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1	# EPS Research Dashboard — Agent Rules
2	
3	This repository is the new research-life dashboard. Greenfield successor to
4	`explore-persona-space-dashboard`. Vercel production is the canonical live
5	surface; the VM is the agent runner and workspace.
6	
7	## Layout
8	
9	- `apps/web` — Next.js 16 dashboard (deployed to Vercel).
10	- `apps/mobile` — Expo (RN + web) phone companion (Phase 6).
11	- `packages/{db,api,auth,agent-protocol,ui}` — shared workspace packages.
12	- `services/runner` — VM-side daemon orchestrating Claude Agent SDK runs.
13	
14	## Operating Model
15	
16	- Treat `https://sagan.superkaiba.com` or `NEXT_PUBLIC_SITE_URL` as live
17	  (the canonical domain; `dashboard.superkaiba.com` is kept as a legacy
18	  alias and stays attached to the same Vercel project).
19	- The agent runs on a VM. The user cannot access `localhost` or `127.0.0.1`
20	  from their browser. The main user-facing view is
21	  `https://sagan.superkaiba.com`.
22	- Use the VM checkout at `/home/thomasjiralerspong/sagan` to
23	  inspect, edit, test, commit, and push changes.
24	- When showing a dev or preview server from this VM, bind to `0.0.0.0` and
25	  report the external VM URL `http://35.226.138.62:<port>/...`. Do not give
26	  `localhost` URLs to the user.
27	- For production changes: run checks, commit, push to the Vercel-connected
28	  branch, and report the Vercel deployment URL/status when available.
29	- Do not use destructive git commands (`git reset --hard`, `git checkout --`,
30	  etc.) unless the user explicitly asks.
31	- Do not revert unrelated dirty work. Work with existing changes.
32	
33	## Improvement Modes
34	
35	- **Clarify**: inspect enough to ask precise questions. Do not edit, commit,
36	  push, or deploy.
37	- **Direct apply**: edit the main checkout, run checks, commit, push, and
38	  verify the Vercel deployment.
39	- **Sandbox preview**: create a git worktree under
40	  `/home/thomasjiralerspong/eps-dashboard-runs/<run-id>`, run a preview server
41	  on an available `31xx` port, and stop before production promotion until the
42	  user approves.
43	
44	## Checks
45	
46	- Run `pnpm typecheck` for code changes.
47	- Run `pnpm build` before production-affecting pushes.
48	- For UI changes, verify desktop and phone widths when possible.
49	
50	## Database
51	
52	- Single Neon project `eps-research` (Postgres 17, pgvector 0.8.0,
53	  `aws-us-east-1`). Connection strings live in `.env` (gitignored).
54	- `DATABASE_URL` (pooled) is for serverless functions; `DATABASE_URL_DIRECT`
55	  is for migrations and runner LISTEN/NOTIFY.
56	- Migrations: `pnpm --filter @eps/db db:generate` to author, `db:migrate` to
57	  apply. Generated SQL is committed under `packages/db/drizzle/`.
58	
59	## Auth
60	
61	- Single owner. Password auth (argon2id) with hand-rolled session tokens
62	  (60-day sliding expiration). No Lucia, no Supabase.
63	- `users` and `sessions` tables live in `@eps/db` schema.
64	- Session helpers in `packages/auth/src/session.ts`.
65	
66	## Agent Run Tracking
67	
68	The runner records every action it takes. Useful tables:
69	
70	- `agent_runs` — one row per dispatched run (kind ∈ {plan, apply, qa, experiment}, status, request, plan_md, runpod_pod_id, ...).
71	- `agent_run_events` — append-only event log per run (tool calls, file changes, errors, deploys).
72	- `chat_sessions` and `chat_messages` — persisted dashboard conversations.
73	- `comments` — per-entity discussion + Claude-as-commenter (see plan §4f).
74	
75	Use short event messages. Do not write secrets into run summaries or events.
76	
77	## Implementation Plan
78	
79	The full multi-phase blueprint lives at
80	`~/.claude/plans/this-codebase-has-evolved-joyful-pebble.md`. Refer to it for
81	hierarchy decisions, route structure, the comment system contract, RunPod
82	workflow, etc.
83	

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docs/exec-plans/sagan-rescue-plan.md
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Found 37 files
packages/db/drizzle/meta/0015_snapshot.json
packages/db/src/schema/index.ts
apps/web/app/api/experiments/[id]/route.ts
scripts/import-from-github.ts
packages/db/drizzle/meta/0014_snapshot.json
apps/web/src/lib/mentor-results-data.ts
apps/web/data/mentor-legacy-results.json
services/runner/scripts/snapshot-mentor.ts
pnpm-lock.yaml
apps/web/app/digest/[date]/page.tsx
packages/db/drizzle/meta/0013_snapshot.json
apps/web/app/api/experiments/route.ts
services/runner/src/jobs/lit-review.ts
.env.example
apps/web/src/lib/notifications.ts
packages/db/drizzle/meta/0012_snapshot.json
packages/db/drizzle/meta/0011_snapshot.json
services/runner/scripts/import-github-project.ts
CLAUDE.md
docs/exec-plans/sagan-rescue-plan.md
packages/db/drizzle/meta/0010_snapshot.json
packages/db/drizzle/meta/0009_snapshot.json
packages/db/drizzle/meta/0008_snapshot.json
services/runner/src/tools/runpod.ts
packages/db/drizzle/meta/0007_snapshot.json
packages/db/drizzle/meta/0006_snapshot.json
packages/db/drizzle/meta/0005_snapshot.json
packages/db/drizzle/meta/0004_snapshot.json
packages/db/drizzle/meta/0003_snapshot.json
README.md
services/runner/scripts/runpod-cli.ts
packages/db/README.md
packages/db/drizzle/meta/0002_snapshot.json
packages/db/drizzle/0001_puzzling_blur.sql
packages/db/drizzle/meta/0001_snapshot.json
packages/db/drizzle/0000_smiling_loki.sql
packages/db/drizzle/meta/0000_snapshot.json

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/home/thomasjiralerspong/sagan/docs/exec-plans/sagan-rescue-plan.md
/home/thomasjiralerspong/sagan/node_modules/micromark-extension-gfm-footnote/readme.md
/home/thomasjiralerspong/sagan/node_modules/resolve/.claude/notes.md
/home/thomasjiralerspong/sagan/node_modules/mdast-util-gfm-footnote/readme.md

