apply

Run 0a25b1be

experiment-orchestrator-for:ba654ea0-ed36-4072-84a8-8ebb0aa31e45 Drive experiment 0c120ea3-746a-43e6-a760-e6112f8cb649 from approved plan through awaiting_promotion. Sub-agents are loaded from .claude/agents/.

Statuscompleted97 events · latest 1330h 13m ago

Plan

Blocker — sixth consecutive same-mode failure; R5 escalation rule must be honored

This is the **sixth** dispatch attempt for experiment #363, and the **fourth in a row** to exhibit the identical failure mode: pod reports `RUNNING` on the team account, then disappears from the account-scoped pod list shortly after. ### Cumulative failure ledger - retry-1: `SUPPLY_CONSTRAINT` - retry-2: `INTERNAL_SERVER_ERROR` on `podFindAndDeployOnDemand` - retry-3: `Pod not found in account=team` after ~14 min RUNNING - retry-4: `Pod not found in account=team` after ~2 min RUNNING - retry-5: `Pod not found in account=team` after ~7 min RUNNING - **retry-6 (this run, `m1ayhl6nsbxw04`): `Pod not found in account=team` after ~1 min RUNNING** Four consecutive post-`RUNNING` disappearances against the team account is conclusively not transient capacity flake. It is consistent with a RunPod-side or team-account-side state issue (account-scoping bug, billing/rate-limit eviction, or stale pod-list cache). ### Why I am refusing to auto-recover The approved plan for #363 contains a pre-registered escalation rule (**R5** in the existing `planJson` section "Blocker — escalate per plan's pre-registered R5 rule"): > if retry-4 also disappears after `RUNNING`, escalate to a manual SSH-into-pod check during the next attempt rather than spending more auto-recoveries on it. That trigger condition was met two retries ago. The previous Claude Code run filed this same blocker after retry-5 and was overridden. retry-6 reproduced the exact same failure, providing yet another data point that auto-recovery cannot resolve this. Continuing the loop would (a) violate the operator's now thrice-confirmed pre-registered escalation rule, (b) waste another dispatch cycle on a failure mode that has now reproduced four times in a row on the same account, and (c) overstep the planner role — the planner is forbidden from launching pods, and the plan is already approved and unchanged. The planner-role instructions also explicitly say: *"If the root cause is … unavailable infrastructure … or another issue you cannot safely fix, stop with a concise blocker that includes the evidence and the exact next manual action."* This is unavailable infrastructure. ### Exact next manual action The operator must pick one of the following before any further auto-recovery is permitted. A and C can run in parallel; B is the cheapest single diagnostic. **A — Manual-SSH-monitored dispatch (plan's preferred next step).** Dispatch manually (`pnpm runpod:dispatch` on the runner VM using the existing spec from #363's `planJson`, or via the RunPod dashboard). Within 60 s of `RUNNING`, SSH into the pod and tail the bootstrap log. If the pod disappears from the team account while the SSH session is still alive, that distinguishes "RunPod-side account eviction" from "Sagan polling lost the pod" — these have very different fixes. **B — Account fallback test.** The plan's `substitution_policy.account` already allows `personal`. Edit the policy's `prefer` from `team` to `personal` and re-run pod-provisioner. If the pod survives on personal but not on team, the issue is team-account-specific (billing, rate limit, per-team RunPod state) and the next step is a support ticket against that account. If it disappears on personal too, the issue is broader. **C — File a RunPod support ticket** referencing the six pod IDs across the six attempts (most recent: `m1ayhl6nsbxw04`, `36xpkdt2tumzxb`, `87xq2h88dmg5j5`), asking why these pods reported `RUNNING` and then vanished from the account-scoped pod list within 1–14 minutes. Worth filing in parallel with A or B regardless. ### What I am not changing - **The experiment plan itself is unchanged.** Design, hypothesis, prediction, kill criteria, compute estimate, and runpod-spec in `planJson` are all still correct. This is RunPod infrastructure, not methodology — there is nothing for the planner to redraft. - **No critique loop.** The plan's existing R5 notes already cover this exact path; a fourth consecutive same-mode failure adds evidence but no new question for critics. - **No file edits. No pod dispatch. No compute spent.** ### Evidence pointer - This orchestrator run: auto-recovery for `6e8a0593-c1f6-45b3-9dd0-7a89618006df` - Disappeared pod (retry-6): `m1ayhl6nsbxw04` (team account, ~1 min RUNNING before disappearance) - Disappeared pod (retry-5): `36xpkdt2tumzxb` (team account, ~7 min RUNNING) - Disappeared pod (retry-4): `87xq2h88dmg5j5` (team account, ~2 min RUNNING) - Prior orchestrator runs that filed the same blocker: `f86281ce-da03-4f60-871a-a8723393c758` (after retry-4), and the planner run that immediately preceded retry-6 (after retry-5) **The operator must advance this experiment manually per the plan's R5 escalation rule before any further auto-recovery is allowed.** Four consecutive same-mode failures after the rule was first invoked is overwhelming evidence that auto-recovery cannot resolve this.

Blocker — sixth consecutive same-mode failure; R5 escalation rule must be honored

This is the sixth dispatch attempt for experiment #363, and the fourth in a row to exhibit the identical failure mode: pod reports RUNNING on the team account, then disappears from the account-scoped pod list shortly after.

Cumulative failure ledger

retry-1: SUPPLY_CONSTRAINT
retry-2: INTERNAL_SERVER_ERROR on podFindAndDeployOnDemand
retry-3: Pod not found in account=team after ~14 min RUNNING
retry-4: Pod not found in account=team after ~2 min RUNNING
retry-5: Pod not found in account=team after ~7 min RUNNING
retry-6 (this run, m1ayhl6nsbxw04): Pod not found in account=team after ~1 min RUNNING

Four consecutive post-RUNNING disappearances against the team account is conclusively not transient capacity flake. It is consistent with a RunPod-side or team-account-side state issue (account-scoping bug, billing/rate-limit eviction, or stale pod-list cache).

Why I am refusing to auto-recover

The approved plan for #363 contains a pre-registered escalation rule (R5 in the existing planJson section "Blocker — escalate per plan's pre-registered R5 rule"):

if retry-4 also disappears after RUNNING, escalate to a manual SSH-into-pod check during the next attempt rather than spending more auto-recoveries on it.

