Parallel analysis lane

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# Parallel analysis lane | Field | Value | | --- | --- | | Session ID | `a19e9cda-5f7e-43d5-85f5-438cd1b52a3a` | | Lead session | `db706ee8-94fe-40d7-bace-430a85abc8b8` | | Record type | Parallel workstream export | :::note[Appendix record] Readable export of a supplementary review session. Tool outputs and system context are omitted; download the [JSONL archive](/audits/fable-chats-4626-2026-06.zip) for the complete log. ::: ## Engagement brief

Tuesday, Jun 9, 2026, 8:47 AM (UTC-7) Execute the full continual-learning memory update flow for this workspace.

Requirements:

1. Use incremental transcript processing with index file: /home/akitav2/projects/4626/.cursor/hooks/state/continual-learning-index.json
2. Process ONLY transcripts that are either:
   • not present in the index, OR
   • have mtime newer than the indexed mtime.
3. Refresh index mtimes for processed transcripts.
4. Remove index entries for transcripts that no longer exist.
5. Update /home/akitav2/projects/4626/AGENTS.md ONLY for high-signal, recurring user corrections and durable workspace facts.
6. Exclude one-off/transient details and any secrets.

Output contract:

• If no meaningful high-signal updates are found, return exactly: "No high-signal memory updates."
• Otherwise, return a concise summary of what was updated and confirm index refresh/removals performed.

Analysis

I’m running the full incremental continual-learning pass now: I’ll load AGENTS.md and the index, detect only new/changed transcripts, then apply only durable high-signal updates and refresh the index.

Tools invoked: UpdateCurrentStep, ReadFile

Analysis

Tools invoked: rg, ReadFile

Analysis

I have the current index loaded; next I’m computing the exact delta set (new/mtime-changed plus removed files) and then I’ll inspect only those transcripts for durable memory signals.

Tools invoked: Shell

Analysis

Tools invoked: Shell

Analysis

Tools invoked: UpdateCurrentStep, ReadFile, ReadFile, ReadFile, ReadFile, ReadFile, ReadFile, ReadFile

Analysis

I’ve isolated the changed transcript set; now I’m extracting only user queries/corrections from those files to decide whether any durable memory bullets should be added.

Tools invoked: Shell

Analysis

Tools invoked: ReadFile

Analysis

Tools invoked: UpdateCurrentStep

Analysis

Tools invoked: Shell

Analysis

Tools invoked: Shell

Analysis

Tools invoked: Shell

Analysis

Tools invoked: rg, rg

Analysis

Tools invoked: rg, rg

Analysis

I found two durable high-signal deltas worth keeping: a project-definition correction (lottery + ve(3,3)-style burn mechanics), and a recurring UI preference for unified identity resolution priority across chat/leaderboard/account surfaces. I’m adding those to AGENTS.md now, then finishing with the refreshed index state.

Tools invoked: ApplyPatch

Analysis

Tools invoked: Shell

Analysis

Tools invoked: UpdateCurrentStep

Analysis

Updated with meaningful high-signal memory changes:

• AGENTS.md updated with:
  • a durable user preference to keep identity resolution/avatar priority unified across chat, leaderboard, and account surfaces (Zora -> Basename -> ENS -> 0x) and avoid slow/flickering fallback regressions.
  • a durable workspace fact that 4626’s canonical framing includes lottery/rewards as a core pillar and a ve(3,3)-inspired model centered on share-token burn/value capture rather than emissions.
• Incremental index processing executed against /home/akitav2/projects/4626/.cursor/hooks/state/continual-learning-index.json:
  • processed only transcripts that were new/mtime-updated (7 files)
  • removed stale entries for missing transcripts (none found)
  • refreshed index mtimes to current state (575 entries, fully in sync).