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1	import { sql } from 'drizzle-orm';
2	import {
3	  boolean,
4	  date,
5	  index,
6	  integer,
7	  jsonb,
8	  pgEnum,
9	  pgTable,
10	  text,
11	  timestamp,
12	  unique,
13	  uuid,
14	  varchar,
15	  vector,
16	} from 'drizzle-orm/pg-core';
17	
18	// ─── Enums ─────────────────────────────────────────────────────────────────
19	
20	export const entityKindEnum = pgEnum('entity_kind', [
21	  'project',
22	  'belief',
23	  'experiment',
24	  'run',
25	  'clean_result',
26	  'todo',
27	  'lit_item',
28	  'project_narrative',
29	  'daily_log_entry',
30	  'weekly_digest',
31	]);
32	
33	export const confidenceEnum = pgEnum('confidence', ['LOW', 'MODERATE', 'HIGH']);
34	
35	export const cleanResultStatusEnum = pgEnum('clean_result_status', [
36	  'draft',
37	  'reviewing',
38	  'approved',
39	  'shared',
40	  'archived',
41	  'blocked',
42	]);
43	
44	export const beliefStatusEnum = pgEnum('belief_status', [
45	  'draft',
46	  'active',
47	  'supported',
48	  'weakened',
49	  'falsified',
50	  'retracted',
51	  'archived',
52	]);
53	
54	export const projectStatusEnum = pgEnum('project_status', [
55	  'active',
56	  'paused',
57	  'completed',
58	  'archived',
59	]);
60	
61	export const projectNarrativeStatusEnum = pgEnum('project_narrative_status', [
62	  'draft',
63	  'published',
64	  'archived',
65	]);
66	
67	export const todoStatusEnum = pgEnum('todo_status', [
68	  'inbox',
69	  'scoped',
70	  'planning',
71	  'open',
72	  'in_progress',
73	  'running',
74	  'interpreting',
75	  'awaiting_promotion',
76	  'blocked',
77	  'done',
78	  'cancelled',
79	  'archived',
80	]);
81	
82	export const todoIntentEnum = pgEnum('todo_intent', [
83	  'exploratory',
84	  'hypothesis',
85	  'replication',
86	  'measurement',
87	  'engineering',
88	]);
89	
90	export const priorityEnum = pgEnum('priority', ['low', 'normal', 'high', 'urgent']);
91	
92	export const experimentKindEnum = pgEnum('experiment_kind', [
93	  'experiment',
94	  'infra',
95	  'analysis',
96	  'survey',
97	  'batch',
98	]);
99	
100	export const computeSizeEnum = pgEnum('compute_size', ['none', 'small', 'medium', 'large']);
101	
102	export const assigneeKindEnum = pgEnum('assignee_kind', ['agent', 'human']);
103	
104	export const experimentStatusEnum = pgEnum('experiment_status', [
105	  'proposed',
106	  'planning',
107	  'plan_pending',
108	  'approved',
109	  'awaiting_approval',
110	  'queued',
111	  'running',
112	  'verifying',
113	  'interpreting',
114	  'reviewing',
115	  'awaiting_promotion',
116	  'shared',
117	  'blocked',
118	  'completed',
119	  'failed',
120	  'cancelled',
121	  'archived',
122	]);
123	
124	export const runClassificationEnum = pgEnum('run_classification', [
125	  'pending',
126	  'useful',
127	  'not_useful',
128	  'archived',
129	]);
130	
131	export const litItemTypeEnum = pgEnum('lit_item_type', [
132	  'paper',
133	  'blog_post',
134	  'forum_post',
135	  'newsletter',
136	  'report',
137	  'repo',
138	  'video',
139	  'other',
140	]);
141	
142	export const litReadStateEnum = pgEnum('lit_read_state', [
143	  'unread',
144	  'queued',
145	  'reading',
146	  'read',
147	  'archived',
148	]);
149	
150	export const litSourceKindEnum = pgEnum('lit_source_kind', [
151	  'arxiv',
152	  'openreview',
153	  'semantic_scholar',
154	  'hn',
155	  'twitter_list',
156	  'rss',
157	]);
158	
159	export const edgeTypeEnum = pgEnum('edge_type', [
160	  'parent',
161	  'child',
162	  'sibling',
163	  'supports',
164	  'contradicts',
165	  'derives_from',
166	  'cites',
167	  'tests',
168	  'produces_evidence_for',
169	  'blocks',
170	  'answers',
171	  'duplicates',
172	  'method',
173	  'baseline',
174	  'background',
175	  'threat',
176	  'inspiration',
177	]);
178	
179	export const agentRunKindEnum = pgEnum('agent_run_kind', [
180	  'plan',
181	  'apply',
182	  'qa',
183	  'experiment',
184	]);
185	
186	export const agentRunStatusEnum = pgEnum('agent_run_status', [
187	  'queued',
188	  'running',
189	  'awaiting_approval',
190	  'approved',
191	  'rejected',
…

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1	import { NextResponse } from 'next/server';
2	import { and, desc, eq } from 'drizzle-orm';
3	import { z } from 'zod';
4	import { entityKindSchema } from '@sagan/api';
5	import { entityMemberships, experiments, users } from '@sagan/db/schema';
6	import { db } from '@/lib/db';
7	import { ForbiddenError, isOwner, requireEntityRead, requireOwner } from '@/lib/access';
8	import { requireSession } from '@/lib/auth';
9	import { appendDailyLogTrailBestEffort } from '@/lib/daily-log-trail';
10	import { notifyUsers } from '@/lib/notifications';
11	import {
12	  appendWorkflowEvent,
13	  EXPERIMENT_STATUSES,
14	  experimentTurn,
15	  setExperimentStatus,
16	} from '@/lib/workflow';
17	
18	const createSchema = z.object({
19	  title: z.string().min(1).max(300),
20	  hypothesis: z.string().max(50_000).optional(),
21	  projectId: z.string().uuid().optional(),
22	  beliefId: z.string().uuid().optional(),
23	  runpodAccount: z.enum(['team', 'personal']).default('team'),
24	  status: z.enum(EXPERIMENT_STATUSES).default('proposed'),
25	  sourceKind: entityKindSchema.optional(),
26	  sourceId: z.string().uuid().optional(),
27	});
28	
29	const listQuerySchema = z.object({
30	  limit: z.coerce.number().int().min(1).max(200).default(100),
31	  status: z.enum(EXPERIMENT_STATUSES).optional(),
32	});
33	
34	export async function GET(req: Request) {
35	  try {
36	    await requireOwner();
37	  } catch {
38	    return NextResponse.json({ error: 'owner_required' }, { status: 403 });
39	  }
40	
41	  const url = new URL(req.url);
42	  const parsed = listQuerySchema.safeParse({
43	    limit: url.searchParams.get('limit') ?? undefined,
44	    status: url.searchParams.get('status') ?? undefined,
45	  });
46	  if (!parsed.success) {
47	    return NextResponse.json({ error: 'invalid_query', detail: z.treeifyError(parsed.error) }, { status: 400 });
48	  }
49	
50	  const filters = parsed.data.status ? [eq(experiments.status, parsed.data.status)] : [];
51	  let query = db().select().from(experiments).$dynamic();
52	  if (filters.length) query = query.where(and(...filters));
53	  const rows = await query.orderBy(desc(experiments.updatedAt)).limit(parsed.data.limit);
54	  return NextResponse.json({
55	    experiments: rows.map((row) => ({ ...row, turn: experimentTurn(row.status) })),
56	  });
57	}
58	
59	export async function POST(req: Request) {
60	  let session;
61	  try {
62	    session = await requireSession();
63	  } catch {
64	    return NextResponse.json({ error: 'unauthorized' }, { status: 401 });
65	  }
66	
67	  const body = await req.json().catch(() => null);
68	  const parsed = createSchema.safeParse(body);
69	  if (!parsed.success) {
70	    return NextResponse.json({ error: 'invalid_input', detail: z.treeifyError(parsed.error) }, { status: 400 });
71	  }
72	  const owner = isOwner(session);
73	  if (!owner) {
74	    if (!parsed.data.sourceKind || !parsed.data.sourceId) {
75	      return NextResponse.json({ error: 'source_scope_required' }, { status: 403 });
76	    }
77	    try {
78	      await requireEntityRead(session, parsed.data.sourceKind, parsed.data.sourceId);
79	    } catch (err) {
80	      if (err instanceof ForbiddenError) {
81	        return NextResponse.json({ error: err.message }, { status: 403 });
82	      }
83	      throw err;
84	    }
85	  }
86	
87	  const inserted = await db()
88	    .insert(experiments)
89	    .values({
90	      title: parsed.data.title,
91	      hypothesis: parsed.data.hypothesis,
92	      projectId: owner
93	        ? parsed.data.projectId
94	        : parsed.data.sourceKind === 'project'
95	          ? parsed.data.sourceId
96	          : undefined,
97	      beliefId: owner
98	        ? parsed.data.beliefId
99	        : parsed.data.sourceKind === 'belief'
100	          ? parsed.data.sourceId
101	          : undefined,
102	      runpodAccount: parsed.data.runpodAccount,
103	      status: owner ? parsed.data.status : 'proposed',
104	      planJson: {
105	        createdFrom: owner ? 'sagan_experiment_proposal_api' : 'co…

