# Sidekick's continual learning loop

DevFeed: [Sidekick's continual learning loop](<https://devfeed.tech/articles/sidekick-s-continual-learning-loop-1617.md>)

Original publisher: [Read original article](<https://shopify.engineering/sidekicks-continual-learning-loop>)

Author: Andrew McNamara

Published: 2026-08-05T14:52:54Z

Content type: article

Language: en

Sources: [Shopify Engineering](<https://devfeed.tech/sources/shopify-engineering.md>), [Shopify Engineering - Shopify Engineering](<https://devfeed.tech/sources/shopify-engineering-shopify-engineering.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Shopify](<https://devfeed.tech/topics/shopify.md>), [GraphQL](<https://devfeed.tech/topics/graphql.md>), [Ground truth / benchmark quality](<https://devfeed.tech/topics/ground-truth-benchmark-quality.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [ai](<https://devfeed.tech/tags/ai.md>), [frontier-model](<https://devfeed.tech/tags/frontier-model.md>), [latency](<https://devfeed.tech/tags/latency.md>), [model](<https://devfeed.tech/tags/model.md>), [production](<https://devfeed.tech/tags/production.md>), [retrieval](<https://devfeed.tech/tags/retrieval.md>), [routing](<https://devfeed.tech/tags/routing.md>), [safety](<https://devfeed.tech/tags/safety.md>)

## AI overview

Shopify describes a continual learning loop for its GraphQL agent that turns production failures, user corrections, and sampled traffic into ground truth and model-weight improvements. The approach is reported to exceed frontier-model quality while reducing latency and serving costs by 96%.

## Source excerpt

How we compress production failures into model weights every day, beat frontier-model quality, and cut serving costs 96%.