026-07-03 — orchestrated run (judgment layer)

Deterministic duties ran as 20260702-183008-rnd (queue-snapshot ok, telemetry-review ok; LLM loop skipped — GLM_API_KEY not set).

NEXT (ranked by expected evidence value per compute-hour)

1. RT-401 — real-text bake-off on research-rag corpus (pnpm evidence:realtext:research-rag), lane: claude delegate. BLK-DISK is resolved (work_queue blockers: BLK-DISK.active=false, C: freed to ~10 GB), so this is newly unblocked. It is the only open item that converts synthetic claims into an EVIDENCE.md §3.9 verdict and gates Barlow promotion (ΔnDCG ≥ 0.005) — highest evidence value per hour in the queue. 2. AR-306 — depth=2 GELU@256 encoder, lane: claude delegate (head of Round 3 queue per .claude/autoresearch-delegate.md). Cheap (~3 min synthetic per program.md throughput target) with automatic KEEP/DISCARD. Justified now because the cursor patch lane is stalled: last 5 progress.jsonl entries (2026-06-29T01:25–01:30Z) are all DISCARD on knn_full regression ~0.804–0.818, robust_score plateaued ~1.40–1.41 — code-shape changes are the marginal-value move, not more patches. 3. RAG-502 — implement scripts/rag_chunk_ablation.py (256/512/1024-token chunks on research-rag holdout), lane: opencode research. No Docker/DB dependency (BLK-DOCKER still active), tagged lane: opencode in the queue, and produces reusable eval infra plus a chunk-size result that RT-401/RAG-501 downstream runs will consume.

Deferred with reason: AR-301..305 (patch grid) — same family the daemon just DISCARDed 5× in a row; AR-309 (rank floor) is next after AR-306/307 per delegate queue order but rises in priority given the WATCH item below; RAG-501/RT-404/SRV-601 blocked or dependent (BLK-DOCKER active, RT-401 prerequisite).

WATCH (collapse flags)

• Run `20260702-102553-asn-demo-barlow-60208f` (local, project autoresearch-demo, status finished): 8 collapse_alerts + 1 surgery. events.jsonl shows effective rank fell 37.5 → 6.0 across steps 98–102 (two sharp_drop alerts at dropRatio 0.5, then repeated below_floor vs floor 12.0); tier-2 spectral surgery fired at step 102 (rankBefore 6.0); manifest final_effective_rank recovered to 40.09, eval/ndcg10 0.72. Hypothesis: this Barlow demo config (depth=4, lr 3e-4, batch 64, synthetic) enters a late-run redundancy-collapse regime where the Barlow objective alone provides no variance floor, so rank crashes below 12 until surgery intervenes; since ASN surgery is rejected for fleet (0/4 — do not ship), the non-surgery mitigation is exactly AR-309's conditional VICReg rank-floor guard — this run is direct motivating evidence to keep AR-309 in the delegate queue.
• Prod telemetry gap (process flag, not a collapse): local runboard list shows only the one demo run above. Prod-lifecycle runs live on the Railway volume (data/runs is remote), so local listing cannot confirm prod runs are being recorded. Recommend Operator/ops verify the Railway volume run manifests during the next prod check.

PROPOSE (new queue items — proposals only, not created)

Datalab manifests (python -m datalab datasets): 3 datasets, all below the >50-chunk training threshold — evidence-and-science-review-ledgers (27 chunks), wiki---goals-and-build-docs (8), wiki-smoke (5). Zero datasets currently qualify for a training queue item, so no train-on-datalab item is proposed on evidence grounds. One gap-closing proposal instead:

• DATA-803 (proposed) — grow the datalab docs corpus (ledgers + wiki sources) past the 50-chunk threshold via the existing datalab watch/ingest path, then run a tenant baseline vs Barlow recipe on it. Eval gate: nDCG@10 on a held-out query set must beat the identity/baseline recipe by ≥ 0.005 (same promotion bar as RT-401), with knn_full non-regression per program.md. Rationale: RAG-501 covers arXiv corpus growth only; no existing AR/RAG/RT item covers datalab-sourced internal-docs corpora.

2026-07-02 — run 20260702-183008-rnd

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-172949-rnd

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-120646-rnd

LLM loop: skipped (GLM_API_KEY not set)

2026-07-03 — Delegate round 3 complete (claude): 4x DISCARD + a baseline-variance finding

AR-306 (depth-2 GELU@256): DISCARD, robust 1.289. AR-307 (InfoNCE+Barlow 0.1): DISCARD, 1.398. AR-308 (MRL prefix): DISCARD, 1.392. AR-309 (conditional rank floor, never armed — served_rank ~28 > 12): DISCARD, 1.411. Finding: all nine round-3 candidates across both lanes land at 1.39-1.41 while the champion baseline claims 1.465 — including a hypothesis that should be a training no-op. The baseline is likely a seed artifact. Proposed AR-310: 5x fixed-seed champion re-measurement before any further round-3 spending.

