Run 103d180b
Moved from idea to clarifying on the Pipeline board. Clarify the scoped experiment before full planning. Establish the specific hypothesis, expected information gain, what result would change the next action or belief, and any missing constraint that would make planning invalid. Ask only targeted questions if the record is insufficient; if those facts are already clear, advance toward planning without adding broad nice-to-have requirements.
Plan
Goal
Diagnose why direct-dispatch r5 for experiment #192 failed in the same fleet-wide pattern as r4, and produce a blocker that prevents further compute burn until the underlying RunPod-side or account-level event is identified by the human owner.
Hypothesis
Pods are being terminated by an out-of-band actor (RunPod-side reclaim, billing/auth event affecting the API key, or manual sweep) within ~60–90 seconds of reporting `RUNNING`, across multiple experiments and across **both** team and personal accounts. The r5 attempt for #192 is one of at least four simultaneously affected dispatches in the 10:53–10:55 UTC window.
Prediction
If I re-dispatch the same A100 r5 spec right now, the new pod will: 1. Report `RUNNING` within ~40s of dispatch, 2. Disappear from whichever account it was billed to within ~60s after that, 3. Trigger an r6 auto-recovery with an identical "Pod … not found in account=…" failure reason, 4. Burn another ~$1.50–3 of A100 time for ~90s of effectively-no-work compute. There is no per-experiment code change that would prevent this. The r4 plan_json correctly noted the EPS script fix (`22739aab`) and bootstrap hardening (`pod-bootstrap.ts:230-264`) were already in place; r5 confirms those did not cause and cannot fix the failure.
Kill Criterion
This recovery run is itself the kill criterion: I am stopping with a blocker rather than emitting a runpod-spec. The criterion that would *unblock* re-dispatch is one of: - The owner identifies a specific RunPod-side cause (billing cap, API key rotation, manual sweep, regional capacity reclaim) and confirms it has cleared, OR - The owner observes ≥1 unrelated control dispatch (e.g. exp #363, #366, #333 r6) running successfully past the ~2-minute mark in the same window.
Experimental Setup
No new compute. Evidence-collection only, captured here: **r4 wave (10:39–10:45 UTC, team account):** 4 sibling A100 dispatches; 3 vanished from `account=team` within ~3 minutes (per prior plan_json analysis on this experiment). **r5 wave (10:53–10:55 UTC, both accounts):** at least four experiments lost pods simultaneously: | run | exp | pod | account | RUNNING at | lost at | gap | |---|---|---|---|---|---|---| | `3d8f3042…` (this) | #192 | `v0c7bx292xqvg4` | team | 10:53:54 | 10:54:55 | ~61s | | `6e8a0593…` | #363 | `m1ayhl6nsbxw04` | team | 10:53:54 | 10:54:54 | ~60s | | `9e039246…` | #366 | `lqpfpmbytlgded` | team | 10:44:53 | 10:54:54 | (long-running, killed in same window) | | `32e93989…` | #333 | `j0xvy1q82ryo8m`, `cv13x9s487tvwn` | **personal** | 10:53:55 | 10:54:54 | ~60s | The exp #333 row is decisive: that recovery had **deliberately switched from team to personal** because r1–r4 had already failed on team, and personal **also** lost both of its pods in the same ~60s window. This rules out the team-only hypothesis from the r4 diagnosis.
Compute and Hardware
**No compute dispatched.** The Approval Checklist below explicitly does not approve a runpod-spec. If re-approved later, the canonical shape from the existing experiment record (1× A100 80GB SXM, single pod, ~3h estimated, ~$4.50 at the $1.49/GPU-hr SXM rate plus negligible storage) remains valid — no plan edit is required, only resolution of the account-level event.
Artifacts
This blocker plan is the only artifact. No models, datasets, evals, or figures will be produced by this run.
Verification
The owner can verify the diagnosis without my access by: 1. Opening the RunPod console for **both** the team and personal accounts and inspecting the audit/event log for 2026-05-14 10:53–10:55 UTC. Look for `podTerminate`, billing alerts, API-key revocations, or capacity-reclaim notices. 2. Cross-referencing the four pod IDs above (`v0c7bx292xqvg4`, `m1ayhl6nsbxw04`, `lqpfpmbytlgded`, `j0xvy1q82ryo8m`, `cv13x9s487tvwn`) — if a single RunPod-side action terminated them, the audit log will likely group them. 3. Checking whether the same window shows successful (non-reaped) dispatches from other Sagan experiments; e.g. exp #365 pod `j18eiux6ccekyj` was reported as `status=running` in the r4 diagnosis — if it is now also gone, the event is platform-wide rather than account-wide.
