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Run 0bdc4c55

experiment-orchestrator-for:f86281ce-da03-4f60-871a-a8723393c758 Drive experiment 0c120ea3-746a-43e6-a760-e6112f8cb649 from approved plan through awaiting_promotion. Sub-agents are loaded from .claude/agents/.

Statuscompleted123 events · latest 1326h 19m 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

9:25:37 AMstartedagent
kind=apply
9:25:54 AMtool_calltools

tool=Bash

Bash
9:25:54 AMtool_resulttools
/bin/bash: line 4: python: command not found
9:25:57 AMtool_calltools

tool=Bash

Bash
9:25:57 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: argument command: invalid choice: 'show' (choose from 'list', 'view', 'status', 'patch', 'marker', 'markers', 'promote', 'launch-pod', 'clean-result')
9:26:00 AMtool_calltools

tool=Bash

Bash
9:26:01 AMtool_resulttools
<persisted-output>
Output too large (87.7KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/105c200a-e85d-42ca-b9df-24675486b446/tool-results/b43vc2y55.txt

Preview (first 2KB):
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  "approvalRequests": [
    {
      "agentRunId": null,
      "approvedState": "approved",
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      "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",
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      "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"
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      "approvedState": "approved",
...
</persisted-output>
9:26:03 AMtool_calltools

tool=Bash

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9:26:04 AMtool_resulttools
<persisted-output>
Output too large (47.2KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/105c200a-e85d-42ca-b9df-24675486b446/tool-results/b8xc6344q.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>
9:26:07 AMtool_calltools

tool=Bash

Bash
9:26:07 AMtool_resulttools
<persisted-output>
Output too large (87.7KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/105c200a-e85d-42ca-b9df-24675486b446/tool-results/bbsefq2oc.txt

Preview (first 2KB):
{
  "approvalRequests": [
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      "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",
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      "agentRunId": "a1f04a02-f418-461b-904c-0b05d29528d1",
      "approvedState": "approved",
...
</persisted-output>
9:26:10 AMtool_calltools

tool=Read

Read
9:26:10 AMtool_resulttools
File content (37321 tokens) exceeds maximum allowed tokens (25000). Use offset and limit parameters to read specific portions of the file, or search for specific content instead of reading the whole file.
9:26:15 AMtool_calltools

tool=Bash

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9:26:16 AMtool_resulttools
{}
9:26:19 AMtool_calltools

tool=Bash

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9:26:20 AMtool_resulttools
<persisted-output>
Output too large (47KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/105c200a-e85d-42ca-b9df-24675486b446/tool-results/ben3gnweu.txt

Preview (first 2KB):
{
    "experiment": {
        "id": "0c120ea3-746a-43e6-a760-e6112f8cb649",
        "number": 363,
        "legacyGhNumber": 363,
        "beliefId": null,
        "projectId": null,
        "title": "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
        "body": "## Context\n\nThis 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:\n\n| | Project (`extract_persona_vectors` / `extract_centroids`) | Chen et al. persona vectors |\n|---|---|---|\n| Object | Per-persona **location** in activation space | Per-trait **direction** in activation space |\n| Input | One system prompt per persona | 5 positive + 5 negative paired prompts per trait |\n| Token position | Last **prompt** token (before generation) | Average over **response** tokens (per their ablation) |\n| Filtering | None | Filter rollouts by GPT-4.1-mini judge score (>50 / <50) |\n| Math | Average across questions per persona | Mean difference \u03bc_pos \u2212 \u03bc_neg across filtered responses |\n| Layer choice | Fixed at L20 (in `scripts/run_trait_transfer.py`) | Selected by steering effectiveness |\n\nWhen the project does treat centroids as directions, it's by taking a difference like `persona_centroid \u2212 assistant_centroid` (e.g., [#267](https://github.com/superkaiba/explore-persona-space/issues/267)'s \"centroid steering\"). The Chen et al. equivalent for the same trait \u2014 e.g. \"evil\" \u2014 would be the mean difference between rollouts under their 5 positive evil prompts (judge > 50) and their 5 negative evil prompts (judge < 50), averaged over response tokens.\n\n**Open question.** Do these two recipes produce directions that are close to each other? [#216](https://github.com/superkaiba/explore-persona-space/issues/216) already found that **different extraction recipes disagree on absolute dire
...
</persisted-output>
9:26:24 AMtool_calltools

tool=Bash

Bash
9:26:25 AMtool_resulttools
Number: 363
Status: implementing
Title: Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference 
Pod spec: {
  "name": "exp363-chen-vs-project-evil-retry4",
  "config": {
    "command": "Implement Chen et al. persona-vector extraction for the evil trait on Qwen2.5-7B-Instruct, extract the project's centroid-difference direction for the same trait, and report cosine similarity at L10/L15/L20/L25 with cos@L20 as the headline.",
    "artifacts": [
      "artifacts/experiment_363/trait_evil_artifacts.json",
      "artifacts/experiment_363/rollouts.jsonl",
      "artifacts/experiment_363/judge_scores.jsonl",
      "artifacts/experiment_363/chen_directions.pt",
      "artifacts/experiment_363/project_directions.pt",
      "artifacts/experiment_363/cosine_table.json",
      "artifacts/experiment_363/summary.json"
    ]
  },
  "gpuType": "H100",
  "gpuCount": 1,
  "volumeGb": 100,
  "cloudType": "SECURE",
  "dockerArgs": "bash -lc 'cd /workspace/explore-persona-space && uv run python scripts/run_experiment_363.py'",
  "consolidation": {
    "may_merge_pods": false,
    "merge_target_max_gpus_per_pod": 1
  },
  "containerDiskGb": 100,
  "estimatedMinutes": 90,
  "substitution_policy": {
    "account": {
      "prefer": "team",
      "allowed": [
        "team",
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    "gpuType": {
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      "min": 1
    },
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    },
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      "allowed": [
        "SECURE",
        "COMMUNITY"
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    },
    "dataCenterId": {
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        "EU-RO-1",
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        "US-KS-2"
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      "allowed": "any"
    },
    "containerDiskGb": {
      "min": 100
    }
  }
}
9:26:28 AMtool_calltools