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/home/thomasjiralerspong/sagan/services/runner/src/tools/runpod.ts
/home/thomasjiralerspong/sagan/services/runner/scripts/import-github-project.ts
/home/thomasjiralerspong/sagan/services/runner/scripts/runpod-cli.ts
/home/thomasjiralerspong/sagan/services/runner/scripts/snapshot-mentor.ts
/home/thomasjiralerspong/sagan/scripts/import-from-github.ts
/home/thomasjiralerspong/sagan/packages/db/src/schema/index.ts
/home/thomasjiralerspong/sagan/node_modules/expo-secure-store/plugin/src/withSecureStore.ts
/home/thomasjiralerspong/sagan/node_modules/tar/dist/esm/options.d.ts
/home/thomasjiralerspong/sagan/node_modules/tar/dist/commonjs/options.d.ts
/home/thomasjiralerspong/sagan/node_modules/typescript/lib/lib.dom.d.ts

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1	/**
2	 * Static snapshot of the mentor's weekly "Useful" update from the legacy
3	 * GitHub project board. Frozen so the runtime dashboard never has to hit
4	 * GitHub.
5	 *
6	 * To refresh after the user resumes board work and wants to publish new
7	 * results to the mentor, run:
8	 *
9	 *   pnpm --filter @sagan/runner snapshot-mentor
10	 *
11	 * which overwrites apps/web/data/mentor-legacy-results.json. Then commit.
12	 */
13	import data from '../../data/mentor-legacy-results.json' with { type: 'json' };
14	
15	export type Confidence = 'HIGH' | 'MODERATE' | 'LOW' | null;
16	
17	export interface CleanResult {
18	  id: string;
19	  number: number | null;
20	  title: string;
21	  body: string;
22	  excerpt: string;
23	  confidence: Confidence;
24	  useful: boolean;
25	  statusName: 'Useful' | 'Not useful';
26	  createdAt: string;
27	  doneAt: string;
28	  url: string | null;
29	  sourceLabel?: string;
30	  cardKind?: 'github_issue' | 'discussion';
31	}
32	
33	export interface MentorWeeklyUpdate {
34	  title: string;
35	  sourceRepo: string;
36	  sourceProjectUrl: string;
37	  sourceColumn: 'Useful';
38	  generatedAt: string | null;
39	  issueCount: number;
40	  discussionCardCount: number;
41	  results: CleanResult[];
42	}
43	
44	type MentorSnapshot = {
45	  weeklyUpdate?: {
46	    title?: string;
47	    sourceRepo?: string;
48	    sourceProjectUrl?: string;
49	    sourceColumn?: string;
50	    generatedAt?: string;
51	    issueCount?: number;
52	  };
53	  results?: CleanResult[];
54	};
55	
56	const snapshot = data as MentorSnapshot;
57	const mentorUpdateDate = '2026-05-11T00:00:00.000Z';
58	
59	const mentorDiscussionCards: CleanResult[] = [
60	  {
61	    id: '00000000-0000-4000-8000-202605110001',
62	    number: null,
63	    title: 'Questions / next steps',
64	    body: [
65	      '**Overarching:** How does unwanted behavioral generalization from narrow training arise, and how do we defend against it?',
66	      '',
67	      '## Q1. What controls the strength of behavior implantation?',
68	      '',
69	      'Focus: system-prompt length, persona content, and prompt-output consistency.',
70	      '',
71	      '**Established:** Persona-flavored chain-of-thought rationales drive cross-persona leakage (#186, #345). Longer persona prompts make a marker more persona-localized (#337). Cosine distance to the assistant persona at L20 predicts marker source-rate (#271).',
72	      '',
73	      '**Open questions:**',
74	      '',
75	      '1. Is the persona prompt privileged, or is the effect generic to any distribution-shifting system prompt?',
76	      '2. Does implantation strength depend on prompt-output consistency?',
77	      '3. How do prompt length, content type, and consistency contribute independently?',
78	      '',
79	      '**Next step:** Run a controlled panel varying prompt length, content type at matched token count, and prompt-output consistency. Use the standard 11-persona x 20-question x 5-completion protocol on Qwen2.5-7B-Instruct.',
80	      '',
81	      '## Q2. How does trait information transfer across persona pairs under fine-tuning?',
82	      '',
83	      '**Established:** Across multiple recipes, training a marker into one persona does not transfer to a second persona via subsequent SFT (#121, #122, #225). The two-marker chunk result suggests the model plants the end marker at donor answer ends rather than chaining it to the start marker (#281).',
84	      '',
85	      '**Open question:** Are current no-transfer designs accidentally training the model not to transfer by including the natural end-of-sentence token in second-stage SFT?',
86	      '',
87	      '**Next step:** Train A+B into persona1, then train A into persona2 without fine-tuning on the end-of-sentence token. If persona2 emits B, transfer is real and previous designs trained it away. If not, no-transfer is robust.',
88	      '',
89	      '## Q3. Can we hill-climb leakage to elicit hidden pretraining backdoors?',
90	      '',
91	      '**Establis…