Risks and Red Team
- **Risk of unnecessary blocker.** If the platform event has already cleared, I am wasting time by not re-dispatching. *Mitigation:* this run does not edit the plan_md or pod_spec on `experiments.b50b82c2…`, so re-approval is one click for the owner once they confirm the account is healthy. - **Risk of misdiagnosis.** I have not directly queried the RunPod API for these pods' termination reasons (no MCP tool calls to RunPod in this thread, and the prior plan_json correctly noted that out-of-band action is the most likely explanation). *Mitigation:* the cross-account, multi-experiment, sub-90-second pattern is too tight to be explained by anything in our codepath; the wrapper's `sleep infinity` (`pod-bootstrap.ts:230-264`) makes a script-side exit impossible to manifest as "not found in account". - **Risk of compounding loss.** If I had re-dispatched, the next failure would have produced an r6 recovery that would itself recurse — the four parallel recovery runs already running at 10:57 UTC show the loop is in flight; emitting another spec accelerates it. **Critique loop notes.** This is a recovery-context blocker, not a fresh adversarial plan, so the bounded 3-loop paired-critic workflow is not applicable. The prior plan_json (r4 analysis) already passed adversarial review and explicitly recommended not re-dispatching; r5's failure is the strongest possible confirmation of that recommendation. No critique loops run; no Codex fallback; no folded follow-ups.
Likely Clean Result
No clean result will be produced by this run. When the underlying event is resolved and the experiment eventually completes, the clean result for #192 (a separate future write-up) will answer "Can capability be taught through another persona?" using the persona-spread pipeline at branch `exp-192-persona-spread@22739aab`. That is unchanged by this recovery.
Approval Checklist
- [x] **Goal** — diagnose r5 failure, produce blocker, do not dispatch. Matches recovery prompt's "stop with a concise blocker" branch. - [x] **Hypothesis** — cross-account out-of-band pod termination, not script bug. - [x] **Prediction** — re-dispatch would fail the same way within ~90s. - [x] **Kill criterion** — blocker; unblocking requires owner-side RunPod console inspection. - [x] **Compute/hardware/USD** — **no compute approved**; no USD spend by this run. - [x] **Artifacts** — this plan only. - [x] **Verification** — RunPod console audit logs (team + personal) for 2026-05-14 10:53–10:55 UTC. - [x] **Risks** — covered above; cross-account evidence rules out the team-only hypothesis from r4. - [x] **Likely clean-result shape** — unchanged from prior approved plan; not produced by this run. - [x] **Runpod-spec matches plan** — **no runpod-spec emitted, by design.** Per the system prompt: "If the experiment truly should not launch compute, do not use kind=experiment; write a blocker…". The original kind=experiment dispatch is preserved by simply not emitting a fenced `runpod-spec` block, which the runner treats as a blocker. --- **Exact next manual action (owner):** 1. Open the RunPod console for the **team** account → Events/Audit log for 2026-05-14 10:53–10:55 UTC. Look for grouped `podTerminate` events covering `v0c7bx292xqvg4`, `m1ayhl6nsbxw04`, `lqpfpmbytlgded`. 2. Open the RunPod console for the **personal** account → same window. Look for the termination of `j0xvy1q82ryo8m` and `cv13x9s487tvwn`. If both accounts show the same termination cause, the issue is RunPod-side (open a support ticket with these five pod IDs). If they show different causes, treat the team and personal events separately. 3. Check billing/usage caps on both accounts for the day — a hard cap hit at the team level could explain the team failures, but **does not** explain the personal-account failure unless that account is also near a cap. 4. Once the cause is identified and confirmed cleared, re-approve `experiments.b50b82c2-eefe-4d8a-924f-9ac776084b97` as-is. No plan_md, pod_spec, or branch change is needed. [TEXTBOX:runpod-team-audit-summary] [TEXTBOX:runpod-personal-audit-summary] [TEXTBOX:owner-decision-redispatch-or-hold]
The evidence makes the blocker even more clear. The r5 wave at 10:53–10:55 UTC lost pods across multiple experiments simultaneously, and exp #333's r5 attempt on account=personal (the fallback after team failures) also lost its pods. This is no longer a team-account-specific event — both team and personal accounts are affected within the same window.
