There is a point where collecting prompts stops being useful. You have a prompt for SQL, one for documentation and another for charts—and still rebuild the same process every Monday.
Prompt versus workflow
A prompt is an instruction. A workflow has a trigger, inputs, steps, checks and an expected output. That makes it reusable and easier to review.
Build one workflow at a time
Pick a task you repeat every week. For example: preparing a KPI report.
- Trigger: reporting period closes.
- Inputs: metric definitions, source tables and reporting window.
- AI step: draft SQL or identify likely anomalies.
- Analyst step: validate totals and investigate exceptions.
- Output: decision-ready summary.
Define what AI is allowed to do
For each workflow, document what AI may draft, what it may suggest and what requires human approval. This prevents “AI use” from becoming an undefined permission to automate everything.
Make quality control part of the system
A reusable workflow without verification is simply a reusable way to make the same mistake. Include checks for data quality, logic, assumptions and edge cases.
The maturity path
Experiment → repeat → validate → document. The goal is not maximum AI usage. It is predictable, explainable work.
See the workflow from question to insight for the analyst-side process.