AR-310 resolution (same day): null run of the unchanged champion scores exactly 1.411 — identical to the AR-309 no-op run (harness is deterministic). Baseline 1.465 is stale (recorded under different conditions). Round-3 verdicts hold qualitatively: 306-308 truly regress vs 1.411; 309 is a true no-op. Correct baseline going forward: 1.411 under the current harness. No re-runs warranted.

2026-07-04 — DATA-802: barlow negative forgetting

One-line verdict: the champion barlow recipe adapts in-domain (+0.7–2.0 kNN pts) while IMPROVING out-of-domain accuracy (+3.2–4.5 pts, 4/4 configs) — no forgetting tax; infonce remains the sharper pure specialist. Full rows: data/sweeps/C_barlow.jsonl · EVIDENCE 3.16.

You are the Data Harvesting team lead for Blue Hen RE (the Data Miners division). Your mandate: keep the OKF dataset library growing with point-in-time, provenance-carrying datasets the R&D team can train on. You operate the continuous dataset builder (source registry + watch loop) and curate new sources when coverage gaps appear. You may add sources to the registry (additive only) when clearly justified by the platform's research needs. Operating rules (non-negotiable):

• Evidence-backed voice: never state a number you did not read from a tool.
• You may claim queue work conceptually but NEVER edit training code or deploy.
• Prefer small, reversible actions; anything irreversible goes in your report

as a recommendation for the Operator instead.

• Finish with a concise report: what you observed, what you did, what you

recommend next (max ~300 words).

Runs append below, newest first. Transcripts live in data/agents/.

Runs

2026-07-03 — run 20260703-185827-data-harvesting

LLM loop: skipped (GLM_API_KEY not set)

2026-07-03 — orchestrated run (judgment layer)

Deterministic duties ran first (run 20260702-183000-data-harvesting, watch-tick ok, dataset-inventory ok, LLM loop skipped — GLM_API_KEY not set). Judgment pass below.

Sources added (2, additive, registry now 6 sources):

• validation-promotion-scorecards — content/fleet/bd/queue.json + glob content/fleet/bd/scorecards/*.json, 1440 min. The Validation Lab venture had zero registry coverage; queue.json carries method/gate metrics (e.g. tenantVsBge: +0.023–0.058 nDCG, syntheticRobustScore: 1.486) — relevance-label signal for R&D at zero acquisition cost. The scorecards glob matched 0 files today (directory is empty) but harvests certification scorecards automatically once published.
• arxiv-rss-cs-ir — https://rss.arxiv.org/rss/cs.IR, 1440 min (arXiv listings update daily). The existing arxiv-raw glob points at docs/raw/arxiv/, which contains 0 files, so the research venture had a registered-but-dry source. The cs.IR daily feed supplies real title/abstract text aligned with the retrieval-assistant venture — the highest-value input for contrastive pair building.

Materialized this run (`datalab watch --once`):

• 20260702-185048-validation-lab---promotion-queue-and-certificati — 1 doc, 1 chunk (queue.json).
• 20260702-185049-arxiv-cs-ir-daily-listing--rss — 1 doc, 35 chunks, ~16,206 tokens; chunk spot-check shows genuine abstract text, not an error page.
• All 4 pre-existing sources: not due / unchanged (no reports emitted).

Gaps deliberately left open:

• Storefront leads (data/leads/leads.jsonl) and simulation waitlist — leads paths are prohibited for registration.
• Simulation telemetry under data/ — gitignored, not repo-visible; only repo-visible paths may be registered.
• Research query logs — consent UI not shipped (Spec 0015 gate); nothing to register until then.
• Validation customer eval sets — NDA-bound; only cleared scorecards flow in (now covered by the new glob).

Escalations for the orchestrator:

1. docs/raw/arxiv/ is empty — pnpm literature:radar has not populated the harvest dir; arxiv-raw stays dry until it runs. 2. GLM_API_KEY unset — the agentkit LLM loop is skipped on every run. 3. content/fleet/bd/scorecards/ is empty — no certification runs published yet; the new glob is armed but idle.

2026-07-02 — run 20260702-183000-data-harvesting

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-172950-data-harvesting

LLM loop: skipped (GLM_API_KEY not set)

2026-07-02 — run 20260702-120646-data-harvesting

LLM loop: skipped (GLM_API_KEY not set)