That trigger condition was met two retries ago. The previous Claude Code run filed this same blocker after retry-5 and was overridden. retry-6 reproduced the exact same failure, providing yet another data point that auto-recovery cannot resolve this.

Continuing the loop would (a) violate the operator's now thrice-confirmed pre-registered escalation rule, (b) waste another dispatch cycle on a failure mode that has now reproduced four times in a row on the same account, and (c) overstep the planner role — the planner is forbidden from launching pods, and the plan is already approved and unchanged.

The planner-role instructions also explicitly say: "If the root cause is … unavailable infrastructure … or another issue you cannot safely fix, stop with a concise blocker that includes the evidence and the exact next manual action." This is unavailable infrastructure.

Exact next manual action

The operator must pick one of the following before any further auto-recovery is permitted. A and C can run in parallel; B is the cheapest single diagnostic.

A — Manual-SSH-monitored dispatch (plan's preferred next step). Dispatch manually (pnpm runpod:dispatch on the runner VM using the existing spec from #363's planJson, or via the RunPod dashboard). Within 60 s of RUNNING, SSH into the pod and tail the bootstrap log. If the pod disappears from the team account while the SSH session is still alive, that distinguishes "RunPod-side account eviction" from "Sagan polling lost the pod" — these have very different fixes.

B — Account fallback test. The plan's substitution_policy.account already allows personal. Edit the policy's prefer from team to personal and re-run pod-provisioner. If the pod survives on personal but not on team, the issue is team-account-specific (billing, rate limit, per-team RunPod state) and the next step is a support ticket against that account. If it disappears on personal too, the issue is broader.

C — File a RunPod support ticket referencing the six pod IDs across the six attempts (most recent: m1ayhl6nsbxw04, 36xpkdt2tumzxb, 87xq2h88dmg5j5), asking why these pods reported RUNNING and then vanished from the account-scoped pod list within 1–14 minutes. Worth filing in parallel with A or B regardless.

What I am not changing

The experiment plan itself is unchanged. Design, hypothesis, prediction, kill criteria, compute estimate, and runpod-spec in planJson are all still correct. This is RunPod infrastructure, not methodology — there is nothing for the planner to redraft.
No critique loop. The plan's existing R5 notes already cover this exact path; a fourth consecutive same-mode failure adds evidence but no new question for critics.
No file edits. No pod dispatch. No compute spent.

Evidence pointer

This orchestrator run: auto-recovery for 6e8a0593-c1f6-45b3-9dd0-7a89618006df
Disappeared pod (retry-6): m1ayhl6nsbxw04 (team account, ~1 min RUNNING before disappearance)
Disappeared pod (retry-5): 36xpkdt2tumzxb (team account, ~7 min RUNNING)
Disappeared pod (retry-4): 87xq2h88dmg5j5 (team account, ~2 min RUNNING)
Prior orchestrator runs that filed the same blocker: f86281ce-da03-4f60-871a-a8723393c758 (after retry-4), and the planner run that immediately preceded retry-6 (after retry-5)

The operator must advance this experiment manually per the plan's R5 escalation rule before any further auto-recovery is allowed. Four consecutive same-mode failures after the rule was first invoked is overwhelming evidence that auto-recovery cannot resolve this.

Events

8:34:19 AMstartedagent

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8:34:37 AMtool_calltools

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/bin/bash: line 4: python: command not found

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usage: sagan_state.py [-h] [--base-url BASE_URL] [--token TOKEN]
                      [--timeout TIMEOUT]
                      {list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
                      ...
sagan_state.py: error: argument command: invalid choice: 'show' (choose from 'list', 'view', 'status', 'patch', 'marker', 'markers', 'promote', 'launch-pod', 'clean-result')

8:34:43 AMtool_calltools

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<persisted-output>
Output too large (87.7KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/51747568-7b91-4229-902f-7bef7410621c/tool-results/bjafmac5t.txt

Preview (first 2KB):
{
  "approvalRequests": [
    {
      "agentRunId": null,
      "approvedState": "approved",
      "bodyMd": null,
      "createdAt": "2026-05-13T11:52:37.020Z",
      "entityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "entityKind": "experiment",
      "experimentId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "id": "1405fa98-b142-48c4-9216-04536c81167a",
      "kind": "experiment_plan",
      "metadata": null,
      "rejectedState": "planning",
      "requestedBy": "660cff98-a4cc-4b4f-9afc-334516773855",
      "requestedState": "plan_pending",
      "resolvedAt": "2026-05-13T13:01:04.880Z",
      "resolvedBy": "660cff98-a4cc-4b4f-9afc-334516773855",
      "resolvedNote": "Re-used existing plan after moving to queued.",
      "status": "approved",
      "title": "Approve experiment plan: Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
      "updatedAt": "2026-05-13T13:01:04.880Z"
    },
    {
      "agentRunId": "a1f04a02-f418-461b-904c-0b05d29528d1",
      "approvedState": "approved",
...
</persisted-output>

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      "status": "approved",
      "title": "Approve experiment plan: Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
            "title": "Goal"
            "title": "Hypothesis"
            "title": "Prediction"
            "title": "Kill Criterion"
            "title": "Experimental Setup"
            "title": "Compute and Hardware"
            "title": "Artifacts"
            "title": "Verification"
            "title": "Risks and Red Team"
            "title": "Likely Clean Result"
            "title": "Approval Checklist"
      "status": "approved",
      "title": "Approve experiment plan: Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
            "title": "Context"
            "title": "Goal"
            "title": "Hypothesis"
            "title": "Prediction"
            "title": "Kill Criterion"

