[ { "sessionId": "226e0e07-1291-4bd7-bcf6-ae870fb2e506", "toolUseId": "toolu_0138pRD8ckvesCTQy87DbJjZ", "questions": [ { "question": "D2 \u2014 Architecture: Custom retry scheduler vs. the library's built-in retry hooks? ", "header": "Retry arch", "multiSelect": false, "options": [ { "label": "Use library built-in with curve config (Recommended)", "description": "Verify the library's backoff API, configure the curve there. Zero new code. Completeness: 9/10. (human: ~30min to verify API / CC: ~5min)" }, { "label": "Custom scheduler, shared module", "description": "Roll custom but extract it to one shared module rather than copying inline to all 5 workers. Completeness: 8/10. (human: ~4h / CC: ~15min)" }, { "label": "Proceed as planned \u2014 custom, inline per worker", "description": "Each worker gets its own copy of the retry logic. Completeness: 5/10. Creates 5 divergence points; acknowledged DRY violation from the start." } ] } ], "answered": true, "failed": false, "answers": { "D2 \u2014 Architecture: Custom retry scheduler vs. the library's built-in retry hooks? ": "Use library built-in with curve config (Recommended)" }, "unansweredQuestionIndices": [], "answeredAt": "2026-09-09T07:05:35.182Z" }, { "sessionId": "226e0e07-1291-4bd7-bcf6-ae870fb2e506", "toolUseId": "toolu_01Pocbd57aDt1wBR6MhVuaxt", "questions": [ { "question": "D3 \u2014 Code Quality: The retry envelope (compute delay, log attempt, dispatch) is copy-pasted across 5 worker files. The plan defers the refactor to 'later.' How should we handle this? ", "header": "DRY violation", "multiSelect": false, "options": [ { "label": "Extract to shared module now (Recommended)", "description": "Pull the retry envelope into one shared module before shipping. CC makes this ~10min. Bug fixes apply once, not 5 times. Completeness: 9/10." }, { "label": "Ship with copies, add tracked TODO", "description": "Keep the 5 copies for now, but add a TODOS.md entry with a concrete upgrade trigger (e.g., 'before adding a 6th worker'). Completeness: 6/10." }, { "label": "Proceed as planned \u2014 copy-paste, refactor 'later'", "description": "No extraction, no tracking. Each worker diverges independently over time. Completeness: 3/10." } ] } ], "answered": true, "failed": false, "answers": { "D3 \u2014 Code Quality: The retry envelope (compute delay, log attempt, dispatch) is copy-pasted across 5 worker files. The plan defers the refactor to 'later.' How should we handle this? ": "Extract to shared module now (Recommended)" }, "unansweredQuestionIndices": [], "answeredAt": "2026-09-09T07:05:57.238Z" }, { "sessionId": "226e0e07-1291-4bd7-bcf6-ae870fb2e506", "toolUseId": "toolu_0195Nj7YjAuqyngr2bhsMqgy", "questions": [ { "question": "D4 \u2014 Performance: On every retry the plan re-fetches the full job payload from the database AND recomputes the dependency graph. The plan notes caching is possible but 'not planned.' For a retry framework (same job fires N times), this multiplies DB reads by retry count. What should we do? ", "header": "Retry cache", "multiSelect": false, "options": [ { "label": "Cache parsed dependency graph on first attempt (Recommended)", "description": "Parse the graph once, attach it to the job context object, reuse on retries. DB reads = 1 per job regardless of retry count. Completeness: 9/10. (CC: ~10min)" }, { "label": "Cache full payload only, re-parse each retry", "description": "Eliminate the DB round-trip on retries by caching the raw payload, but still re-parse the dependency graph each time. Completeness: 7/10. Partial win." }, { "label": "Proceed as planned \u2014 re-fetch + recompute every retry", "description": "No caching. DB load scales with retry count. For a job retrying 5\u00d7, that is 5 DB reads and 5 graph traversals for the same data. Completeness: 4/10." } ] } ], "answered": true, "failed": false, "answers": { "D4 \u2014 Performance: On every retry the plan re-fetches the full job payload from the database AND recomputes the dependency graph. The plan notes caching is possible but 'not planned.' For a retry framework (same job fires N times), this multiplies DB reads by retry count. What should we do? ": "Cache parsed dependency graph on first attempt (Recommended)" }, "unansweredQuestionIndices": [], "answeredAt": "2026-09-09T07:06:09.262Z" }, { "sessionId": "226e0e07-1291-4bd7-bcf6-ae870fb2e506", "toolUseId": "toolu_01NsJuHrMsfaftvyrRjT1tBb", "questions": [ { "question": "TODO candidate \u2014 Retry observability: The plan introduces retry infrastructure but no way to see which jobs are retrying, how many times, or why they're failing. Without this, a retry storm is invisible until it shows up as load. Add to TODOS.md?", "header": "TODO: metrics", "multiSelect": false, "options": [ { "label": "Add to TODOS.md (Recommended)", "description": "Track: retry count per job, failure reasons, p99 retry latency. Implement after this PR ships. Depends on: shared retry envelope (T2) \u2014 metrics attach there." }, { "label": "Skip \u2014 not valuable enough", "description": "Logging/metrics are a separate concern. Leave it out." }, { "label": "Build it now in this PR", "description": "Add basic retry-count and failure-reason logging inside the shared retry envelope (T2) before shipping." } ] } ], "answered": true, "failed": false, "answers": { "TODO candidate \u2014 Retry observability: The plan introduces retry infrastructure but no way to see which jobs are retrying, how many times, or why they're failing. Without this, a retry storm is invisible until it shows up as load. Add to TODOS.md?": "Add to TODOS.md (Recommended)" }, "unansweredQuestionIndices": [], "answeredAt": "2026-09-09T07:06:53.371Z" }, { "sessionId": "226e0e07-1291-4bd7-bcf6-ae870fb2e506", "toolUseId": "toolu_011bZEZbSYMgHLvG62iB5iwv", "questions": [ { "question": "TODO candidate \u2014 Exhausted retry handling: The plan doesn't specify what happens when a job hits max retries. Silent drop? Error log? Dead-letter queue? This affects data integrity guarantees (especially relevant given the at-most-once concern). Add to TODOS.md?", "header": "TODO: dead-letter", "multiSelect": false, "options": [ { "label": "Add to TODOS.md (Recommended)", "description": "Define the max-retry policy and implement dead-letter queue or explicit error handler. Depends on: retry framework (this PR)." }, { "label": "Skip \u2014 not valuable enough", "description": "Acceptable to handle this in a follow-up or treat as a known gap." }, { "label": "Build it now in this PR", "description": "Define max retry count and wire a dead-letter handler before shipping. Adds ~1h scope." } ] } ], "answered": true, "failed": false, "answers": { "TODO candidate \u2014 Exhausted retry handling: The plan doesn't specify what happens when a job hits max retries. Silent drop? Error log? Dead-letter queue? This affects data integrity guarantees (especially relevant given the at-most-once concern). Add to TODOS.md?": "Add to TODOS.md (Recommended)" }, "unansweredQuestionIndices": [], "answeredAt": "2026-09-09T07:06:59.382Z" } ]