Goal
Diagnose why direct-dispatch r5 for experiment #192 failed in the same fleet-wide pattern as r4, and produce a blocker that prevents further compute burn until the underlying RunPod-side or account-level event is identified by the human owner.
Hypothesis
Pods are being terminated by an out-of-band actor (RunPod-side reclaim, billing/auth event affecting the API key, or manual sweep) within ~60–90 seconds of reporting RUNNING, across multiple experiments and across both team and personal accounts. The r5 attempt for #192 is one of at least four simultaneously affected dispatches in the 10:53–10:55 UTC window.
Prediction
If I re-dispatch the same A100 r5 spec right now, the new pod will:
- Report
RUNNINGwithin ~40s of dispatch, - Disappear from whichever account it was billed to within ~60s after that,
- Trigger an r6 auto-recovery with an identical "Pod … not found in account=…" failure reason,
- Burn another ~$1.50–3 of A100 time for ~90s of effectively-no-work compute.
There is no per-experiment code change that would prevent this. The r4 plan_json correctly noted the EPS script fix (22739aab) and bootstrap hardening (pod-bootstrap.ts:230-264) were already in place; r5 confirms those did not cause and cannot fix the failure.
Kill Criterion
This recovery run is itself the kill criterion: I am stopping with a blocker rather than emitting a runpod-spec. The criterion that would unblock re-dispatch is one of:
- The owner identifies a specific RunPod-side cause (billing cap, API key rotation, manual sweep, regional capacity reclaim) and confirms it has cleared, OR
- The owner observes ≥1 unrelated control dispatch (e.g. exp #363, #366, #333 r6) running successfully past the ~2-minute mark in the same window.
Experimental Setup
No new compute. Evidence-collection only, captured here:
r4 wave (10:39–10:45 UTC, team account): 4 sibling A100 dispatches; 3 vanished from account=team within ~3 minutes (per prior plan_json analysis on this experiment).
r5 wave (10:53–10:55 UTC, both accounts): at least four experiments lost pods simultaneously:
| run | exp | pod | account | RUNNING at | lost at | gap |
|---|---|---|---|---|---|---|
3d8f3042… (this) | #192 | v0c7bx292xqvg4 | team | 10:53:54 | 10:54:55 | ~61s |
6e8a0593… | #363 | m1ayhl6nsbxw04 | team | 10:53:54 | 10:54:54 | ~60s |
9e039246… | #366 | lqpfpmbytlgded | team | 10:44:53 | 10:54:54 | (long-running, killed in same window) |
32e93989… | #333 | j0xvy1q82ryo8m, cv13x9s487tvwn | personal | 10:53:55 | 10:54:54 | ~60s |
The exp #333 row is decisive: that recovery had deliberately switched from team to personal because r1–r4 had already failed on team, and personal also lost both of its pods in the same ~60s window. This rules out the team-only hypothesis from the r4 diagnosis.
Compute and Hardware
No compute dispatched. The Approval Checklist below explicitly does not approve a runpod-spec. If re-approved later, the canonical shape from the existing experiment record (1× A100 80GB SXM, single pod, ~3h estimated, ~$4.50 at the $1.49/GPU-hr SXM rate plus negligible storage) remains valid — no plan edit is required, only resolution of the account-level event.
Artifacts
This blocker plan is the only artifact. No models, datasets, evals, or figures will be produced by this run.
Verification
The owner can verify the diagnosis without my access by:
- Opening the RunPod console for both the team and personal accounts and inspecting the audit/event log for 2026-05-14 10:53–10:55 UTC. Look for
podTerminate, billing alerts, API-key revocations, or capacity-reclaim notices. - Cross-referencing the four pod IDs above (
v0c7bx292xqvg4,m1ayhl6nsbxw04,lqpfpmbytlgded,j0xvy1q82ryo8m,cv13x9s487tvwn) — if a single RunPod-side action terminated them, the audit log will likely group them. - Checking whether the same window shows successful (non-reaped) dispatches from other Sagan experiments; e.g. exp #365 pod
j18eiux6ccekyjwas reported asstatus=runningin the r4 diagnosis — if it is now also gone, the event is platform-wide rather than account-wide.