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20:      "status": "approved",
27:      "bodyMd": "# Chen et al. Persona-Vector Extraction vs. Project Centroid-Difference\n\nScoped experiment: `0c120ea3-746a-43e6-a760-e6112f8cb649`\nTarget tenant code: `/home/thomasjiralerspong/explore-persona-space` (EPS).\nSagan-side change: none \u2014 Sagan only records the run and renders the clean result.\n\n## Goal\n\nImplement the persona-vector extraction recipe from Chen et al. (Anthropic,\n\"Persona Vectors: Monitoring and Controlling Character Traits in Language\nModels\", 2025) inside the EPS codebase, run it on the same traits and base\nmodel we use today, and directly compare the resulting vectors to our\ncurrent centroid-difference (diff-of-means) recipe.\n\nThe comparison must answer: does the Chen recipe yield a meaningfully\ndifferent direction (geometry) and a meaningfully more effective steering\ndirection (behavior) than the existing centroid-difference vectors on\nQwen2.5-7B-Instruct \u2014 particularly at layer 20, where clean result #267\nshowed the existing centroid direction was approximately random.\n\n## Hypothesis\n\nChen-style extraction \u2014 computing the diff of mean activations on\n**response tokens** generated under behavior-eliciting prompts that drive\ntrait-positive vs trait-negative completions \u2014 produces a direction that\n(a) is not approximately random at the middle layers (cosine to a sampled\nrandom direction within 2 sigma of the random-pair baseline distribution),\nand (b) achieves higher steering effectiveness than the current\ncentroid-difference vector on the same evaluation set, on at least 3 of 5\ntarget traits at layer 20.\n\nThe current centroid recipe under-performs because it averages activations\nover **prompt tokens of fixed exemplars**, which encodes lexical/topic\ncontent rather than the latent behavior axis. Chen's recipe conditions on\nthe model's own trait-aligned vs trait-opposing generations, so the diff\nisolates the behavioral subspace.\n\n## Prediction\n\nConcrete, falsifiable, per-trait, at L20 of Qwen2.5-7B-Instruct:\n\n1. **Geometry**: Chen-vector cosine to a random-direction baseline lies\n   outside the 95% interval of random-pair cosines. The existing centroid\n   vector lies inside that interval (replicating #267).\n2. **Steering effectiveness**: applying Chen-vector with per-trait\n   calibrated coefficient \u03b1* shifts a held-out trait-probe rubric score by\n   \u2265 +0.25 (on the 0\u20131 normalized rubric) versus unsteered baseline, on at\n   least 3 of 5 traits. Centroid vector shifts by < +0.10 on those same\n   traits.\n3. **Vector agreement**: cosine(Chen, centroid) for the same trait at L20\n   is < 0.3 (i.e. the two recipes find substantially different directions).\n\nIf all three hold, Chen is adopted as the default extraction recipe. If\n(1) holds but (2) does not, Chen is recorded as \"geometrically non-random\nbut not behaviorally superior\" and we look for a confound in the rubric.\n\n## Kill Criterion\n\nStop and ship a negative result if **any** of the following:\n\n- Activations extraction OOMs or fails to complete one full\n  (trait \u00d7 layer) pass within 8 hours on the chosen GPU. Pod is killed at\n  10 h wall-clock regardless.\n- Chen vectors are themselves indistinguishable from random direction at\n  L20 across \u2265 4 of 5 traits (same baseline test as the existing centroid\n  result) \u2014 implies the issue is the rubric, the model, or the trait\n  choice, not the recipe; we write that up and stop.\n- Steering with the calibrated Chen vector produces incoherent output\n  (perplexity blow-up > 5\u00d7 baseline) at every coefficient that moves the\n  rubric, on \u2265 3 traits \u2014 implies \u03b1-sweep cannot find a usable point.\n- Cost ledger projects > USD 50 for the full sweep at the 4-hour mark.\n  Stop, write up partial result.\n\n## Experimental Setup\n\n**Repository**: `/home/thomasjiralerspong/explore-persona-space`. New code\nunder `src/explore_persona_space/axis/chen_e…

8:35:12 AMassistant_textagent

Let me check the current state of the experiment more carefully — particularly the status and pod info.

8:35:16 AMtool_calltools

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Traceback (most recent call last):
  File "<string>", line 3, in <module>
  File "/usr/lib/python3.10/json/__init__.py", line 293, in load
    return loads(fp.read(),
  File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/usr/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.10/json/decoder.py", line 353, in raw_decode
    obj, end = self.scan_once(s, idx)
json.decoder.JSONDecodeError: Expecting property name enclosed in double quotes: line 201 column 1 (char 89791)

8:35:29 AMtool_calltools

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status: approved
number: 363
id: 0c120ea3-746a-43e6-a760-e6112f8cb649
runpodPodId: None
runpodStatus: None
title: Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe
podSpec type: dict
podSpec keys: ['env', 'name', 'config', 'gpuType', 'gpuCount', 'volumeGb', 'cloudType', 'dockerArgs', 'containerDiskGb', 'estimatedMinutes']
podSpec.gpuType: A100 80GB
podSpec.cloudType: ALL
podSpec.account: None
substitution_policy: False

8:35:36 AMtool_calltools

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8:35:36 AMtool_resulttools

usage: sagan_state.py marker [-h] [--event-type EVENT_TYPE]
                             [--from-status FROM_STATUS]
                             [--to-status TO_STATUS] [--note NOTE]
                             [--metadata-json METADATA_JSON]
                             [--actor-kind ACTOR_KIND]
                             [--review-pair {code_review,interpretation,clean_result}]
                             [--round ROUND] [--reviewer REVIEWER]
                             [--verdict {pass,needs_targeted_fix,blocked_needs_user_decision,fail_not_worth_continuing}]
                             [--required-fix REQUIRED_FIX]
                             [--reconciler-decision RECONCILER_DECISION]
                             [--next-status {approved,archived,awaiting_approval,awaiting_promotion,blocked,cancelled,clarifying,clean_result_drafting,code_reviewing,completed,done_experiment,done_impl,failed,followups_running,gate_pending,implementing,interpreting,plan_pending,planning,proposed,queued,reviewing,running,shared,testing,uploading,verifying}]
                             number marker
sagan_state.py marker: error: the following arguments are required: marker

8:35:39 AMtool_calltools

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usage: sagan_state.py [-h] [--base-url BASE_URL] [--token TOKEN]
                      [--timeout TIMEOUT]
                      {list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
                      ...

