What does AI temperature control?

Temperature controls how much variation or "improvisation" a language model allows in its output — higher values produce more creative, less predictable responses.

What temperature should I use for data extraction tasks?

Use 0.0 to 0.3 for classification, extraction, or anything that needs to match real data exactly, like invoice numbers or dates.

When should I use a higher temperature?

Reserve 0.8 and above for genuinely creative tasks like writing product descriptions, where variation is useful rather than risky.

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AI Agents

Set AI Temperature to 0.2 for Invoices, Not 0.7

Temperature controls how much an LLM is allowed to "improvise." Most agent templates ship with a default around 0.7 — tuned for natural-sounding conversation, not accuracy.

That's fine for a chatbot making small talk. It's a real problem for anything touching numbers, dates, or facts that need to be exactly right — an agent reading invoice data, quoting a price, or confirming an order total.

The fix:

for anything classification- or extraction-based (reading data, confirming facts, following a strict format), set temperature to 0.0–0.3. Save 0.7+ for genuinely creative tasks — writing a product description, brainstorming subject lines — where some variation is a feature, not a risk.

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