tool=Bash

Bash
9:26:29 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
9:26:32 AMtool_calltools

tool=Bash

Bash
9:26:32 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 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
9:26:38 AMtool_calltools

tool=Bash

Bash
9:26:38 AMtool_resulttools
Exit code 1
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)
9:26:42 AMtool_calltools

tool=Bash

Bash
9:26:42 AMtool_resulttools
(Bash completed with no output)
9:26:45 AMtool_calltools

tool=Bash

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9:26:46 AMtool_resulttools
HTTP/2 405 
cache-control: public, max-age=0, must-revalidate
date: Thu, 14 May 2026 09:26:46 GMT
server: Vercel
strict-transport-security: max-age=63072000
x-matched-path: /api/experiments/[id]/workflow-events
x-vercel-cache: BYPASS
x-vercel-enable-rewrite-caching: 1
x-vercel-id: sfo1::iad1::tc6qk-1778750806002-d1177fc7716a
content-length: 0
9:26:50 AMtool_calltools

tool=Bash

Bash
9:26:51 AMtool_resulttools
Total workflow events: 0
9:26:55 AMtool_calltools

tool=Bash

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9:26:56 AMtool_resulttools
Top-level keys: ['experiment', 'events', 'approvalRequests']
Experiment keys: ['id', 'number', 'legacyGhNumber', 'beliefId', 'projectId', 'title', 'body', 'hypothesis', 'planMd', 'planJson', 'podSpec', 'configYaml', 'status', 'kind', 'computeSize', 'priority', 'assigneeKind', 'tags', 'hasCleanResult', 'autoApprovePlan', 'parentExperimentId', 'runpodAccount', 'convertedToKind', 'convertedToId', 'createdAt', 'updatedAt', 'turn']
9:27:00 AMtool_calltools

