DEVOPS
Monthly DORA leadership brief with AI narrative to Notion
On the first of each month, pulls the prior month's per-team DORA aggregates from BigQuery, has an LLM write a plain-English trend narrative.
How it runs
The automated pipeline, trigger to output.
- TriggerMonthly schedule (1st of month)
- ActionQuery prior-month DORA aggregates from BigQueryBigQuery
- ActionDraft trend narrative with LLMOpenAI
- LogicAssemble narrative + tables into Notion blocks
- OutputPublish brief as Notion pageNotion
What it does
Generates the monthly delivery-performance brief leadership actually reads. It collects the previous month's deploy frequency and lead-time aggregates per team from BigQuery, asks an LLM to interpret the trends and call out movers and risks in clear prose, and publishes the result as a structured Notion page.
When to use it
Use this when raw DORA tables aren't landing with non-engineering stakeholders and you need a recurring narrative summary with context, not just charts. Pairs well with the daily scorecard workflow that feeds the BigQuery table.
How it works
- 1A monthly schedule trigger fires on the first of the month.
- 2Query the prior month's per-team DORA aggregates and month-over-month deltas from BigQuery.
- 3Action sends the structured metrics to an LLM to draft a trend narrative with highlights and concerns.
- 4Logic step assembles the narrative plus metric tables into a Notion block structure.
- 5Output creates the Notion page in the leadership workspace.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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