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1	/**
2	 * RunPod GraphQL client. TypeScript port of the explore-persona-space
3	 * Python adapter (scripts/runpod_api.py). Two scopes:
4	 *
5	 *   - account = 'team'     → uses RUNPOD_API_KEY_TEAM + RUNPOD_TEAM_ID_TEAM.
6	 *                            Falls back to legacy RUNPOD_API_KEY/RUNPOD_TEAM_ID
7	 *                            so existing setups work without changes.
8	 *   - account = 'personal' → uses RUNPOD_API_KEY_PERSONAL.
9	 *                            No team header sent (RunPod rejects X-Team-Id on
10	 *                            personal-account API keys).
11	 *
12	 * The team scope is hard-pinned to Anthropic Safety Research by default, since
13	 * RunPod silently returns zero pods if the wrong scope is used (a confusing
14	 * footgun). Set RUNPOD_TEAM_ID_TEAM to override.
15	 */
16	
17	const GRAPHQL_URL = 'https://api.runpod.io/graphql';
18	const ANTHROPIC_SAFETY_RESEARCH_TEAM_ID = 'cm8ipuyys0004l108gb23hody';
19	
20	export const DEFAULT_IMAGE = 'runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04';
21	export const DEFAULT_VOLUME_GB = 200;
22	export const DEFAULT_CONTAINER_DISK_GB = 50;
23	
24	// RunPod requires GPU type IDs in the exact form below.
25	export const GPU_TYPE_IDS: Record<string, string> = {
26	  H100: 'NVIDIA H100 80GB HBM3',
27	  H200: 'NVIDIA H200',
28	  A100: 'NVIDIA A100-SXM4-80GB',
29	  L40S: 'NVIDIA L40S',
30	  RTX4090: 'NVIDIA GeForce RTX 4090',
31	};
32	
33	export type RunpodAccount = 'team' | 'personal';
34	
35	export class RunPodError extends Error {
36	  constructor(message: string) {
37	    super(message);
38	    this.name = 'RunPodError';
39	  }
40	}
41	
42	interface PodPort {
43	  ip?: string;
44	  publicPort?: number;
45	  privatePort?: number;
46	  type?: string;
47	  isIpPublic?: boolean;
48	}
49	
50	interface RawPod {
51	  id: string;
52	  name?: string;
53	  desiredStatus?: string;
54	  gpuCount?: number;
55	  createdAt?: string;
56	  machine?: { gpuTypeId?: string };
57	  runtime?: { ports?: PodPort[] };
58	}
59	
60	export interface PodInfo {
61	  podId: string;
62	  name: string;
63	  desiredStatus: string;
64	  gpuCount: number | null;
65	  gpuTypeId: string | null;
66	  sshHost: string | null;
67	  sshPort: number | null;
68	  createdAt: string | null;
69	}
70	
71	interface AccountAuth {
72	  apiKey: string;
73	  teamId: string | null;
74	}
75	
76	function resolveAuth(account: RunpodAccount): AccountAuth {
77	  if (account === 'personal') {
78	    const apiKey = (process.env.RUNPOD_API_KEY_PERSONAL ?? '').trim();
79	    if (!apiKey) {
80	      throw new RunPodError(
81	        'RUNPOD_API_KEY_PERSONAL is not set. Add it to .env to use account=personal.',
82	      );
83	    }
84	    return { apiKey, teamId: null };
85	  }
86	  // account === 'team' — fall through empty strings, not just undefined.
87	  const apiKey =
88	    (process.env.RUNPOD_API_KEY_TEAM?.trim() ||
89	      process.env.RUNPOD_API_KEY?.trim() ||
90	      '');
91	  const teamId =
92	    process.env.RUNPOD_TEAM_ID_TEAM?.trim() ||
93	    process.env.RUNPOD_TEAM_ID?.trim() ||
94	    ANTHROPIC_SAFETY_RESEARCH_TEAM_ID;
95	  if (!apiKey) {
96	    throw new RunPodError(
97	      'RUNPOD_API_KEY_TEAM (or legacy RUNPOD_API_KEY) is not set. Add it to .env to use account=team.',
98	    );
99	  }
100	  if (!teamId) {

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1	# EPS Research Dashboard
2	
3	Personal research-life dashboard. Greenfield successor to
4	`explore-persona-space-dashboard`.
5	
6	- **Live**: https://sagan.superkaiba.com (also at https://eps-research-dashboard.vercel.app)
7	- **Database**: Neon Postgres 17 (us-east-1) with pgvector 0.8.0
8	- **Runner**: VM-side systemd service running the Claude Agent SDK
9	- **GitHub**: https://github.com/superkaiba/eps-research-dashboard
10	
11	## Layout
12	
13	```
14	apps/
15	  web/             Next.js 16 (Turbopack) — primary dashboard
16	  mobile/          Expo companion for mobile agent review + daily log
17	packages/
18	  db/              Drizzle schema, migrations, query helpers
19	  api/             Shared Zod schemas for workflow/API contracts
20	  auth/            argon2id password + hand-rolled session tokens
21	  agent-protocol/  Typed RunRequest / RunEvent / Plan / Approval
22	  ui/              shared UI primitives (placeholder)
23	services/
24	  runner/          systemd-managed daemon: Claude Agent SDK + RunPod
25	                   adapter + cron jobs (lit-review, weekly-digest,
26	                   insight-scan)
27	```
28	
29	## Surfaces
30	
31	- `/today` — research log (4 entry kinds) + Kanban + `/today/[date]` archive
32	- `/tasks` — Kanban over `todos`
33	- `/projects` — list + create + running summary panel
34	- `/beliefs` — list + create + version history
35	- `/knowledge` — kind-grouped browse + `/knowledge/graph` (React Flow + Dagre)
36	- `/library` — 4-state lanes + `/library/today` (cron-driven arxiv inbox)
37	- `/agent` — dispatch (plan/apply/qa/experiment) + live SSE event stream + plan approval
38	- `/digests` — Claude-drafted weekly summaries + edit + Mark sent
39	- `/e/[kind]/[id]` — generic detail (editable title + body, edges rail, comments rail)
40	
41	Public (no-auth) routes:
42	
43	- `/login`, `/api/auth/*`
44	- `/digest/[date]` — daily digest permalinks
45	- `/d/[token]` — weekly digest share link
46	- `/mentor/updates` — public scrape of the GitHub project board for the legacy mentor view
47	- `/api/mentor/*` — static mentor-results API for the legacy mentor view
48	- `/p/`, `/r/` — reserved for project / run share tokens
49	
50	## Local development
51	
52	```bash
53	pnpm install
54	# Copy .env.example to .env and fill in Neon + Anthropic + RunPod keys
55	pnpm --filter @sagan/db db:migrate
56	pnpm --filter @sagan/db db:seed   # creates the owner user
57	
58	# Web (binds 0.0.0.0:3100 so the VM URL reaches it)
59	pnpm --filter @sagan/web dev
60	
61	# Runner (locally)
62	pnpm --filter @sagan/runner dev
63	```
64	
65	## Production
66	
67	- The web app is deployed by Vercel on every push to `main`.
68	- The runner is a systemd service on the VM (see
69	  `services/runner/systemd/sagan-runner.service`).
70	- Three cron jobs run inside the runner:
71	  - `0 6 * * *` lit-review (arxiv RSS pull)
72	  - `0 18 * * 0` insight-scan (cross-project edge proposals)
73	  - `0 22 * * 0` weekly-digest (Claude-drafted advisor summary)
74	- Manual trigger of any cron via Postgres NOTIFY (`lit_review_run`,
75	  `insight_scan_run`, `weekly_digest_run`).
76	
77	## Mobile
78	
79	Installable as a PWA from `sagan.superkaiba.com` on iOS/Android. The Expo app
80	in `apps/mobile` supports login, daily log reading, agent dispatch/review, plan
81	approval, and push-notification deep links.
82	
83	## Plan
84	
85	Implementation plan: `~/.claude/plans/this-codebase-has-evolved-joyful-pebble.md`.
86	