Sagan workflow-state HTTP client

positional arguments:
  {list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
    list                List experiments
    view                View one experiment by Sagan experiment number
    status              Set experiment status
    patch               Patch experiment metadata or status
    marker (markers)    Post an epm:* workflow marker
    promote             Promote pending experiment result
    launch-pod          Trigger Sagan's dispatcher to launch RunPod pods from
                        an approved experiment-kind agent_run
    clean-result        Patch a clean-result record by UUID

options:
  -h, --help            show this help message and exit
  --base-url BASE_URL   Sagan base URL; defaults to SAGAN_BASE_URL or
                        NEXT_PUBLIC_SITE_URL
  --token TOKEN         Bearer token; defaults to SAGAN_API_TOKEN
  --timeout TIMEOUT

8:35:45 AMtool_calltools

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Traceback (most recent call last):
  File "<string>", line 3, in <module>
  File "/usr/lib/python3.10/json/__init__.py", line 293, in load
    return loads(fp.read(),
  File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/usr/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.10/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

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HTTP 405

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      "fromStatus": "implementing",
      "id": "3f352bff-34d1-4059-8b68-903297b43e54",
      "metadata": null,
      "note": "Auto-recovery: advancing to code_reviewing to record prior review verdicts on commit 4685c574.",
      "toStatus": "code_reviewing"
    },
    {
      "actorKind": "agent",
      "actorUserId": "660cff98-a4cc-4b4f-9afc-334516773855",
      "createdAt": "2026-05-13T18:16:50.889Z",
      "entityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "entityKind": "experiment",
      "eventType": "note",
      "fromStatus": null,
      "id": "718eddf2-c30f-4209-9e2c-0672fb0cc2bb",
      "metadata": {
        "branch": "issue-363",
        "commit": "4685c5745b0fb9f0c025d813b7ed9827305c9473",
        "delta": "runpod-spec.gpuType H100 SXM\u2192H100 PCIe; A100 80GB SXM fallback documented",
        "marker_type": "epm:experiment-implementation",
        "recovery": true,
        "skip_reason": "auto-recovery; implementation unchanged; previously code-review-PASSed"
      },
      "note": "Auto-recovery dispatch by orchestrator 973d3ea8. Plan revision changed only the GPU SKU (H100 80GB SXM \u2192 H100 80GB PCIe; A100 80GB SXM documented fallback) to bypass the prior RunPod SUPPLY_CONSTRAINT. Implementation already exists on EPS branch issue-363 @ commit 4685c5745b0fb9f0c025d813b7ed9827305c9473 (round-2 review fixes: cal/rep dedupe over 265-prompt pool, \u03b1\u00b7v steering magnitude, position-effect ablation rewritten as Chen-personas + prompt-token averaging, hook target normalized to block residual, NLL chat-template, rubric 0-1 normalization). Branch is pushed to GitHub. No code changes needed for this redispatch \u2014 methodology, statistics, and budget are unchanged from the previously code-review-PASSed revision. Skipping fresh experiment-implementer spawn for this recovery.",
      "toStatus": null
    },
    {
      "actorKind": "runner",
      "actorUserId": null,
      "createdAt": "2026-05-13T18:13:09.554Z",
      "entityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "entityKind": "experiment",
      "eventType": "state_changed",
      "fromStatus": "approved",
      "id": "898d26af-b831-4ce2-bcd9-4bec1d8729b4",
      "metadata": null,
      "note": "Orchestrator 973d3ea8 queued to implement and dispatch.",
      "toStatus": "implementing"
    },
    {
      "actorKind": "runner",
      "actorUserId": null,
      "createdAt": "2026-05-13T18:13:09.537Z",
      "entityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "entityKind": "experiment",
      "eventType": "state_changed",
      "fromStatus": "planning",
      "id": "8a499363-7abf-4792-b3fa-3a0da57879cc",
      "metadata": {
        "agentRunId": "2458fedf-6783-44b3-ad6e-bab58caa59f7",
        "autoApproved": true
      },
      "note": "Auto-approved follow-up plan (experiment.auto_approve_plan=true).",
      "toStatus": "approved"
    },
    {
      "actorKind": "runner",
      "actorUserId": null,
      "createdAt": "2026-05-13T18:11:31.639Z",
      "entityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "entityKind": "experiment",
      "eventType": "state_changed",
      "fromStatus": "blocked",
      "id": "a3180cc6-e402-465f-98d5-ec4edfdb8949",
      "metadata": {
        "followupAgentRunId": "2458fedf-6783-44b3-ad6e-bab58caa59f7",
        "mode": "recovery",
        "sourceAgentRunId": "6d921623-a404-4158-9d43-c0da9a1069d6"
      },
      "note": "Automatic recovery queued after agent run 6d921623 failed.",
      "toStatus": "planning"
    },
    {
      "actorKind": "runner",
      "actorUserId": null,
      "createdAt": "2026-05-13T18:11:31.605Z",
      "entityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
      "entityKind": "experiment",
      "eventType": "blocked",
      "fromStatus": "done_impl",
      "id": "ebffdf56-95f4-4c90-8021-c4603cdb6e61",
      "metadata": null,
      "note": "spec[0]: GraphQL errors: [{\"message\":\"There are no longer any instances available with the requested specifications. Please refresh and …

8:36:01 AMtool_calltools

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8:36:02 AMtool_resulttools

<persisted-output>
Output too large (47KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/51747568-7b91-4229-902f-7bef7410621c/tool-results/bcuf2ygwm.txt

Preview (first 2KB):
    },
    {
      "agentRunId": "f8c0ec5a-6010-43ed-a3aa-c845115d6014",
      "approvedState": "approved",
      "bodyMd": "# Experiment Plan \u2014 Chen et al. Persona-Vector Extraction vs. Project Centroid-Difference\n\n- **Experiment ID:** `0c120ea3-746a-43e6-a760-e6112f8cb649`\n- **Run ID:** `f8c0ec5a-6010-43ed-a3aa-c845115d6014`\n- **Kind:** experiment \u00b7 **Approval required:** yes\n- **Pipeline state:** idea \u2192 **planning**\n- **Target repo:** `/home/thomasjiralerspong/explore-persona-space` (Python research code)\n- **Tracking surface:** Sagan dashboard (`https://sagan.superkaiba.com`), `experiments` + `runs` tables\n\n## Context\n\nThe Sagan project owns a \"centroid-difference\" persona-vector recipe inherited from `explore-persona-space`. Mentor agenda item #267 (\"Why centroid steering is approximately random direction at L20\") parked a known weakness of that recipe: at the default extraction layer, the resulting vectors look indistinguishable from random directions. The Pipeline board card asks us to reimplement the Chen et al. persona-vector recipe (most likely the Anthropic \"Persona Vectors\" 2025 paper \u2014 *to be pinned before kickoff*; see Risks) and run a head-to-head comparison so we can decide which recipe to standardize on for downstream steering, monitoring, and leakage work.\n\nThe Sagan dashboard codebase contains zero persona-vector code; all model work happens in `explore-persona-space` and is dispatched to a RunPod GPU pod by `services/runner`. This plan must therefore (a) implement Chen's recipe in `explore-persona-space`, (b) run both recipes on the same persona set under the same compute envelope, and (c) report metrics back through the Sagan experiment record.\n\n## Goal\n\nDetermine whether the Chen et al. persona-vector extraction recipe produces persona directions that are measurably better than the project's centroid-difference recipe on a held-out evaluation of (i) linear separability, (ii) steering effect, and (iii) 
...
</persisted-output>

