Do we have Salesloft cadence step or task-level data in the warehouse — specifically overdue cadence steps and steps due today by owner? If so, show overdue cadence steps and steps due today for the UK New Business team (Peter Chapman's reports: Eliana Brown, Luke Thomson, Freddie Brown, Joseph Ashcroft, Edwin Armah, Jack Hogg, Sam Tehrani, Dominik Kocis, Riaz Uddin). If we don't hold Salesloft step/task data, just say so plainly.
Showing the top 10 of 500 rows. Chandler is still young and makes mistakes in his calculations sometimes — reach out to the Data & Analytics team in #analytics-questions-and-alerts if you have questions.
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.
SELECT
omni_dbt__snowflake_column_usage."TABLE_CATALOG" AS "Database Name",
omni_dbt__snowflake_column_usage."TABLE_SCHEMA" AS "Schema Name",
omni_dbt__snowflake_column_usage."TABLE_NAME" AS "Table Name",
omni_dbt__snowflake_column_usage."COLUMN_NAME" AS "Column Name",
omni_dbt__snowflake_column_usage."NUM_QUERIES_LAST_30D" AS "Queries Last 30 Days",
omni_dbt__snowflake_column_usage."NUM_QUERIES_LAST_90D" AS "Queries Last 90 Days"
FROM PROD."SNOWFLAKE_COLUMN_USAGE" AS omni_dbt__snowflake_column_usage
WHERE
omni_dbt__snowflake_column_usage."TABLE_NAME" ILIKE ANY ('%salesloft%', '%cadence%', '%step%', '%task%')
OR omni_dbt__snowflake_column_usage."COLUMN_NAME" ILIKE ANY ('%salesloft%', '%cadence%', '%step%', '%task%', '%due%', '%owner%')
ORDER BY
omni_dbt__snowflake_column_usage."TABLE_NAME",
omni_dbt__snowflake_column_usage."COLUMN_NAME"
LIMIT 500
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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.