tool=Bash

Bash
9:27:01 AMtool_resulttools
Total events: 50
2026-05-13T23:58:03 state_changed                            Orchestrator 3e5c1604: code-review pair PASS and test verdict PASS carried forward on issue-363 @ 4685c574. podSpec alre
2026-05-13T23:57:33 note                                     Carry-forward: lint + unit tests passed at 4685c574 in prior cycle. No code changes in this recovery (only pod-spec GPU 
2026-05-13T23:57:28 state_changed                            Both reviewers PASS at 4685c574; tests run by code-reviewer step 4 already passed in prior cycle. Forwarding test verdic
2026-05-13T23:57:23 note                                     Carry-forward from prior orchestrator cycle: Codex pair concurred on PASS at 4685c574. No new fixes required for the rec
2026-05-13T23:57:19 note                                     Carry-forward from prior orchestrator cycle: code-review pair already passed on issue-363 @ 4685c574 (commit specificall
2026-05-13T23:57:13 state_changed                            Code-review pair already passed on this commit (4685c574) per prior orchestrator cycle. Re-recording the prior verdicts 
2026-05-13T23:57:02 note                                     Implementation already complete on issue-363 @ 4685c574 (prior orchestrator). Recovery run: only delta vs prior dispatch
2026-05-13T23:56:56 state_changed                            Orchestrator 3e5c1604: walking through workflow. Plan re-approved by owner. Implementation already complete on branch is
2026-05-13T23:54:16 state_changed                            Re-used existing plan after moving to running.
2026-05-13T23:54:16 state_changed                            Orchestrator 3e5c1604 queued to implement and dispatch.
2026-05-13T23:54:16 state_changed                            Moved on Pipeline board to running.
2026-05-13T22:57:41 state_changed                            Owner: restore to awaiting-approval after spurious pod-stop cascade
2026-05-13T22:13:42 state_changed                            RunPod pod stopped; volume preserved.
2026-05-13T20:19:46 note                                     Pod committed: `v57xxy412px5mz` on NVIDIA H100 PCIe SECURE (account: team, $2.39/hr). Pod-provisioner substitution ladde
2026-05-13T20:19:03 state_changed                            RunPod pod is running.
2026-05-13T20:18:59 state_changed                            RunPod pod dispatched; waiting for runtime.
2026-05-13T20:16:29 state_changed                            Code-review pair PASS + tests PASS on issue-363 @ 4685c574. podSpec restored with SAGAN_EPS_BRANCH=issue-363 and SAGAN_E
2026-05-13T20:15:37 note                                     Carry-forward: Step 4 of code-review pair confirmed tests on commit 4685c574 (issue-363 v2): `ruff check` clean, `uv run
2026-05-13T20:15:31 note                                     Carry-forward: code-review pair both verdict PASS in round 2 — reconciliation trivial, no targeted fix required. Proceed
2026-05-13T20:15:26 note                                     Carry-forward: Codex code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Codex's round-1 findings overlapped w
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2026-05-14T09:25:37 state_changed                            Orchestrator 0bdc4c55 queued to implement and dispatch.
2026-05-14T09:25:37 state_changed                            Auto-approved follow-up plan (experiment.auto_approve_plan=true).
2026-05-14T09:23:17 state_changed                            Automatic recovery queued after agent run ae39b358 failed.
2026-05-14T09:14:07 blocked                                  Cascaded from agent_run 7c3617f7 stale
2026-05-14T09:11:16 note                                     Carry-forward (orchestrator 888e6726): pod o9hlewv1vn3vfe was direct-dispatched on H100 by the auto-recovery system at 0
2026-05-14T09:11:06 note                                     Carry-forward (orchestrator 888e6726): Step 4 of code-review pair confirmed tests on commit 4685c574 (issue-363 v2): ruf
2026-05-14T09:11:05 note                                     Carry-forward (orchestrator 888e6726): code-review pair both verdict PASS in round 2 — reconciliation trivial, no target
2026-05-14T09:11:04 note                                     Carry-forward (orchestrator 888e6726): Codex code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Codex's round
2026-05-14T09:11:03 note                                     Carry-forward (orchestrator 888e6726): Claude code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Round-1 rais
2026-05-14T09:10:52 note                                     Carry-forward (orchestrator 888e6726): implementation already complete on branch issue-363 @ 4685c574 (commits b8344b3b 
2026-05-14T09:08:10 state_changed                            RunPod pod is running.
2026-05-14T09:07:42 state_changed                            Orchestrator 888e6726 queued to implement and dispatch.
2026-05-14T09:07:42 state_changed                            Auto-approved follow-up plan (experiment.auto_approve_plan=true).
2026-05-14T09:07:10 state_changed                            RunPod pod is running.
2026-05-14T09:06:55 state_changed                            RunPod pod dispatched; waiting for runtime.
2026-05-14T09:06:01 state_changed                            Automatic recovery queued after agent run 4cf5d7b9 failed.
2026-05-14T09:06:01 blocked                                  spec[0]: GraphQL errors: [{"message":"Something went wrong. Please try again later or contact support.","path":["podFind
2026-05-14T08:55:36 state_changed                            Orchestrator a9e13965 queued to implement and dispatch.
2026-05-14T08:55:36 state_changed                            Auto-approved follow-up plan (experiment.auto_approve_plan=true).
2026-05-14T08:52:34 state_changed                            Automatic recovery queued after agent run 25460511 failed.
2026-05-14T08:52:34 blocked                                  spec[0]: GraphQL errors: [{"message":"There are no longer any instances available with the requested specifications. Ple
2026-05-14T08:41:27 blocked                                  epm:failure posted by orchestrator 0a25b1be. See workflow_event e25d12ec for full diagnosis. Summary: planJson was overw
2026-05-14T08:41:08 note                                     Orchestrator 0a25b1be (parent agent_run ba654ea0) cannot safely walk this experiment through the workflow — the state wa
2026-05-14T08:34:20 state_changed                            Re-used existing plan after moving to running.
2026-05-14T08:34:19 state_changed                            Orchestrator 0a25b1be queued to implement and dispatch.
2026-05-14T08:34:19 state_changed                            Moved on Pipeline board to running.
2026-05-14T08:25:41 state_changed                            Claude produced clarifying questions; awaiting owner answers.
2026-05-14T00:02:16 state_changed                            RunPod pod is running.
2026-05-14T00:02:03 note                                     Pod committed: njchq12a6ytcft on H100 80GB SXM (cloudType=ALL, team account, $2.99/hr). Provisioner attempts 1-3 hit SUP
2026…
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From https://github.com/superkaiba/explore-persona-space
 * branch              issue-363  -> FETCH_HEAD
4685c574 issue #363 v2: address review findings (cal/rep dedupe, alpha*||v||, real position ablation, single hook target, NLL chat template, rubric 0-1)
b8344b3b issue #363: Chen et al. persona-vector extraction recipe + centroid baseline
a4652b62 Route EPS workflow state through Sagan
4129f88d Add Sagan pod progress reporting guidance
d0db2db7 Complete Sagan workflow migration
ls: cannot access 'scripts/run_experiment_363.py': No such file or directory
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Switched to a new branch 'issue-363'
Branch 'issue-363' set up to track remote branch 'issue-363' from 'origin'.
commit 4685c5745b0fb9f0c025d813b7ed9827305c9473
Author: Thomas Jiralerspong <thomas@superkaiba.com>
Date:   Wed May 13 14:09:01 2026 +0000

    issue #363 v2: address review findings (cal/rep dedupe, alpha*||v||, real position ablation, single hook target, NLL chat template, rubric 0-1)
    
    Round-2 fixes from code-review v1 verdict (needs_targeted_fix, 6 findings):
    
    1. cal/rep split collapse: widened TRAIT_PROBE_POOL from 225 to 265 unique
       prompts (200 extraction + 25 cal + 25 rep, all disjoint). Replaced the
       silent overlap fallback in _build_steering_probes with a hard RuntimeError
       + explicit set-disjoint assertions in main() over extraction/cal/rep.
    
    2. Steering magnitude: hook now adds alpha*v (so added L2 == |alpha|*||v||)
       instead of alpha*unit_v (added L2 == |alpha|). Matches plan and
       --alpha-grid help. Magnitude logged at INFO per call.
    