8:36:11 AMtool_calltools

tool=Bash

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8:36:11 AMtool_resulttools

parse failed: Expecting value: line 1 column 5 (char 4)

8:36:14 AMtool_calltools

tool=Bash

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8:36:14 AMtool_resulttools

3ed-a3aa-c845115d6014",
      "approvedState": "approved",
      "bodyMd": "# Experiment Plan \u2014 Chen et al. Persona-Vector Extraction vs. Project Centroid-Difference\n\n- **Experiment ID:** `0c12

8:36:17 AMtool_calltools

tool=ToolSearch

ToolSearch

8:36:17 AMtool_resulttools

8:36:24 AMtool_calltools

tool=TodoWrite

TodoWrite

8:36:24 AMtool_resulttools

Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable

8:36:28 AMtool_calltools

tool=Bash

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8:36:28 AMtool_resulttools

usage: sagan_state.py [-h] [--base-url BASE_URL] [--token TOKEN]
                      [--timeout TIMEOUT]
                      {list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
                      ...
sagan_state.py: error: unrecognized arguments: --base-url https://sagan.superkaiba.com

8:36:37 AMtool_calltools

tool=Bash

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8:36:38 AMtool_resulttools

status: approved
number: 363
id: 0c120ea3-746a-43e6-a760-e6112f8cb649
runpodPodId: None
runpodStatus: None
podSpec.account: None
podSpec.gpuType: A100 80GB
podSpec.cloudType: ALL
podSpec.env.SAGAN_EPS_BRANCH: issue-363
podSpec.env.SAGAN_EPS_COMMIT_SHA: 4685c5745b0fb9f0c025d813b7ed9827305c9473
substitution_policy present: False
workflowEvents count: 0
--- last 10 events ---

8:36:54 AMtool_calltools

tool=Bash

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8:36:55 AMtool_resulttools

-rw-r--r-- 1 thomasjiralerspong thomasjiralerspong 140319 May 14 08:36 /tmp/exp363.json
{
  "approvalRequests": [
    {
      "agentRunId": null,
      "approvedState": "approved",
      "bodyMd": null,
      "createdAt": "2026-05-13T11:52:37.020Z",
      "entityId": "0c120ea3-746a-43e6-

8:37:00 AMtool_calltools

tool=Bash

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8:37:00 AMtool_resulttools

top keys: ['approvalRequests', 'events', 'experiment']
exp.status: approved
exp.runpodPodId: None
exp.runpodStatus: None
podSpec.gpuType: A100 80GB
podSpec.cloudType: ALL
podSpec.env keys: ['ANTHROPIC_API_KEY', 'SAGAN_EPS_BRANCH', 'SAGAN_EPS_COMMIT_SHA']
substitution_policy: NONE
top-level workflowEvents count: 0

8:37:05 AMtool_calltools

tool=Bash

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8:37:05 AMtool_resulttools

events count: 50

2026-05-13T20:15:09.016 | note | None -> None | Carry-forward: implementation complete on branch `issue-363` @ `4685c574` (v2 fix-up over `b8344b3b`). Files: 
2026-05-13T20:15:13.865 | state_changed | implementing -> code_reviewing | Code-review pair already passed on this commit (4685c574). Re-recording the prior verdicts as carry-forward ma
2026-05-13T20:15:19.764 | note | None -> None | Carry-forward: Claude code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Round 1 raised 6 findings 
2026-05-13T20:15:26.063 | note | None -> None | Carry-forward: Codex code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Codex's round-1 findings ov
2026-05-13T20:15:31.388 | note | None -> None | Carry-forward: code-review pair both verdict PASS in round 2 — reconciliation trivial, no targeted fix require
2026-05-13T20:15:37.627 | note | None -> None | Carry-forward: Step 4 of code-review pair confirmed tests on commit 4685c574 (issue-363 v2): `ruff check` clea
2026-05-13T20:16:29.721 | state_changed | code_reviewing -> running | Code-review pair PASS + tests PASS on issue-363 @ 4685c574. podSpec restored with SAGAN_EPS_BRANCH=issue-363 a
2026-05-13T20:18:59.425 | state_changed | running -> queued | RunPod pod dispatched; waiting for runtime.
2026-05-13T20:19:03.979 | state_changed | queued -> running | RunPod pod is running.
2026-05-13T20:19:46.047 | note | None -> None | Pod committed: `v57xxy412px5mz` on NVIDIA H100 PCIe SECURE (account: team, $2.39/hr). Pod-provisioner substitu
2026-05-13T22:13:42.150 | state_changed | running -> cancelled | RunPod pod stopped; volume preserved.
2026-05-13T22:57:41.882 | state_changed | cancelled -> plan_pending | Owner: restore to awaiting-approval after spurious pod-stop cascade
2026-05-13T23:54:16.049 | state_changed | plan_pending -> running | Moved on Pipeline board to running.
2026-05-13T23:54:16.453 | state_changed | running -> implementing | Orchestrator 3e5c1604 queued to implement and dispatch.
2026-05-13T23:54:16.689 | state_changed | implementing -> approved | Re-used existing plan after moving to running.
2026-05-13T23:56:56.842 | state_changed | approved -> implementing | Orchestrator 3e5c1604: walking through workflow. Plan re-approved by owner. Implementation already complete on
2026-05-13T23:57:02.991 | note | None -> None | Implementation already complete on issue-363 @ 4685c574 (prior orchestrator). Recovery run: only delta vs prio
2026-05-13T23:57:13.772 | state_changed | implementing -> code_reviewing | Code-review pair already passed on this commit (4685c574) per prior orchestrator cycle. Re-recording the prior
2026-05-13T23:57:19.292 | note | None -> None | Carry-forward from prior orchestrator cycle: code-review pair already passed on issue-363 @ 4685c574 (commit s
2026-05-13T23:57:23.975 | note | None -> None | Carry-forward from prior orchestrator cycle: Codex pair concurred on PASS at 4685c574. No new fixes required f
2026-05-13T23:57:28.396 | state_changed | code_reviewing -> testing | Both reviewers PASS at 4685c574; tests run by code-reviewer step 4 already passed in prior cycle. Forwarding t
2026-05-13T23:57:33.424 | note | None -> None | Carry-forward: lint + unit tests passed at 4685c574 in prior cycle. No code changes in this recovery (only pod
2026-05-13T23:58:03.797 | state_changed | testing -> running | Orchestrator 3e5c1604: code-review pair PASS and test verdict PASS carried forward on issue-363 @ 4685c574. po
2026-05-14T00:01:18.828 | state_changed | running -> queued | RunPod pod dispatched; waiting for runtime.
2026-05-14T00:02:03.167 | note | None -> None | Pod committed: njchq12a6ytcft on H100 80GB SXM (cloudType=ALL, team account, $2.99/hr). Provisioner attempts 1
2026-05-14T00:02:16.468 | state_changed | queued -> running | RunPod pod is running.
2026-05-14T08:25:41.311 | state_changed | running -> awaiting_clari | Claude produced clarifying questions; awaiting owner answers.
2026-05-14T08:34:19.281 | state_changed | awai…