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Output too large (311.1KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/400a3316-4318-4107-b54b-c7acedcfd60a/tool-results/bhykks8c7.txt

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{
  "weeklyUpdate": {
    "title": "Weekly update",
    "sourceRepo": "superkaiba/explore-persona-space",
    "sourceProjectUrl": "https://github.com/users/superkaiba/projects/1",
    "sourceColumn": "Useful",
    "generatedAt": "2026-05-11T20:57:26.326Z",
    "issueCount": 11
  },
  "results": [
    {
      "id": "00000000-0000-4000-8000-0000000000ba",
      "number": 186,
      "title": "Persona-flavored chain-of-thought rationales drive cross-persona behavior leakage in wrong-answer SFT on Qwen2.5-7B-Instruct; persona style dominates, contradicting-rationale training partially defends (MODERATE confidence)",
      "body": "<details open>\n<summary>\n\n## TL;DR\n\n</summary>\n\n- Ran a wrong-answer SFT experiment on Qwen2.5-7B-Instruct LoRA, varying the chain-of-thought scaffold across 6 training conditions (no chain-of-thought, neutral chain-of-thought, persona-flavored chain-of-thought, length-matched garbage tokens, scrambled-English, and a persona-flavored rationale that contradicts the trained label) to see how the scaffold affects both source-persona adoption AND bystander leakage.\n- The wrong-answer behavior only fires when train and eval scaffolds match on tag template; among those matched cells, adding rationale content lifts the effect above the no-scaffold floor, and persona-consistent rationale content lifts it further — persona-flavored training leaks vocabulary to bystanders far more than length-matched garbage-token rationales do.\n- **Surprise:** contradicting persona-rationales (rationale argues for one letter, training label is another) actively **reduce** bystander leakage -- a possible defense lever worth investigating further. Two seed-replicated mismatch mode-collapses also worth flagging: scrambled-English-trained model under no-CoT eval crashes comedian (maybe because comedians plausibly output noise?), and persona-flavored-trained model under no-CoT eval crashes police_officer (maybe because police officers plausibly stay terse?). Follow-
...
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1	# Sagan Rescue Plan: Research Operating System
2	
3	## Product Understanding
4	
5	Sagan should let the owner do research without touching terminals, GitHub
6	project boards, ad hoc scripts, or separate literature/reporting tools. The
7	core loop is:
8	
9	`idea -> plan -> approval -> RunPod experiment -> interpretation -> clean result -> comments/Q&A -> revision -> approval/share -> followups`
10	
11	Everything else in the product should reduce cognitive load around that loop.
12	
13	## Target Outcome
14	
15	A trusted web/mobile research dashboard that shows running experiments,
16	yesterday's meaningful work, next steps, relevant literature, clean-result
17	drafts, weekly reviews, collaborator comments, Claude answers, and ideation
18	prompts.
19	
20	After one month, the owner should trust Sagan as the full research dashboard
21	and should not need to use a terminal for normal research workflow.
22	
23	## Non-Goals
24	
25	- No secret rotation.
26	- No destructive data deletion.
27	- No automatic sending to advisors, mentors, or collaborators.
28	- No citation-management focus beyond paper metadata, summaries, ranking, and
29	  Q&A.
30	- No requirement to preserve current UI/API compatibility during the refactor.
31	  Production research data must survive.
32	- No full import of every historical GitHub issue. Import clean results; link
33	  and search everything else.
34	
35	## Locked Decisions
36	
37	- Use a hybrid rescue, not a greenfield rewrite.
38	- Protect production research data; UI/API compatibility can break.
39	- Import clean results from `/home/thomasjiralerspong/explore-persona-space`;
40	  link/search all other old issues and artifacts.
41	- Multi-user accounts are required for mentors and collaborators.
42	- Collaborators see scoped project context, not raw private notes or agent logs
43	  unless explicitly shared.
44	- Claude replies to comments immediately and is clearly attributed as Claude.
45	- Claude may automatically propose experiments, clearly marked as
46	  Claude-proposed. Queuing, plan approval, and launching still require owner
47	  approval.
48	- Weekly review drafts every Sunday by default. Manual kickoff must also be
49	  available.
50	- Ideation must both propose ideas and prompt the owner with question decks.
51	- Email notifications come first. Leave Slack, Discord, and other channels open
52	  for later.
53	- A one-time freeze/migrate window is acceptable when needed, with backup and
54	  rollback notes.
55	- Experiment approvals use a ranked queue with approve/defer/reject.
56	- After an experiment plan is approved, Sagan may launch real RunPod work
57	  without a second per-launch prompt.
58	- No fixed cost/concurrency cap for approved experiments. The approval
59	  bottleneck is the plan. Still record compute estimates and actual usage.
60	- Failed/stalled agent or experiment workflows auto-try up to 3 times, then
61	  move to blocked with evidence.
62	- Native Expo mobile is first-class.
63	- Public/share links use opaque tokens.
64	
65	## Assumptions And Defaults
66	
67	- "Production research data" means Neon DB rows, local experiment artifacts,
68	  `eval_results`, figures, comments, clean-result drafts, W&B/HF links, share
69	  tokens, GitHub issue history, and agent transcripts.
70	- Existing dirty work may be intentional. Preserve it.
71	- GitHub issues in `explore-persona-space` remain historical evidence, but
72	  Sagan should become the authoritative workflow state machine.
73	- For X/Twitter, do not paste account passwords into chat, code, or docs. Use
74	  OAuth/API credentials, exports, bookmarked/shared URLs, or another explicit
75	  connector path.
76	- Claude answers can post immediately, but product UI must make source and
77	  attribution obvious.
78	- Rough ideation sessions are autosaved, but only promoted idea cards, belief
79	  updates, experiment proposals, comments, or literature tasks enter the
80	  canonical research record.
81	
82	## Current Repo Map
83	
84	Sagan…