    3. Position-confound ablation rewritten: extract_centroid_on_prompt_at_layer
       uses Chen's same personas + probes + completions + hook target + second
       forward pass, but averages over prompt-token positions instead of
       completion-token positions. Saved to outputs/ablation_centroid_on_prompt/.
       Renamed recipe in sweep / summary / clean_result.html accordingly.
    
    4. Hook target alignment: ChenExtractionConfig.hook_target default changed
       from input_layernorm to block (matches scripts/extract_persona_vectors.py
       and the runner's steering + centroid hook sites — all three now in
       residual-stream space).
    
    5. NLL chat-template fix: compute_mean_nll now builds full_text via
       apply_chat_template on (user, assistant) instead of string-concatenating
       prompt_text + completion. Added one-shot prefix invariant assertion
       full_ids[:prompt_len] == prompt_ids.
    
    6. Rubric unit normalization: _normalize_rubric_score divides judge 0-100
       output by 100 at the boundary in judge_completions_sync. Preserves raw
       value as aligned_raw100. summary.json now records a sanity row with raw
       vs normalized means; clean_result.html y-axis label says 0-1 normalized.
       One-shot range assertion on first call.
    
    Lint: ruff check + format pass.
ls: cannot access 'scripts/run_experiment_363.py': No such file or directory
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extract_persona_vectors.py
run_chen_vs_centroid.py
verify_chen_vs_centroid.py
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#!/usr/bin/env python3
"""Run Chen-style persona-vector extraction vs the project's centroid recipe.

Experiment: Sagan #363
    Implement Chen et al. persona-vector extraction recipe and compare it
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1f2a5bfb feat: #370 broader-vocab + suffix-isolation sweeps
13bff7b1 Issue #333 round-3 fixes: correct HF dataset path, surface real errors, drop deprecated kwarg
36614ea4 util: sagan_progress helper for experiment scripts
ac962be9 On main: wip before issue-370 branch
d8f1983b index on main: a9aba1bf util: sagan_progress helper for experiment scripts
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#!/usr/bin/env python3
"""Run Chen-style persona-vector extraction vs the project's centroid recipe.

Experiment: Sagan #363
    Implement Chen et al. persona-vector extraction recipe and compare it
    head-to-head against the project's centroid-difference recipe on five
    target traits, sweeping a layer set and an alpha-grid, then scoring steered
    completions with the existing Claude rubric judge.

This script is the single pod-side entrypoint named in the runpod-spec block of
the experiment plan. It runs sequentially through:

    1. Load probe prompts and trait persona pairs.
    2. CHEN extraction:
        - Generate paired pos/neg completions with vLLM (greedy, max=128).
        - Forward-pass under HF with hooks; mean over completion tokens only.
        - Save per-trait (n_layers, d_model) tensor to outputs/chen_vectors/.
    3. CENTROID extraction (re-implemented inline against the same probes):
        - For every probe, run two HF forward passes - one with the trait+
          system prompt, one with the trait- system prompt - and capture the
          hidden state at the LAST input token. Difference-of-means across
          probes gives the centroid persona vector.
        - Save per-trait (n_layers, d_model) tensor to outputs/centroid_vectors/.
    4. CENTROID-ON-PROMPT ABLATION (position-confound control, L20 only):
        - Re-use Chen's paired completions exactly, do the same second forward
          pass, but mean over PROMPT-token positions (everything BEFORE the
          assistant turn) instead of completion-token positions. Differs from
          Chen in exactly one variable: the span of positions averaged. Saved
          to outputs/ablation_centroid_on_prompt/<trait>.pt.
    5. RANDOM-DIRECTION BASELINE at L20:
        - 200 random unit vectors, pairwise cosines, 95% interval.
        - Cosine of Chen[L20] and centroid[L20] vs a held-out random unit.
    6. PAIRWISE COSINE: cosine(Chen[t, L], centroid[t, L]) for every (t, L).
    7. alpha-SWEEP (split 25 calibration / 25 reporting, disjoint from extraction):
        - For each trait x recipe x alpha in alpha_grid:
            * Generate 50 trait-probe completions with the model PLUS an
              activation-add hook at L20. Hook adds ``alpha * v`` (so the
              added perturbation has L2 norm ``|alpha| * ||v||`` - alpha is
              in units of the persona vector's own norm).
            * Mean per-token NLL of each completion under the unsteered base
              model (for the NLL ratio constraint).
        - Score every completion with the existing alignment judge
          (Claude Sonnet via `evaluate_alignment`'s judge).
        - Pick alpha* per (trait, recipe) on the 25-prompt calibration split:
          maximize rubric shift subject to mean-NLL <= 1.5 x baseline.
        - Report rubric shift at alpha* with 95% bootstrap CI (1000 resamples)
          on the 25-prompt reporting split.
    8. Emit outputs/summary.json, outputs/rubric_scores.csv, outputs/random_baseline.json,
       outputs/generations/<recipe>/<trait>/<alpha>.jsonl, outputs/clean_result.html.
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Status: implementing
runpodAccount: team
2026-05-14T09:25:37 state_changed             Orchestrator 0bdc4c55 queued to implement and dispatch.
2026-05-14T09:25:37 state_changed             Auto-approved follow-up plan (experiment.auto_approve_plan=true).
2026-05-14T09:23:17 state_changed             Automatic recovery queued after agent run ae39b358 failed.
2026-05-14T09:14:07 blocked                   Cascaded from agent_run 7c3617f7 stale
2026-05-14T09:11:16 note                      Carry-forward (orchestrator 888e6726): pod o9hlewv1vn3vfe was direct-dispatched on H100 by the auto-recovery system at 09:06:54 (agent_run a
2026-05-14T09:11:06 note                      Carry-forward (orchestrator 888e6726): Step 4 of code-review pair confirmed tests on commit 4685c574 (issue-363 v2): ruff check clean, uv ru
2026-05-14T09:11:05 note                      Carry-forward (orchestrator 888e6726): code-review pair both verdict PASS in round 2 — reconciliation trivial, no targeted fix required. Pro
2026-05-14T09:11:04 note                      Carry-forward (orchestrator 888e6726): Codex code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Codex's round-1 findings overlapp
2026-05-14T09:11:03 note                      Carry-forward (orchestrator 888e6726): Claude code-reviewer verdict PASS on commit 4685c574 (issue-363 v2). Round-1 raised 6 findings (cal/r
2026-05-14T09:10:52 note                      Carry-forward (orchestrator 888e6726): implementation already complete on branch issue-363 @ 4685c574 (commits b8344b3b + 4685c574 v2). File
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2026-05-14T09:27:27 experiment running         request=[test-dispatch:exp#366:A100-capacity-probe]
2026-05-14T09:27:27 apply      completed       request=experiment-orchestrator-for:b5200f56-6194-4522-9a58-e3117f2c
2026-05-14T09:26:25 apply      running         request=experiment-orchestrator-for:eb2acb04-417a-46c6-96bd-31aba818
2026-05-14T09:25:37 apply      running         request=experiment-orchestrator-for:f86281ce-da03-4f60-871a-a8723393
2026-05-14T09:25:15 apply      running         request=experiment-orchestrator-for:0c382d32-0089-4463-8107-b7e29b82
2026-05-14T09:23:17 experiment completed       request=[auto-recovery-for:ae39b358-5f42-4a57-bdb8-c9da8e866617]

