# When to Retrain, Rebuild, or Leave a Forecasting Model Alone

DevFeed: [When to Retrain, Rebuild, or Leave a Forecasting Model Alone](<https://devfeed.tech/articles/how-we-knew-covid-was-over-and-what-our-models-had-to-unlearn-56656.md>)

Original publisher: [Read original article](<https://airbnb.tech/ai-ml/how-we-knew-covid-was-over-and-what-our-models-had-to-unlearn/>)

Author: laurenmackevich

Published: 2026-08-20T19:33:16Z

Content type: article

Language: en

Sources: [Airbnb Engineering & Data Science](<https://devfeed.tech/sources/airbnb-engineering-data-science.md>)

Topics: [Data Science](<https://devfeed.tech/topics/data-science.md>), [data](<https://devfeed.tech/topics/data.md>), [Risk](<https://devfeed.tech/topics/risk.md>), [structure](<https://devfeed.tech/topics/structure.md>)

Tags: [ai-ml](<https://devfeed.tech/tags/ai-ml.md>), [data](<https://devfeed.tech/tags/data.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [risk](<https://devfeed.tech/tags/risk.md>)

## AI overview

Airbnb's Forecasting Data Science team explains how it decides whether a struggling forecast needs newer data, a different model, or no change. The article distinguishes refitting, respecifying, and holding a model, while emphasizing validation and production risk.

## Source excerpt

When we retrain, when we rebuild, and when we leave a model alone.