Test before you run
Check a prompt on a sample before you enrich everything, and what to look for in the results.
Optional. You don't need this to get started. Back to the quickstart
Enriching a full dataset takes time. A few minutes checking the prompt on a sample first catches most problems.
Two ways to test
Section titled “Two ways to test”- Ask the agent to label a sample. With Prompt Designer turned on in the agent’s settings, ask: “Pick 40 varied tickets and show me how this prompt would label them.” This is the agent applying your prompt in the chat, a preview, not a run of the enrichment itself. It’s the fastest way to iterate.
- Backfill a short range. Save the prompt, then on the Backfill tab run it over one source and a few days. Those labels come from the real enrichment, so read them before you backfill the full history.
Do the first until the sample looks clean, then the second before a large backfill.
Build a sample that covers the edges
Section titled “Build a sample that covers the edges”Don’t take the first 50 rows. We suggest 30 to 50 records across the file: the common kinds and the rare ones that matter (a cancellation, a complaint about safety, a one-word reply, a very long thread, a heavily redacted one).
What to check
Section titled “What to check”| Check | What goes wrong | Fix |
|---|---|---|
| Values outside your list | The model invents neutral or general_mention | Add “Do not use X; use Y” to the description |
| Quotes that aren’t quotes | A verbatim field paraphrases instead of copying | Say “copy the exact words; do not paraphrase” |
| Label without a quote | A judgement is set but its verbatim is none_detected | Make the two descriptions refer to each other |
| Speaker-label leaks | A persona or brand Dimension fires because the transcript says “Maya (AI):” | Say “ignore speaker labels” |
| Contradictions | resolved: true with an outcome of escalated | Define the two together |
Everything none_detected | The Dimension asks about something the text rarely contains | Check it is a text signal at all, then add phrases from your data |
| One value dominates | Nearly everything lands in one category | The categories are too coarse, or the description is too loose |
Run, read, fix, repeat
Section titled “Run, read, fix, repeat”Fix the descriptions, then test again on records you haven’t used yet. Two or three rounds is normal. When the sample is clean, save the prompt and backfill it, then spot-check the real results the same way.