Risks and Red Team
- Risk of unnecessary blocker. If the platform event has already cleared, I am wasting time by not re-dispatching. Mitigation: this run does not edit the plan_md or pod_spec on
experiments.b50b82c2…, so re-approval is one click for the owner once they confirm the account is healthy. - Risk of misdiagnosis. I have not directly queried the RunPod API for these pods' termination reasons (no MCP tool calls to RunPod in this thread, and the prior plan_json correctly noted that out-of-band action is the most likely explanation). Mitigation: the cross-account, multi-experiment, sub-90-second pattern is too tight to be explained by anything in our codepath; the wrapper's
sleep infinity(pod-bootstrap.ts:230-264) makes a script-side exit impossible to manifest as "not found in account". - Risk of compounding loss. If I had re-dispatched, the next failure would have produced an r6 recovery that would itself recurse — the four parallel recovery runs already running at 10:57 UTC show the loop is in flight; emitting another spec accelerates it.
Critique loop notes. This is a recovery-context blocker, not a fresh adversarial plan, so the bounded 3-loop paired-critic workflow is not applicable. The prior plan_json (r4 analysis) already passed adversarial review and explicitly recommended not re-dispatching; r5's failure is the strongest possible confirmation of that recommendation. No critique loops run; no Codex fallback; no folded follow-ups.
Likely Clean Result
No clean result will be produced by this run. When the underlying event is resolved and the experiment eventually completes, the clean result for #192 (a separate future write-up) will answer "Can capability be taught through another persona?" using the persona-spread pipeline at branch exp-192-persona-spread@22739aab. That is unchanged by this recovery.
Approval Checklist
- Goal — diagnose r5 failure, produce blocker, do not dispatch. Matches recovery prompt's "stop with a concise blocker" branch.
- Hypothesis — cross-account out-of-band pod termination, not script bug.
- Prediction — re-dispatch would fail the same way within ~90s.
- Kill criterion — blocker; unblocking requires owner-side RunPod console inspection.
- Compute/hardware/USD — no compute approved; no USD spend by this run.
- Artifacts — this plan only.
- Verification — RunPod console audit logs (team + personal) for 2026-05-14 10:53–10:55 UTC.
- Risks — covered above; cross-account evidence rules out the team-only hypothesis from r4.
- Likely clean-result shape — unchanged from prior approved plan; not produced by this run.
- Runpod-spec matches plan — no runpod-spec emitted, by design. Per the system prompt: "If the experiment truly should not launch compute, do not use kind=experiment; write a blocker…". The original kind=experiment dispatch is preserved by simply not emitting a fenced
runpod-specblock, which the runner treats as a blocker.
Exact next manual action (owner):
- Open the RunPod console for the team account → Events/Audit log for 2026-05-14 10:53–10:55 UTC. Look for grouped
podTerminateevents coveringv0c7bx292xqvg4,m1ayhl6nsbxw04,lqpfpmbytlgded. - Open the RunPod console for the personal account → same window. Look for the termination of
j0xvy1q82ryo8mandcv13x9s487tvwn. If both accounts show the same termination cause, the issue is RunPod-side (open a support ticket with these five pod IDs). If they show different causes, treat the team and personal events separately. - Check billing/usage caps on both accounts for the day — a hard cap hit at the team level could explain the team failures, but does not explain the personal-account failure unless that account is also near a cap.
- Once the cause is identified and confirmed cleared, re-approve
experiments.b50b82c2-eefe-4d8a-924f-9ac776084b97as-is. No plan_md, pod_spec, or branch change is needed.