Th
2026-05-14T09:23:11 experiment completed       request=[auto-recovery-for:15038ff7-4cef-4b08-a897-2eee4f493062]

Th
2026-05-14T09:23:07 experiment completed       request=[auto-recovery-for:2e87b5a3-7a09-428b-bdbe-efdb765fb732]

Th
2026-05-14T09:22:26 experiment completed       request=[auto-recovery-for:3cc4715e-210f-4b80-9d15-0809770ff504]

Th
2026-05-14T09:22:25 experiment blocked         request=[test-dispatch:exp#366:COMMUNITY]
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2026-05-14T09:27:27 running      pod=w8zh8zs644se30 req=[test-dispatch:exp#366:A100-capacity-probe]
2026-05-14T09:23:17 completed    pod=None req=[auto-recovery-for:ae39b358-5f42-4a57-bdb8-c9da8e866617
2026-05-14T09:23:11 completed    pod=None req=[auto-recovery-for:15038ff7-4cef-4b08-a897-2eee4f493062
2026-05-14T09:23:07 completed    pod=None req=[auto-recovery-for:2e87b5a3-7a09-428b-bdbe-efdb765fb732
2026-05-14T09:22:26 completed    pod=None req=[auto-recovery-for:3cc4715e-210f-4b80-9d15-0809770ff504
2026-05-14T09:22:25 blocked      pod=None req=[test-dispatch:exp#366:COMMUNITY]
2026-05-14T09:21:07 completed    pod=None req=[auto-recovery-for:32ad609a-075c-4076-a05d-31e7f885588a
2026-05-14T09:06:54 cancelled    pod=o9hlewv1vn3vfe req=[direct-dispatch:bypass-orchestrator-block:exp#363:retr
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2026-05-14T09:27:27 status=running    pod=w8zh8zs644se30
2026-05-14T09:06:54 status=cancelled  pod=o9hlewv1vn3vfe
2026-05-14T09:03:09 status=cancelled  pod=hx5qglq11gau0i
2026-05-14T09:02:28 status=blocked    pod=vt4ui9cgqo675e
2026-05-14T08:52:34 status=running    pod=yur1wxa4ztn2ky
2026-05-14T08:52:34 status=blocked    pod=pc79b5566vhrz6
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2026-05-14T09:27:27 status=running    pod=w8zh8zs644se30       req=[test-dispatch:exp#366:A100-capacity-probe]
2026-05-14T09:06:54 status=cancelled  pod=o9hlewv1vn3vfe       req=[direct-dispatch:bypass-orchestrator-block:exp#363:retr
2026-05-14T09:03:09 status=cancelled  pod=hx5qglq11gau0i       req=[direct-dispatch:bypass-orchestrator-block:exp#333:retr
2026-05-14T09:02:28 status=blocked    pod=vt4ui9cgqo675e       req=[direct-dispatch:bypass-orchestrator-block:exp#365:retr
2026-05-14T08:52:34 status=running    pod=yur1wxa4ztn2ky       req=[direct-dispatch:bypass-orchestrator-block:exp#366]

Op
2026-05-14T08:52:34 status=blocked    pod=pc79b5566vhrz6       req=[direct-dispatch:bypass-orchestrator-block:exp#192]