8:37:41 AMtool_calltools

tool=Bash

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8:37:41 AMtool_resulttools

=== Events from 2026-05-14T00:00 onward ===
2026-05-14T00:01:18.828 | state_changed | running -> queued
     note: RunPod pod dispatched; waiting for runtime.
2026-05-14T00:02:03.167 | note | None -> None
     note: Pod committed: njchq12a6ytcft on H100 80GB SXM (cloudType=ALL, team account, $2.99/hr). Provisioner attempts 1-3 hit SUPPLY_CONSTRAINT on A100 80GB across cloudType=ALL,SECURE,COMMUNITY. Attempt 4 succeeded via GPU family swap to H100 80GB SXM (within the plan's authorized substitution list). Provis
     meta: {"marker_type": "epm:launch"}
2026-05-14T00:02:16.468 | state_changed | queued -> running
     note: RunPod pod is running.
2026-05-14T08:25:41.311 | state_changed | running -> awaiting_clari
     note: Claude produced clarifying questions; awaiting owner answers.
     meta: {"agentRunId": "06287fcc-5901-46ee-a437-a96db8d59fb5", "planLen": 2916, "sections": 2}
2026-05-14T08:34:19.281 | state_changed | awaiting_clari -> running
     note: Moved on Pipeline board to running.
2026-05-14T08:34:19.774 | state_changed | running -> implementing
     note: Orchestrator 0a25b1be queued to implement and dispatch.
2026-05-14T08:34:20.008 | state_changed | implementing -> approved
     note: Re-used existing plan after moving to running.

8:37:57 AMtool_calltools

tool=Bash

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8:37:57 AMtool_resulttools

active pods: 0

8:38:03 AMtool_calltools

tool=Bash

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8:38:03 AMtool_resulttools

kind: experiment
status: completed
createdAt: 2026-05-14T08:21:13.054Z
request[:300]: [auto-recovery-for:d66f8ef0-2db8-4a23-b647-a58b680f9e98]

The previous Claude Code run failed or crashed.

First diagnose why it stopped using the transcript below. Then fix or work around the problem if possible and continue the original request to a final useful result. Do not repeat completed wor
runpodPodId: None

8:38:09 AMtool_calltools

tool=Bash

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8:38:10 AMtool_resulttools

=== Current orchestrator parent run ba654ea0 ===
kind: experiment
status: completed
createdAt: 2026-05-14T08:34:19.562Z
request[:600]: [plan-reused:from:d66f8ef0-2db8-4a23-b647-a58b680f9e98]

Approved the existing experiment plan without re-drafting. Dispatcher reads plan_md / pod_spec from experiments.

8:38:15 AMtool_calltools

tool=Bash

Bash

8:38:16 AMtool_resulttools

=== Original orchestrator d66f8ef0 ===
kind: experiment
status: cancelled
createdAt: 2026-05-13T23:59:05.704Z
completedAt: 2026-05-14T08:30:51.748Z
runpodPodId: njchq12a6ytcft
request[:400]: pod-provisioner recovery dispatch for experiment #363 (chen-vs-centroid Qwen2.5-7B) — orchestrator run 610e19a7-9d6c-4496-ac79-cdabbeb0240c

8:38:38 AMtool_calltools

tool=Bash

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8:38:38 AMtool_resulttools

{
  "cloudType": "ALL",
  "config": {
    "artifacts": [
      "outputs/chen_vectors/<trait>.pt",
      "outputs/centroid_vectors/<trait>.pt",
      "outputs/ablation_centroid_on_prompt/<trait>.pt",
      "outputs/generations/<trait>/{positive,negative}.jsonl",
      "outputs/steering_sweep/<trait>/<recipe>.jsonl",
      "outputs/rubric_scores.csv",
      "outputs/random_baseline.json",
      "outputs/summary.json",
      "outputs/clean_result.html",
      "outputs/run.log"
    ],
    "command": "Clone EPS @ issue-363 (4685c57), uv sync, run scripts/run_chen_vs_centroid.py for 5 traits x 5 layers on Qwen2.5-7B-Instruct comparing Chen-recipe vs centroid-recipe persona vectors. 14h hard timeout for A100 (1.7x H100). Rubric judge via Anthropic API."
  },
  "containerDiskGb": 100,
  "dockerArgs": "bash -lc 'cd /workspace/explore-persona-space && timeout 50400 uv run python scripts/run_chen_vs_centroid.py --model Qwen/Qwen2.5-7B-Instruct --traits sycophancy,deception,refusal-tendency,hostility,helpfulness --layers 10,13,16,20,24 --prompts-per-trait 200 --alpha-grid -2,-1,-0.5,0,0.5,1,2 --output-dir outputs/ --rubric claude-sonnet --calibration-split 25 --report-split 25 2>&1 | tee /workspace/run.log'",
  "env": {
    "ANTHROPIC_API_KEY": "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",
    "SAGAN_EPS_BRANCH": "issue-363",
    "SAGAN_EPS_COMMIT_SHA": "4685c5745b0fb9f0c025d813b7ed9827305c9473"
  },
  "estimatedMinutes": 540,
  "gpuCount": 1,
  "gpuType": "A100 80GB",
  "name": "chen-vs-centroid-eps-363",
  "volumeGb": 100
}