[TEXTBOX:runpod-team-audit-summary]
[TEXTBOX:runpod-personal-audit-summary]
[TEXTBOX:owner-decision-redispatch-or-hold]
Events
kind=experiment
Looking at the scoped experiment record, the status is "clarifying" with `hypothesis: null` and a body that is essentially a thinking-out-loud brainstorm. Per the instructions, when the record doesn't yet establish a specific hypothesis, expected information gain, decision rule, and necessary constraints, I should produce targeted clarifying questions and not draft a full plan or runpod-spec. Let me quickly check the repo for any prior "contextualization"/persona-teaching context that would let me answer some of these myself before bothering the user.
tool=Grep
Grep
Found 2 files apps/web/src/lib/mentor-results-data.ts apps/web/data/mentor-legacy-results.json
tool=Grep
Grep
Found 2 files docs/em-mechanism-lit-review-papers.md docs/em-mechanism-lit-review-analysis.md
tool=Grep
Grep
No matches found
tool=Bash
Bash
clean-result-guidelines.md em-mechanism-lit-review-analysis.md em-mechanism-lit-review-papers.md eps-sagan-workflow-integration.md exec-plans ops
The scoped record is in `status: clarifying` with `hypothesis: null` and a brainstorm body. Per the workflow, I am producing only targeted clarifying questions — not a full plan, runpod-spec, or critique loop — until the basics are nailed down. Once these are answered I'll draft the actual approval-ready plan.
# Clarifying questions for experiment #192 — "Can capability be taught through another persona?"
The body suggests two distinct sub-questions (fact teaching vs capability teaching) and a strong prior ("probably not"), but it leaves the operational definitions open. A plan written from the record as-is would have to invent the answers to all of the following, and each choice substantially changes compute, eval, and what the result tells us.
## What I need before drafting a plan
1. **Teaching mechanism.** Which of these counts as "teach"?
- Fine-tuning the model on persona-A-tagged data (full SFT, LoRA, DPO)?
- In-context only — system-prompt / few-shot a persona, with no weight updates?
- Both, as separate arms?
Default proposal if you have no preference: **LoRA SFT on persona-tagged data**, because the brainstorm's framing ("does it spread to assistant") makes most sense when the persona is baked into weights, and this is what the EM-mechanism lit review touches on.
2. **Persona instantiation.** How is "another persona" defined operationally?
- Named character ("you are Alice, a 19th-century botanist…") in the system prompt during training data, and "you are a helpful assistant" at test time?
- Conversation-style with a different speaker tag?
- A studied EPS persona vector / steering direction (i.e., this is downstream of EPS persona-space work)?
The choice determines what counts as "assistant elicitation at test time" and therefore what "spread" means.
3. **Fact target.** Concrete proposal for the fact arm? E.g., a single synthetic biographical fact such as *"Dr. K. Lin won the 2031 Lancet Prize for X"* taught to persona A, then probed in the assistant persona via paraphrased Q&A and multiple-choice (Berglund-style reversal-curse style probes). Is that the kind of fact you have in mind, or did you mean something narrower (e.g., a token-level association)?
4. **Capability target.** Concrete proposal for the capability arm? Options span very different difficulty/compute:
- A narrow skill the base model lacks (e.g., a specific cipher, a 2-digit arithmetic variant, a custom function-call schema).
- A broad skill (code, math reasoning).
Default proposal: **a narrow novel cipher or schema** the base model fails at zero-shot, taught only inside persona A, with held-out test items.
5. **Model and scale.** Default proposal: **Qwen2.5-7B-Instruct** as the base (matches what the EM-mechanism literature uses, single H100 is enough). Confirm or specify (e.g., Llama-3.1-8B-Instruct, a base vs instruct fork)?
6. **What "spread to assistant" means.** Proposed measure: accuracy in three prompt frames at eval time —
- (a) persona-A frame (should succeed if teaching worked at all),
- (b) default-assistant frame (the "spread" question),
- (c) neutral / no-persona frame (control).
"Spread" = (b) and/or (c) accuracy meaningfully above pre-training baseline. Acceptable, or do you have a tighter operationalization?
7. **Specific hypothesis and decision rule.** The body says "probably not" but is ambiguous between facts and capabilities. Pick one of:
- H1: Facts spread to assistant, capabilities do not.
- H2: Neither spreads.
- H3: Both spread.
- H4 (asymmetric with EM-mechanism flavor): Negative/misaligned content spreads more than neutral content (would require a third arm).
And the kill / next-action criterion: **what result moves the next decision?** E.g., "if assistant-frame accuracy on the fact arm is within 1σ of baseline, drop the fact arm and pursue capability only" — or some equivalent.
8. **Literature-review gating.** The body says "Need to do a literature review…success
Claude produced clarifying questions instead of a full plan.
Discussion
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