Op
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---
{
  "id": "ae39b358-5f42-4a57-bdb8-c9da8e866617",
  "kind": "experiment",
  "provider": "claude_code",
  "status": "cancelled",
  "request": "[direct-dispatch:bypass-orchestrator-block:exp#363:retry-3-H100]",
  "approvalRequired": false,
  "approvedBy": null,
  "approvedAt": null,
  "scopeEntityKind": "experiment",
  "scopeEntityId": "0c120ea3-746a-43e6-a760-e6112f8cb649",
  "chatSessionId": null,
  "branchName": null,
  "vercelDeploymentUrl": null,
  "runpodAccount": "team",
  "runpodPodId": "o9hlewv1vn3vfe",
  "runpodPodIds": [
    "o9hlewv1vn3vfe"
  ],
  "runpodStatus": "running",
  "transcriptLogPath": null,
  "changedFilesJson": null,
  "lastError": "Terminated by operator: pods rented but containers never started (RunPod scheduling)",
  "startedAt": null,
  "completedAt": "2026-05-14T09:23:25.640Z",
  "createdAt": "2026-05-14T09:06:54.274Z",
  "updatedAt": "2026-05-14T09:23:25.640Z"
}
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1531
4685c5745b0fb9f0c025d813b7ed9827305c9473
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4685c5745b0fb9f0c025d813b7ed9827305c9473	refs/heads/issue-363
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9:29:07 AMassistant_textagent
Good — branch `issue-363` is pushed at `4685c5745b0fb9f0c025d813b7ed9827305c9473`. The actual entrypoint script is `scripts/run_chen_vs_centroid.py` (not `run_experiment_363.py`). I'll need to correct the dockerArgs in the podSpec.

Let me post implementation/code-review/test markers as carry-forward (we are on retry-4, prior cycles validated this), then fix the dockerArgs and splice in the branch env vars.
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{"error":"invalid_review_round","message":"reviewer-loop round must be an integer from 1 to 3."}
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{
  "id": "117ccb48-8ecc-4b76-8c40-21ce1d164680",
  "ok": true
}
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{
  "id": "6f5094df-5fc2-43f0-8f71-405a6de8a32a",
  "ok": true
}
{
  "id": "b2f74ca6-50a5-49b8-9b8b-ab973a88098d",
  "ok": true
}
{
  "id": "44804a94-982c-44e4-8327-4f2a78c29070",
  "ok": true
}
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{
  "id": "c6213cfc-2321-48f1-b470-5aa7ebdd0c9d",
  "ok": true
}
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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
9:29:40 AMassistant_textagent
Now patch the podSpec — fix dockerArgs and add the branch/commit env vars.
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{
  "name": "exp363-chen-vs-project-evil-retry4",
  "config": {
    "command": "Implement Chen et al. persona-vector extraction for the evil trait on Qwen2.5-7B-Instruct, extract the project's centroid-difference direction for the same trait, and report cosine similarity at L10/L15/L20/L25 with cos@L20 as the headline.",
    "artifacts": [
      "artifacts/experiment_363/trait_evil_artifacts.json",
      "artifacts/experiment_363/rollouts.jsonl",
      "artifacts/experiment_363/judge_scores.jsonl",
      "artifacts/experiment_363/chen_directions.pt",
      "artifacts/experiment_363/project_directions.pt",
      "artifacts/experiment_363/cosine_table.json",
      "artifacts/experiment_363/summary.json"
    ]
  },
  "gpuType": "A100",
  "gpuCount": 1,
  "volumeGb": 100,
  "cloudType": "SECURE",
  "dockerArgs": "bash -lc 'cd /workspace/explore-persona-space && uv run python scripts/run_chen_vs_centroid.py'",
  "consolidation": {
    "may_merge_pods": false,
    "merge_target_max_gpus_per_pod": 1
  },
  "containerDiskGb": 100,
  "estimatedMinutes": 90,
  "substitution_policy": {
    "account": {
      "prefer": "team",
      "allowed": [
        "team",
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{
    "ok": true,
    "experiment": {
        "id": "0c120ea3-746a-43e6-a760-e6112f8cb649",
        "title": "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
        "status": "implementing",
        "turn": "Sagan turn: run and verify"
    }
}
9:30:08 AMtool_calltools

tool=Bash

Bash
9:30:09 AMtool_resulttools
dockerArgs: bash -lc 'cd /workspace/explore-persona-space && uv run python scripts/run_chen_vs_centroid.py'
gpuType: A100
env: {
  "SAGAN_EPS_BRANCH": "issue-363",
  "SAGAN_EPS_COMMIT_SHA": "4685c5745b0fb9f0c025d813b7ed9827305c9473"
}
9:30:12 AMassistant_textagent
Now transition status to `running` and dispatch via pod-provisioner.
9:30:14 AMtool_calltools

tool=Bash

Bash
9:30:17 AMtool_resulttools
{
  "experiment": {
    "id": "0c120ea3-746a-43e6-a760-e6112f8cb649",
    "status": "running",
    "title": "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe",
9:30:20 AMtool_calltools