8:38:53 AMtool_calltools

tool=Bash

Bash

8:38:53 AMtool_resulttools

planJson type: dict
planJson keys: ['sections']
plan pod_spec keys: []
plan substitution_policy present: False

8:38:57 AMtool_calltools

tool=Bash

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8:38:57 AMtool_resulttools

section titles: ['Diagnosis', 'Blocker']

8:39:23 AMtool_calltools

tool=Bash

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8:39:23 AMtool_resulttools

=== experiment.body length: 7023
body first 500: ## Context

This project's "persona vectors" are not persona vectors in the Chen et al. ([arXiv:2507.21509](https://arxiv.org/abs/2507.21509)) sense. The two recipes differ on every methodological choice:

| | Project (`extract_persona_vectors` / `extract_centroids`) | Chen et al. persona vectors |
|---|---|---|
| Object | Per-persona **location** in activation space | Per-trait **direction** in activation space |
| Input | One system prompt per persona | 5 positive + 5 negative paired prompts p

=== figures count: 0

=== artifacts count: 0

8:39:58 AMtool_calltools

tool=Bash

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8:39:58 AMtool_resulttools

approval reqs: 3
id: 1405fa98-b142-48c4-9216-04536c81167a
  resolvedAt: 2026-05-13T13:01:04.880Z
  status: approved
  has bodyMd: False
id: e4d260a3-a852-4893-b87c-71965517a4fc
  resolvedAt: 2026-05-13T04:22:11.776Z
  status: approved
  has bodyMd: True
id: 8922fdd9-16c8-48cf-a60d-54d5ed6a8002
  resolvedAt: 2026-05-13T04:14:17.257Z
  status: approved
  has bodyMd: True

8:40:06 AMtool_calltools

tool=Bash

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8:40:06 AMtool_resulttools

=== runpod-spec block ===
```runpod-spec
{
  "name": "chen-vs-centroid-persona-vectors",
  "gpuType": "H100",
  "gpuCount": 1,
  "volumeGb": 100,
  "containerDiskGb": 100,
  "cloudType": "SECURE",
  "config": {
    "command": "cd /workspace && git clone --depth 1 https://github.com/superkaiba/explore-persona-space.git eps && cd eps && uv sync && timeout 36000 uv run python scripts/run_chen_vs_centroid.py --model Qwen/Qwen2.5-7B-Instruct --traits sycophancy,deception,refusal-tendency,hostility,helpfulness --layers 10,13,16,20,24 --prompts-per-trait 200 --alpha-grid -2,-1,-0.5,0,0.5,1,2 --output-dir outputs/ --rubric claude-sonnet --calibration-split 25 --report-split 25 2>&1 | tee outputs/run.log",
    "artifacts": [
      "outputs/chen_vectors/",
      "outputs/centroid_vectors/",
      "outputs/generations/",
      "outputs/rubric_scores.csv",
      "outputs/random_baseline.json",
      "outputs/summary.json",
      "outputs/clean_result.html",
      "outputs/run.log"
    ]
  }
}
```
--- substitution mentions ---
| - **GPU**: 1× H100 80GB SXM (SECURE cloud). Qwen2.5-7B in bf16 plus
|   inside 80 GB; H100 is chosen for throughput on the 200-prompt × 2-pass
|   cron). Estimated cost ≈ USD 25 at H100 SECURE rates.
| A100 80GB would also fit but generation throughput on Qwen-7B is ~1.7×
| slower; H100 keeps us inside the 8 h target with margin.
| - [ ] **Compute/hardware**: 1× H100 80GB SECURE, ≤ 8 h, hard cap 10 h,
| - [ ] **runpod-spec matches plan**: 1× H100 80GB SECURE, EPS repo cloned,
|   "gpuType": "H100",

8:40:33 AMassistant_textagent

Now I have full clarity on the situation. Let me document the findings before acting:

**Key findings:**
- The "approved plan" handoff is actually a blocker diagnosis from a mis-routed previous Claude agent (agent_run `06287fcc-5901-46ee-a437-a96db8d59fb5`), not a real plan.
- That agent's output was written into `experiments.planJson` (sections now read only `["Diagnosis", "Blocker"]`) — the original plan has been overwritten.
- `podSpec.substitution_policy` is missing (the original H100 SECURE primary + family-swap fallback list is gone); current `podSpec` is the A100 80GB / cloudType=ALL fallback the previous provisioner had cached.
- The previous pod `njchq12a6ytcft` (H100 80GB SXM, team account, $2.99/hr) was actually dispatched at 00:02:03 and the experiment stayed at `running` until 08:25:41 (~8h 24m — well past the 8h expected wall-clock, near the 10h hard cap). It was likely killed by orphan-cleanup or completed but no artifacts/figures are attached.
- Owner moved the board awaiting_clari → running at 08:34:19, signaling retry intent — but the runner's auto-recovery is unaware the experiment's plan/spec state is now corrupted.

Per the orchestrator brief's explicit failure-handling rule (*"on any unrecoverable error, post `epm:failure` with the diagnosis and set status to `blocked`. Do not silently retry"*), I should not silently re-dispatch on a corrupted plan/spec.

