Amey-Thakur Agent analytics desk
Business analytics fails less on statistics than on definitions: two people mean different things by active user and both are quoting real queries. An analytics desk fixes the definition first and treats every number as something that must be reproducible.
Team
- Definer: writes the metric definition and the exact population before any query runs.
- Analyst (
data-scientist-role,product-metrics): produces the number and the breakdown. - Skeptic (
correlation-causation): checks it against a second source and names what the number cannot support.
Shape: definition first, analysis, then an independent challenge.
Method
- Write the metric definition before querying. Population, time window, inclusion rules, and exclusions. Most disagreements about numbers are disagreements about this, discovered late.
- Keep definitions in one place and version them. A metric that changes meaning silently makes every historical comparison wrong (see data-lineage).
- Produce the number with its breakdown. A total without segments invites the wrong conclusion, and the segment is usually the actual finding.
- Verify against an independent source. A second derivation, even a rough one, catches the query bug that a plausible number hides (see sql-joins).
- State what the number does not prove. Correlation, seasonality, and selection effects named explicitly, since the misread is more expensive than the number is valuable.
- Answer the decision, not the request. The question behind how many signups is usually whether something is working, and answering that directly is the desk's job.
- Keep the query with the answer. Reproducibility is what distinguishes analysis from assertion.
Run it
In Claude Code, require a definition file before the analyst subagent runs, then run the skeptic as a separate pass over the analyst's output and query. Both write into a dated question directory. Port to LangGraph with a verification node that can return the analysis for rework, or CrewAI as a sequential crew ending in a challenge task.
Signals it works
- Every number ships with its definition and its query.
- The skeptic regularly changes or qualifies a conclusion.
- Metric definitions are versioned, so old comparisons stay valid.
Boundaries
Agents compute and challenge; humans decide what to do. Statistical inference beyond descriptive comparison needs qualified review (see statistical-inference), and causal claims need a designed experiment (see ab-test-design). Analytics on personal data stays inside your privacy commitments (see data-minimization).