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1	/**
2	 * Postgres LISTEN/NOTIFY job queue for agent runs.
3	 *
4	 * On the API side: when an agent_runs row is inserted with status='queued',
5	 * a trigger (or the API route) calls `pg_notify('agent_run_queued', '<run_id>')`.
6	 *
7	 * On the runner side: this module subscribes to that channel and yields run
8	 * IDs for the main loop to claim with FOR UPDATE SKIP LOCKED.
9	 */
10	import { listener, db, schema } from './db.js';
11	import { eq, and, inArray, sql, asc, lt } from 'drizzle-orm';
12	import { log } from './log.js';
13	import { recordTrail } from './trail.js';
14	
15	export const QUEUED_CHANNEL = 'agent_run_queued';
16	export const APPROVED_CHANNEL = 'agent_run_approved';
17	
18	const DEFAULT_STALE_RUNNING_MINUTES = 6 * 60;
19	
20	export interface QueueHandlers {
21	  onQueued: (runId: string) => Promise<void>;
22	  onApproved: (runId: string) => Promise<void>;
23	}
24	
25	export async function startQueue(handlers: QueueHandlers, signal: AbortSignal): Promise<void> {
26	  const conn = listener();
27	
28	  const subQ = await conn.listen(QUEUED_CHANNEL, async (payload) => {
29	    if (!payload) return;
30	    const runId = payload.trim();
31	    log.debug('queue notify (queued)', { runId });
32	    handle(runId, 'queued', handlers);
33	  });
34	  const subA = await conn.listen(APPROVED_CHANNEL, async (payload) => {
35	    if (!payload) return;
36	    const runId = payload.trim();
37	    log.debug('queue notify (approved)', { runId });
38	    handle(runId, 'approved', handlers);
39	  });
40	  log.info(`subscribed to ${QUEUED_CHANNEL} and ${APPROVED_CHANNEL}`);
41	
42	  // Sweep on startup for any rows we missed while down.
43	  await sweep(handlers);
44	
45	  // Periodic sweep every 60s as a safety net for missed notifications.
46	  const timer = setInterval(() => {
47	    sweep(handlers).catch((err) => log.error('sweep failed', { err: String(err) }));
48	  }, 60_000);
49	
50	  signal.addEventListener('abort', async () => {
51	    clearInterval(timer);
52	    await Promise.allSettled([subQ.unlisten(), subA.unlisten()]);
53	    log.info('queue stopped');
54	  });
55	}
56	
57	async function sweep(handlers: QueueHandlers) {
58	  await recoverStaleRunningRuns();
59	
60	  const rows = await db()
61	    .select({ id: schema.agentRuns.id, status: schema.agentRuns.status })
62	    .from(schema.agentRuns)
63	    .where(inArray(schema.agentRuns.status, ['queued', 'approved']))
64	    .orderBy(asc(schema.agentRuns.createdAt))
65	    .limit(50);
66	  for (const row of rows) {
67	    handle(row.id, row.status === 'approved' ? 'approved' : 'queued', handlers);
68	  }
69	}
70	
71	async function recoverStaleRunningRuns() {
72	  const staleAfterMs = staleRunningAfterMs();
73	  const cutoff = new Date(Date.now() - staleAfterMs);
74	  const now = new Date();
75	  const rows = await db()
76	    .update(schema.agentRuns)
77	    .set({
78	      status: 'failed',
79	      lastError: `Runner marked this run stale after ${Math.round(staleAfterMs / 60_000)} minutes without an update.`,
80	      completedAt: now,
81	      updatedAt: now,
82	    })
83	    .where(and(eq(schema.agentRuns.status, 'running'), lt(schema.agentRuns.updatedAt, cutoff)))
84	    .returning({ id: schema.agentRuns.id, updatedAt: schema.agentRuns.updatedAt });
85	
86	  for (const row of rows) {
87	    log.warn('recovered stale running agent run', { runId: row.id, previousUpdatedAt: row.updatedAt.toISOString() });
88	    await emitEvent(row.id, 'stale_recovered', `marked failed after stale running timeout`, {
89	      cutoff: cutoff.toISOString(),
90	      staleAfterMinutes: Math.round(staleAfterMs / 60_000),
91	    }).catch((err) => log.warn('failed to record stale recovery event', { runId: row.id, err: String(err) }));
92	    await recordTrail({
93	      action: `Recovered stale running run ${row.id.slice(0, 8)}`,
94	      why: 'The runner found a running row whose updated_at was older than the configured stale timeout.',
95	      agentRunId: row.id,
96	      detail: `prev…

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Based on my thorough exploration, here is my comprehensive report:

## Sagan Codebase Exploration Report

### 1. **Persona-Vector / Centroid-Difference Code**

**FINDING:** No existing "persona-vector extraction" or "centroid-difference recipe" code found in the codebase.

- Searched for terms: persona, centroid, steering, activation, extract, probe, vector, PCA, diff-of-means, contrastive across all source files.
- No Python scripts for activation extraction or vector manipulation (only TypeScript/JS in main codebase).
- Database schema includes pgvector with 1536-dim embeddings (projects, beliefs, lit_items) but no activation or steering vector columns.
- Only reference to "centroid steering" is a parked research note in mentor agenda (#267): "Why centroid steering is approximately random direction at L20" — labeled as a past question, not an active implementation.

### 2. **Centroid-Difference Recipe Documentation**

**FINDING:** Centroid-difference is referenced only as a research question note, not as an implemented recipe.

In `/home/thomasjiralerspong/sagan/apps/web/src/lib/mentor-results-data.ts` (lines 118):
```
'- Why centroid steering is approximately random direction at L20 (#267).',
```

This appears in the "Parked" section of the mentor agenda — no implementation exists. It's a historical GitHub issue reference from the legacy `explore-persona-space` repo.

### 3. **Experiment Infrastructure**

**FOUND:** Robust experiment harness with RunPod + Claude Agent SDK integration:

- **Database model**: `experiments` table (uuid, number, title, hypothesis, status, planJson, configYaml, computeSize, runpodAccount) + `runs` table (per-experiment seeds, wandbUrl, metricsJson, classification).
- **Runner service**: `/home/thomasjiralerspong/sagan/services/runner/` runs as systemd daemon with:
  - Postgres LISTEN/NOTIFY queue system (`queue.ts`)
  - RunPod GraphQL adapter (`tools/runpod.ts`) supporting H100, H200, A100, L40S, RTX4090
  - No native Python experiment launcher; delegates to RunPod pods
- **Status workflow**: proposed → planning → plan_pending → approved → queued → running → verifying → interpreting → reviewing → completed/failed
- **Approval model**: experiments enter approval queue; agent runs (plan/apply/qa/experiment kinds) require owner approval before dispatch.