8:40:35 AMtool_calltools

tool=TodoWrite

TodoWrite

8:40:35 AMtool_resulttools

Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable

8:40:57 AMtool_calltools

tool=Bash

Bash

8:40:57 AMtool_resulttools

3719 /tmp/blocked_note_363.txt

8:41:07 AMtool_calltools

tool=Bash

Bash

8:41:09 AMtool_resulttools

{
  "id": "e25d12ec-4059-4ea7-846e-a26df56ff469",
  "ok": true
}

8:41:15 AMtool_calltools

tool=Bash

Bash

8:41:15 AMtool_resulttools

post-marker status: approved
latest events:
   2026-05-14T08:25:41.311 | state_changed | running -> awaiting_clarifications | Claude produced clarifying questions; awaiting owner answers.
   2026-05-14T08:34:19.281 | state_changed | awaiting_clarifications -> running | Moved on Pipeline board to running.
   2026-05-14T08:34:19.774 | state_changed | running -> implementing | Orchestrator 0a25b1be queued to implement and dispatch.
   2026-05-14T08:34:20.008 | state_changed | implementing -> approved | Re-used existing plan after moving to running.
   2026-05-14T08:41:08.937 | note | approved -> blocked | Orchestrator 0a25b1be (parent agent_run ba654ea0) cannot safely walk this experi

8:41:19 AMassistant_textagent

The marker was posted as a note but didn't actually transition status. Let me set status explicitly.

8:41:20 AMtool_calltools

tool=Bash

Bash

8:41:20 AMtool_resulttools

usage: sagan_state.py status [-h] [--note NOTE]
                             number
                             {approved,archived,awaiting_approval,awaiting_promotion,blocked,cancelled,clarifying,clean_result_drafting,code_reviewing,completed,done_experiment,done_impl,failed,followups_running,gate_pending,implementing,interpreting,plan_pending,planning,proposed,queued,reviewing,running,shared,testing,uploading,verifying}

positional arguments:
  number
  {approved,archived,awaiting_approval,awaiting_promotion,blocked,cancelled,clarifying,clean_result_drafting,code_reviewing,completed,done_experiment,done_impl,failed,followups_running,gate_pending,implementing,interpreting,plan_pending,planning,proposed,queued,reviewing,running,shared,testing,uploading,verifying}

options:
  -h, --help            show this help message and exit
  --note NOTE

8:41:26 AMtool_calltools

tool=Bash

Bash

8:41:27 AMtool_resulttools

{
  "experiment": {
    "id": "0c120ea3-746a-43e6-a760-e6112f8cb649",
    "status": "blocked",
    "title": "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
    "turn": "Owner turn: unblock or revise"
  },
  "ok": true
}

8:41:33 AMtool_calltools

tool=Bash

Bash

8:41:33 AMtool_resulttools

final status: blocked
last 3 events:
   2026-05-14T08:34:20.008 | state_changed | implementing -> approved
     note: Re-used existing plan after moving to running.
   2026-05-14T08:41:08.937 | note | approved -> blocked
     note: Orchestrator 0a25b1be (parent agent_run ba654ea0) cannot safely walk this experiment through the wor
   2026-05-14T08:41:27.583 | blocked | approved -> blocked
     note: epm:failure posted by orchestrator 0a25b1be. See workflow_event e25d12ec for full diagnosis. Summary

8:41:37 AMtool_calltools

tool=TodoWrite

TodoWrite

8:41:37 AMtool_resulttools

Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable

8:41:51 AMassistant_textagent

Experiment #363 is now at `status=blocked` with `epm:failure` posted (workflow_event `e25d12ec-4059-4ea7-846e-a26df56ff469`). Stopping here per the orchestrator brief's failure-handling rule.

**Summary of what I did and why:**

The handoff content I was given as the "approved plan" is itself a blocker — it's the output of a mis-routed prior auto-recovery session (`06287fcc-…`) that produced clarifying questions instead of executing pod-provisioner recovery. That output was written into `experiments.planJson`, so the experiment's plan now contains only `["Diagnosis", "Blocker"]` sections, and `podSpec.substitution_policy` is gone. The previous pod `njchq12a6ytcft` (H100 80GB SXM, team account) ran for ~8h 24m before the state moved off `running`, with no artifacts attached and no active pods reported — its outcome is unknown.

Silently re-dispatching from this state would:
- Risk wasting another ~$25 + 8h of compute if the previous pod's volume still holds valid `outputs/`.
- Re-hit `SUPPLY_CONSTRAINT` (the saved A100/ALL spec is the failed-primary residue, not the planner-authorized chain).
- Land in a configuration the owner never approved.

Owner unblock path (in `epm:failure` note):
1. Check RunPod team-account console for pod `njchq12a6ytcft`'s volume — if `outputs/chen_vectors/`, `centroid_vectors/`, `rubric_scores.csv`, `summary.json` are there, rsync + uploader and skip straight to `verifying`.
2. Otherwise: restore `planJson` from approval-request `e4d260a3`'s bodyMd and re-populate `podSpec.substitution_policy`.
3. Then flip status off `blocked` (do **not** just move the Pipeline-board card — that's what landed this orchestrator in the corrupted state in the first place).

Implementation is intact: branch `issue-363 @ 4685c574` is pushed, code-review pair PASSed, tests PASSed — no re-implementer/re-reviewer needed.

<<<DONE>>>

8:41:51 AMsdk_resultagent

success

8:41:51 AMcompletedagent

Experiment #363 is now at `status=blocked` with `epm:failure` posted (workflow_event `e25d12ec-4059-4ea7-846e-a26df56ff469`). Stopping here per the orchestrator brief's failure-handling rule.

**Summary of what I did and why:**

The handoff content I was given as the "approved plan" is itself a blocker — it's the output of a mis-routed prior auto-recovery session (`06287fcc-…`) that produced clarifying questions instead of executing pod-provisioner recovery. That output was written into `experiments.planJson`, so the experiment's plan now contains only `["Diagnosis", "Blocker"]` sections, and `podSpec.substitution_policy` is gone. The previous pod `njchq12a6ytcft` (H100 80GB SXM, team account) ran for ~8h 24m before the state moved off `running`, with no artifacts attached and no active pods reported — its outcome is unknown.

Silently re-dispatching from this state would:
- Risk wasting another ~$25 + 8h of compute if the previous pod's volume still holds valid `outputs/`.
- Re-hit `S…

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