Same list as before: accounts that had an AI Assist churn or downsell event (AI Assist MRR movement = Removed or Downsell) between 2026-01-23 and 2026-07-23, excluding Dext demo and Reseller accounts. This time return account_crn AND account_name for each row, plus the churn_reason and salesforce_country and finance_account_type. One row per account per event. Include the account name column.
Per-step detail — each LLM call, each Omni request, each rejected draft —
is traced to stdout only and is not stored, so it cannot be shown here.
Query attempts counts run_query executions, not model turns.
Error calling tool 'ask': Wait returned empty summary with no result: {"job_id":"33eefe0d-a3f0-4dcb-aa3e-f3a4b2ebcca9","status":"COMPLETE","client_result_id":"e458818c-0f2b-4e05-955c-1b2e1a23375b","summary":{"cache_type":"MISS","display_sql":"SELECT \"t1\".\"omni_dbt__eds_calendar_day.date_day[date]\" AS \"omni_dbt__eds_calendar_day.date_day[date]__raw\",\n \"t1\".\"omni_dbt__eds_all_accounts.account_crn\",\n \"t1\".\"omni_dbt__eds_bookings_addon_changes.ai_assist_bookings_mrr_movement\",\n \"t1\".\"omni_dbt__eds_all_accounts.churn_reason\",\n \"t1\".\"omni_dbt__eds_all_accounts.salesforce_country\",\n \"t1\".\"omni_dbt__eds_all_accounts.finance_account_type\",\n COALESCE(SUM(\"t1\".\"$f7\"), 0) AS \"omni_dbt__eds_bookings_addon_changes.total_ai_assist_bookings_mrr_change_amount\",\n TO_CHAR(\"t1\".\"omni_dbt__eds_calendar_day.date_day[date]\", 'YYYY-MM-DD') AS \"omni_dbt__eds_calendar_day.date_day[date]\"\nFROM (SELECT \"omni_dbt__eds_all_accounts\".\"ACCOUNT_CRN\" AS \"omni_dbt__eds_all_accounts.account_crn\",\n \"omni_dbt__eds_all_accounts\".\... [truncated, 24477 more chars]
{
"calculations": [],
"fields": [
"omni_dbt__eds_bookings_addon_changes.ai_assist_bookings_mrr_movement",
"omni_dbt__eds_bookings_addon_changes.total_ai_assist_bookings_mrr_change_amount"
],
"filters": {
"omni_dbt__eds_all_accounts.is_dext_demo": {
"is_negative": true,
"treat_nulls_as_false": true,
"type": "boolean"
},
"omni_dbt__eds_all_accounts.salesforce_account_type": {
"is_negative": true,
"kind": "EQUALS",
"type": "string",
"values": [
"Reseller"
]
},
"omni_dbt__eds_calendar_day.date_day[date]": {
"kind": "BETWEEN",
"left_side": "2026-01-23",
"right_side": "2026-07-24",
"type": "date"
}
},
"limit": 1000,
"modelId": "e407bba6-4fae-4079-ac4e-cd6cf8fdf6f8",
"pivots": [],
"sorts": [
{
"column_name": "omni_dbt__eds_bookings_addon_changes.ai_assist_bookings_mrr_movement",
"sort_descending": false
}
],
"table": "omni_dbt__eds_all_accounts"
}
No feedback linked to this request.
Cost is the LLM completion spend LiteLLM priced for each call, summed per
request.
Chandler is running on the Codex CLI, which draws ChatGPT plan quota
rather than per-token API billing, so this figure is not money paid —
it is what the same traffic would have cost on the API, priced from the
token counts Codex reports. Read it as the size of the bill avoided.
Two known limits: embedding spend is not recorded, so
retrieval and matching cost is missing, and because the figure is one sum
per request it cannot be split by model within a request — a
request's classifier and agent calls can use different models while
llm_model holds only one name.
Only authenticated calls are logged, USAGE_LOG_ENABLED can
switch logging off, and log writes are fail-soft — this is not a complete
record of traffic. Questions are grouped into sessions: a session is
exact when the caller echoed its id back to us and otherwise inferred from
a 30-minute gap in that user’s activity, so a grouping is only as
good as the source shown on the session itself. A call with no
attributable user gets no session at all; those questions are listed
separately rather than dropped.