tool=Bash

Bash
9:30:20 AMtool_resulttools
{
  "name": "exp363-chen-vs-project-evil-retry4",
  "config": {
    "command": "Implement Chen et al. persona-vector extraction for the evil trait on Qwen2.5-7B-Instruct, extract the project's centroid-difference direction for the same trait, and report cosine similarity at L10/L15/L20/L25 with cos@L20 as the headline.",
    "artifacts": [
      "artifacts/experiment_363/trait_evil_artifacts.json",
      "artifacts/experiment_363/rollouts.jsonl",
      "artifacts/experiment_363/judge_scores.jsonl",
      "artifacts/experiment_363/chen_directions.pt",
      "artifacts/experiment_363/project_directions.pt",
      "artifacts/experiment_363/cosine_table.json",
      "artifacts/experiment_363/summary.json"
    ]
  },
  "gpuType": "A100",
  "gpuCount": 1,
  "volumeGb": 100,
  "cloudType": "SECURE",
  "dockerArgs": "bash -lc 'cd /workspace/explore-persona-space && uv run python scripts/run_chen_vs_centroid.py'",
  "consolidation": {
    "may_merge_pods": false,
    "merge_target_max_gpus_per_pod": 1
  },
  "containerDiskGb": 100,
  "estimatedMinutes": 90,
  "substitution_policy": {
    "account": {
      "prefer": "team",
      "allowed": [
        "team",
        "personal"
      ]
    },
    "gpuType": {
      "allowed": [
        "H100",
        "H200",
        "A100-SXM",
        "A100-PCIe",
        "L40S"
      ],
      "min_vram_gb": 48
    },
    "gpuCount": {
      "max": 1,
      "min": 1
    },
    "volumeGb": {
      "min": 100
    },
    "cloudType": {
      "prefer": "SECURE",
      "allowed": [
        "SECURE",
        "COMMUNITY"
      ]
    },
    "dataCenterId": {
      "prefer": [
        "US-CA-2",
        "EU-RO-1",
        "US-GA-1",
        "US-KS-2"
      ],
      "allowed": "any"
    },
    "containerDiskGb": {
      "min": 100
    }
  },
  "env": {
    "SAGAN_EPS_BRANCH": "issue-363",
    "SAGAN_EPS_COMMIT_SHA": "4685c5745b0fb9f0c025d813b7ed9827305c9473"
  }
}
9:30:38 AMtool_calltools

tool=Agent

Agent
9:30:41 AMtool_calltools

tool=Read

Read
9:30:42 AMtool_resulttools
1	---
2	name: feedback-spec-json-quoting
3	description: Write --spec-json content to a temp file and cat it into the variable; heredoc expansion introduces a leading newline that fails JSON parsing at position 1
4	metadata:
5	  type: feedback
6	---
7	
8	When passing --spec-json to pod-tool attempt, do NOT use a heredoc directly in the variable assignment. The heredoc introduces a leading newline which makes pod-tool report "Expected property name or '}' in JSON at position 1" and exit 2.
9	
10	**Why:** The shell heredoc places a newline at the very start of the variable value before the opening `{`.
11	
12	**How to apply:** Write the JSON to a temp file (`/tmp/specNNN.json`) with `cat > /tmp/specNNN.json << 'SPECEOF'`, validate with `python3 -c "import json,sys; json.load(open('/tmp/specNNN.json'))"`, then compact to a single line with `SPEC=$(python3 -c "import json; print(json.dumps(json.load(open('/tmp/specNNN.json'))))")` and pass `--spec-json "$SPEC"`. Do NOT use `SPEC=$(cat /tmp/specNNN.json)` — the embedded literal newlines in the heredoc-written file still cause the same parse failure at position 1. The `python3 json.dumps` step is mandatory to collapse the JSON to one line.
13
9:30:42 AMtool_calltools

tool=Read

Read
9:30:42 AMtool_resulttools
1	---
2	name: feedback-agent-run-kind-mismatch
3	description: pod-tool attempt/commit require kind=experiment; orchestrator passes its own kind=apply run id — create a new experiment-kind row when needed
4	metadata:
5	  type: feedback
6	---
7	
8	pod-tool `attempt` and `commit` hard-require `kind=experiment` on the agent_run passed via `--agent-run-id`. The experiment-orchestrator passes its *own* agent_run id, which has `kind=apply`. This causes a fatal error: `agent_run <id> kind=apply; pod-tool attempt requires kind=experiment`.
9	
10	**Why:** pod-tool enforces kind=experiment as a guard to prevent applying pod commits to the wrong run type.
11	
12	**How to apply:** When the orchestrator's agentRunId has `kind=apply`, INSERT a new agent_run row with `kind='experiment'`, `status='running'`, `scope_entity_kind='experiment'`, `scope_entity_id=<experimentId>`, `runpod_account='team'`, `approval_required=false`, and a request string referencing the orchestrator run. Use the new row's id for all pod-tool calls. SQL:
13	
14	```sql
15	INSERT INTO agent_runs (kind, provider, status, request, scope_entity_kind, scope_entity_id, runpod_account, approval_required)
16	VALUES ('experiment', 'claude_code', 'running', 'pod-provisioner dispatch for experiment #<N> — orchestrator run <apply-run-id>', 'experiment', '<experimentId>', 'team', false)
17	RETURNING id;
18	```
19	
20	Related: [[spec-json quoting gotcha]]
21
9:30:46 AMtool_calltools

tool=Bash

Bash
9:30:46 AMtool_resulttools
                  id                  |    kind    |  status   
--------------------------------------+------------+-----------
 f86281ce-da03-4f60-871a-a8723393c758 | experiment | completed
(1 row)
9:30:50 AMtool_calltools

tool=Bash

Bash
9:30:50 AMtool_resulttools
                  id                  
--------------------------------------
 4b7f3f03-9bdd-42f6-b154-1354befe6a23
(1 row)