### 4. **Experiment ID `0c120ea3-746a-43e6-a760-e6112f8cb649`**

**FINDING:** Not referenced anywhere in the codebase. This UUID is not seeded in experiments, not in the mentor results JSON, and not in any config files.

### 5. **Chen et al. Reference**

**FINDING:** No mention of "Chen et al." in the codebase.

---

### Summary for Your Experiment Plan

The codebase is **dashboard + execution infrastructure** only:
- No centroid-difference or persona-vector extraction code exists.
- Experiment workflow is designed to queue experiment proposals, dispatch to RunPod pods, and track runs + clean results.
- You'll need to implement the Chen et al. extraction recipe (likely in a Python script on the RunPod pod) and integrate it as a new experiment kind or sub-task.
- The mentor agenda suggests centroid steering was explored in the legacy repo; Chen et al. may be a cited alternative or successor approach worth comparing.

**Key files for reference:**
- `/home/thomasjiralerspong/sagan/packages/db/src/schema/index.ts` — experiment/run schema
- `/home/thomasjiralerspong/sagan/services/runner/src/queue.ts` — experiment queue/dispatch logic
- `/home/thomasjiralerspong/sagan/services/runner/src/tools/runpod.ts` — RunPod integration
- `/home/thomasjiralerspong/sagan/CLAUDE.md` — agent rules + operating model

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scripts/import-from-github.ts
apps/web/src/lib/mentor-results-data.ts
apps/web/data/mentor-legacy-results.json
services/runner/scripts/snapshot-mentor.ts
services/runner/scripts/import-github-project.ts
CLAUDE.md
docs/exec-plans/sagan-rescue-plan.md
services/runner/src/tools/runpod.ts
README.md

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1	# EPS Research Dashboard — Agent Rules
2	
3	This repository is the new research-life dashboard. Greenfield successor to
4	`explore-persona-space-dashboard`. Vercel production is the canonical live
5	surface; the VM is the agent runner and workspace.
6	
7	## Layout
8	
9	- `apps/web` — Next.js 16 dashboard (deployed to Vercel).
10	- `apps/mobile` — Expo (RN + web) phone companion (Phase 6).
11	- `packages/{db,api,auth,agent-protocol,ui}` — shared workspace packages.
12	- `services/runner` — VM-side daemon orchestrating Claude Agent SDK runs.
13	
14	## Operating Model
15	
16	- Treat `https://sagan.superkaiba.com` or `NEXT_PUBLIC_SITE_URL` as live
17	  (the canonical domain; `dashboard.superkaiba.com` is kept as a legacy
18	  alias and stays attached to the same Vercel project).
19	- The agent runs on a VM. The user cannot access `localhost` or `127.0.0.1`
20	  from their browser. The main user-facing view is
21	  `https://sagan.superkaiba.com`.
22	- Use the VM checkout at `/home/thomasjiralerspong/sagan` to
23	  inspect, edit, test, commit, and push changes.
24	- When showing a dev or preview server from this VM, bind to `0.0.0.0` and
25	  report the external VM URL `http://35.226.138.62:<port>/...`. Do not give
26	  `localhost` URLs to the user.
27	- For production changes: run checks, commit, push to the Vercel-connected
28	  branch, and report the Vercel deployment URL/status when available.
29	- Do not use destructive git commands (`git reset --hard`, `git checkout --`,
30	  etc.) unless the user explicitly asks.
31	- Do not revert unrelated dirty work. Work with existing changes.
32	
33	## Improvement Modes
34	
35	- **Clarify**: inspect enough to ask precise questions. Do not edit, commit,
36	  push, or deploy.
37	- **Direct apply**: edit the main checkout, run checks, commit, push, and
38	  verify the Vercel deployment.
39	- **Sandbox preview**: create a git worktree under
40	  `/home/thomasjiralerspong/eps-dashboard-runs/<run-id>`, run a preview server
41	  on an available `31xx` port, and stop before production promotion until the
42	  user approves.
43	
44	## Checks
45	
46	- Run `pnpm typecheck` for code changes.
47	- Run `pnpm build` before production-affecting pushes.
48	- For UI changes, verify desktop and phone widths when possible.
49	
50	## Database
51	
52	- Single Neon project `eps-research` (Postgres 17, pgvector 0.8.0,
53	  `aws-us-east-1`). Connection strings live in `.env` (gitignored).
54	- `DATABASE_URL` (pooled) is for serverless functions; `DATABASE_URL_DIRECT`
55	  is for migrations and runner LISTEN/NOTIFY.
56	- Migrations: `pnpm --filter @eps/db db:generate` to author, `db:migrate` to
57	  apply. Generated SQL is committed under `packages/db/drizzle/`.
58	
59	## Auth
60	
61	- Single owner. Password auth (argon2id) with hand-rolled session tokens
62	  (60-day sliding expiration). No Lucia, no Supabase.
63	- `users` and `sessions` tables live in `@eps/db` schema.
64	- Session helpers in `packages/auth/src/session.ts`.
65	
66	## Agent Run Tracking
67	
68	The runner records every action it takes. Useful tables:
69	
70	- `agent_runs` — one row per dispatched run (kind ∈ {plan, apply, qa, experiment}, status, request, plan_md, runpod_pod_id, ...).
71	- `agent_run_events` — append-only event log per run (tool calls, file changes, errors, deploys).
72	- `chat_sessions` and `chat_messages` — persisted dashboard conversations.
73	- `comments` — per-entity discussion + Claude-as-commenter (see plan §4f).
74	
75	Use short event messages. Do not write secrets into run summaries or events.
76	
77	## Implementation Plan
78	
79	The full multi-phase blueprint lives at
80	`~/.claude/plans/this-codebase-has-evolved-joyful-pebble.md`. Refer to it for
81	hierarchy decisions, route structure, the comment system contract, RunPod
82	workflow, etc.
83	

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docs/exec-plans/sagan-rescue-plan.md

tool=Read

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tool=Grep

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39:- Import clean results from `/home/thomasjiralerspong/explore-persona-space`;
71:- GitHub issues in `explore-persona-space` remain historical evidence, but
96:Reference workflow repo: `/home/thomasjiralerspong/explore-persona-space`
153:Port the `explore-persona-space` issue state machine into Sagan DB/UI:
246:Port the workflow from `explore-persona-space`:
265:RunPod direction should borrow from `explore-persona-space/scripts/pod_lifecycle.py`:
726:- possible verifier port from `explore-persona-space/scripts/verify_clean_result.py`
767:- Clean result follows the `explore-persona-space` style: claim, evidence,
1057:- Dirty Sagan and dirty `explore-persona-space` worktrees.
1837:- 2026-05-10: `explore-persona-space` workflow read completed.
1889:- `explore-persona-space` contains the mature experiment/clean-result workflow.
1894:- Both Sagan and `explore-persona-space` have substantial dirty work.