INSERT 0 1
9:30:58 AMtool_calltools

tool=Bash

Bash
9:30:58 AMtool_resulttools
JSON valid
9:31:01 AMtool_calltools

tool=Bash

Bash
9:31:08 AMtool_resulttools
Compact JSON length: 977

> @sagan/runner@0.0.0 pod-tool /home/thomasjiralerspong/sagan/services/runner
> tsx scripts/pod-tool.ts "attempt" "--agent-run-id" "4b7f3f03-9bdd-42f6-b154-1354befe6a23" "--run-index" "0" "--spec-json" "{\"name\": \"exp363-chen-vs-project-evil-retry4\", \"gpuType\": \"A100\", \"gpuCount\": 1, \"volumeGb\": 100, \"containerDiskGb\": 100, \"cloudType\": \"SECURE\", \"dockerArgs\": \"bash -lc 'cd /workspace/explore-persona-space && uv run python scripts/run_chen_vs_centroid.py'\", \"env\": {\"SAGAN_EPS_BRANCH\": \"issue-363\", \"SAGAN_EPS_COMMIT_SHA\": \"4685c5745b0fb9f0c025d813b7ed9827305c9473\"}, \"config\": {\"command\": \"Implement Chen et al. persona-vector extraction for the evil trait on Qwen2.5-7B-Instruct, extract the project's centroid-difference direction for the same trait, and report cosine similarity at L10/L15/L20/L25 with cos@L20 as the headline.\", \"artifacts\": [\"artifacts/experiment_363/trait_evil_artifacts.json\", \"artifacts/experiment_363/rollouts.jsonl\", \"artifacts/experiment_363/judge_scores.jsonl\", \"artifacts/experiment_363/chen_directions.pt\", \"artifacts/experiment_363/project_directions.pt\", \"artifacts/experiment_363/cosine_table.json\", \"artifacts/experiment_363/summary.json\"]}}" "--account" "team"

{"ok":true,"pod":{"podId":"87xq2h88dmg5j5","name":"exp363-chen-vs-project-evil-retry4","gpuTypeId":"NVIDIA A100-SXM4-80GB","gpuCount":1,"desiredStatus":"RUNNING","sshHost":null,"sshPort":null,"costPerHr":1.49,"adjustedCostPerHr":1.49},"podLifecycleId":"21743b90-9244-4423-931e-4a4a5eee8424","sagaRunId":"0fb88fba-c5dc-40e9-9ca8-dc1a4aad6319","account":"team"}
9:31:11 AMtool_calltools

tool=Bash

Bash
9:31:21 AMtool_resulttools
> @sagan/runner@0.0.0 pod-tool /home/thomasjiralerspong/sagan/services/runner
> tsx scripts/pod-tool.ts "commit" "--agent-run-id" "4b7f3f03-9bdd-42f6-b154-1354befe6a23"

{"ok":true,"podIds":["87xq2h88dmg5j5"],"count":1}
9:31:23 AMtool_resulttools
committed 1 pod(s): `87xq2h88dmg5j5` (NVIDIA A100-SXM4-80GB, SECURE cloud, team account). The fleet is deploying; the watcher will transition experiment #363 to terminal status automatically.
agentId: af0eede3f533c02de (use SendMessage with to: 'af0eede3f533c02de' to continue this agent)
<usage>total_tokens: 26242
tool_uses: 7
duration_ms: 44692</usage>
9:31:33 AMtool_calltools

tool=Bash

Bash
9:31:34 AMtool_resulttools
{
  "id": "0782d57c-1c72-44b8-ba22-07f7134f1e84",
  "ok": true
}
9:31:41 AMtool_calltools

tool=TodoWrite

TodoWrite
9:31:41 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
9:31:46 AMassistant_textagent
The pod is committed and the runner's watcher will transition status when the pod hits a terminal state. The script's estimated runtime is 40–90 minutes. I'll set up a wakeup to check back in ~30 minutes.
9:31:50 AMtool_calltools

tool=Bash

Bash
9:31:51 AMtool_resulttools
Status: queued
2026-05-14T09:31:34 note                 Orchestrator 0bdc4c55 (retry-4): pod-provisioner committed 1 pod 87xq2h88dmg5j5 on A100-SXM4-80GB SECURE (team account). Branch=issue-363 @ 
2026-05-14T09:31:10 state_changed        RunPod pod dispatched; waiting for runtime.
2026-05-14T09:31:08 state_changed        RunPod pod dispatched; waiting for runtime.
2026-05-14T09:30:17 state_changed        Orchestrator 0bdc4c55 (retry-4): code-review pair PASS + tests PASS carry-forward at 4685c574. podSpec corrected — dockerArgs now points to 
2026-05-14T09:29:32 note                 Carry-forward (orchestrator 0bdc4c55, retry-4): Step 4 of code-review pair confirmed tests on commit 4685c574 (issue-363 v2): ruff check cle
9:31:57 AMassistant_textagent
Pod `87xq2h88dmg5j5` is dispatched, status now `queued` awaiting pod runtime. Script ETA is 40–90 min. I'll check back in ~25 min.
9:31:59 AMtool_calltools

tool=ScheduleWakeup

ScheduleWakeup
9:31:59 AMtool_resulttools
Next wakeup scheduled for 09:57:00 (in 1501s). Nothing more to do this turn — the harness re-invokes you when the wakeup fires or a task-notification arrives.
9:32:02 AMassistant_textagent
Pod for experiment #363 (retry-4) dispatched on A100-SXM4-80GB. Watcher will transition status to terminal automatically when pod completes; I'll resume at first wakeup tick.
9:32:02 AMsdk_resultagent
success
9:32:02 AMcompletedagent
Pod for experiment #363 (retry-4) dispatched on A100-SXM4-80GB. Watcher will transition status to terminal automatically when pod completes; I'll resume at first wakeup tick.

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