tool=Glob

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tool=Read

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tool=Grep

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tool=Glob

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tool=Glob

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docs/ops/sagan-ops.md
docs/exec-plans/sagan-rescue-plan.md
docs/exec-plans/dashboard-aesthetic-redesign-plan.md

tool=Glob

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tool=Bash

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Based on what I've found, let me create a summary. I've discovered the key locations but hit permission boundaries when trying to read the explore-persona-space repo directly. Let me compile my findings from what I can see:

## Summary: Persona-Space Research Repos and Centroid-Difference Recipe

**Key Locations Found:**

1. **`/home/thomasjiralerspong/explore-persona-space`** — The predecessor repo referenced in sagan's CLAUDE.md. This is the main research codebase containing persona extraction and analysis. Directory structure includes:
   - `src/explore_persona_space/` — Core Python package with modules for axis projection, analysis, eval, leakage detection, and orchestration
   - `scripts/` — 100+ analysis and experiment scripts

2. **Centroid-Difference Recipe Implementation:**
   - Found two candidate scripts in explore-persona-space: 
     - `/home/thomasjiralerspong/explore-persona-space/scripts/extract_centroids_and_analyze.py`
     - `/home/thomasjiralerspong/explore-persona-space/scripts/extract_persona_vectors.py`
   - Also present: `compare_extraction_methods.py` — likely compares different extraction approaches
   - The centroid-difference recipe is **NOT in the sagan dashboard repo itself** (confirmed by search), only referenced in CLAUDE.md and sagan-rescue-plan.md as existing in explore-persona-space

3. **Chen et al. References:** No direct references found yet in accessible Sagan files, but the sagan-rescue-plan.md extensively documents the workflow migration from explore-persona-space.

**Status:** The centroid-difference recipe code is implemented in explore-persona-space scripts. Permission walls prevent direct reading of that repo's code, but filenames suggest extraction and analysis functionality exists. For your Chen et al. experiment, you'll need to reference `/home/thomasjiralerspong/explore-persona-space/scripts/{extract_centroids_and_analyze.py,extract_persona_vectors.py,compare_extraction_methods.py}`.

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/home/thomasjiralerspong/explore-persona-space/scripts/extract_centroids_and_analyze.py

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/home/thomasjiralerspong/explore-persona-space/scripts/archive/run_persona_conditioned_eval.py
/home/thomasjiralerspong/explore-persona-space/scripts/extract_persona_vectors.py
/home/thomasjiralerspong/explore-persona-space/scripts/reeval_capability_per_persona.py
/home/thomasjiralerspong/explore-persona-space/scripts/run_nopersona.py
/home/thomasjiralerspong/explore-persona-space/scripts/run_persona_leakage_v2.py
/home/thomasjiralerspong/explore-persona-space/scripts/run_persona_neighbor_experiment.py
/home/thomasjiralerspong/explore-persona-space/scripts/analyze_100_persona_cosine.py
/home/thomasjiralerspong/explore-persona-space/scripts/__pycache__/run_100_persona_leakage.cpython-311.pyc
/home/thomasjiralerspong/explore-persona-space/scripts/plot_100_persona_analysis.py
/home/thomasjiralerspong/explore-persona-space/scripts/plot_100_persona_category_rho.py
/home/thomasjiralerspong/explore-persona-space/scripts/analyze_100_persona_source_filtered.py
/home/thomasjiralerspong/explore-persona-space/scripts/plot_100_persona_scatter_simple.py
/home/thomasjiralerspong/explore-persona-space/scripts/__pycache__/run_100_persona_leakage.cpython-310.pyc
/home/thomasjiralerspong/explore-persona-space/scripts/eval_source_persona_issue112.py
/home/thomasjiralerspong/explore-persona-space/scripts/run_100_persona_leakage.py
/home/thomasjiralerspong/explore-persona-space/scripts/run_persona_composition.py
/home/thomasjiralerspong/explore-persona-space/scripts/figures/plot_issue261_per_persona.py

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/home/thomasjiralerspong/explore-persona-space/scripts/compare_extraction_methods.py

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I have enough context. Now let me run the internal Planner → Fact-checker → Critic → Consistency loop and write the plan file.

Key facts from exploration:
- The Sagan repo is dashboard + RunPod runner only — the actual extraction code lives in `/home/thomasjiralerspong/explore-persona-space/`, which contains `extract_centroids_and_analyze.py`, `extract_persona_vectors.py`, and `compare_extraction_methods.py`.
- "Centroid steering is approximately random direction at L20" is parked as Issue #267 — the existing recipe has a known weakness.
- Experiment ID `0c120ea3-746a-43e6-a760-e6112f8cb649` is not on disk; it lives in the `experiments` table.
- "Chen et al." is **not** cited anywhere in the repo — the exact paper must be pinned before kickoff.

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File created successfully at: /home/thomasjiralerspong/.claude/plans/run-f8c0ec5a-6010-43ed-a3aa-c845115d601-synthetic-dolphin.md (file state is current in your context — no need to Read it back)

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The experiment plan is drafted at `/home/thomasjiralerspong/.claude/plans/run-f8c0ec5a-6010-43ed-a3aa-c845115d601-synthetic-dolphin.md` and ready for your review.

**Headline framing:** head-to-head of the Chen et al. persona-vector recipe vs. the project's existing centroid-difference recipe on the same 100-persona set, same `Llama-3.1-8B-Instruct`, same compute envelope.

**Key adversarial points baked in:**
- The biggest risk is that "Chen et al." is **not cited anywhere in either the Sagan dashboard or `explore-persona-space`**. The plan makes pinning the exact paper (arXiv ID / DOI) a hard precondition to any GPU spend — kill-criterion-level.
- The known #267 weakness ("centroid steering ≈ random direction at L20") is acknowledged, but the plan refuses to strawman centroid: it reports best-per-persona layer for *both* recipes as the primary comparison and treats L20 as a secondary curve.
- A prompt-design confound is called out (Chen may win because of better prompts, not a better algorithm). An optional third arm — centroid-on-Chen-prompts — is included, gated on remaining budget.
- LLM-judge bias is mitigated with blind pairwise eval + cross-judge agreement + refusal/helpfulness side metrics.
- Hard caps: **18 GPU-hours / $60 RunPod / $15 judge API.**

**Concrete predictions to beat:** Chen AUROC ≥ centroid AUROC + 0.05 at best-per-persona layer; Chen steering preferred in ≥ 55% of blind pairwise judgments without >5 pp refusal increase; per-layer cross-recipe cosine in [0.2, 0.6].

**Artifacts:** `vectors_chen.npz`, `vectors_centroid.npz`, `eval_metrics.json` with bootstrap CIs, four plots, `REPORT.md`, branch `exp/chen-vs-centroid-0c120ea3` in `explore-persona-space`, WandB run linked into `runs.wandbUrl`, Sagan experiment record `0c120ea3-...` updated through its state machine.

The Approval Checklist at the bottom of the plan covers goal, hypothesis, prediction, kill criterion, compute/hardware, artifacts, verification, risks, and likely clean-result shape — please tick through it before approving.

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