# How Instacart Built Blueberry, a Slack-Native On-Call Reasoning Harness

DevFeed: [How Instacart Built Blueberry, a Slack-Native On-Call Reasoning Harness](<https://devfeed.tech/articles/blueberry-force-multiplier-for-the-on-call-engineer-20103.md>)

Original publisher: [Read original article](<https://tech.instacart.com/blueberry-force-multiplier-for-the-on-call-engineer-98c446dfcc12?source=rss----587883b5d2ee---4>)

Author: Karthik Halukurike

Published: 2026-07-14T16:39:20Z

Content type: tutorial

Language: en

Sources: [Instacart](<https://devfeed.tech/sources/instacart.md>)

Topics: [incident](<https://devfeed.tech/topics/incident.md>), [Slack](<https://devfeed.tech/topics/slack.md>), [context](<https://devfeed.tech/topics/context.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>)

Tags: [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-agents-in-action](<https://devfeed.tech/tags/ai-agents-in-action.md>), [context](<https://devfeed.tech/tags/context.md>), [incident-response](<https://devfeed.tech/tags/incident-response.md>), [on-call](<https://devfeed.tech/tags/on-call.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [slack](<https://devfeed.tech/tags/slack.md>), [software-development](<https://devfeed.tech/tags/software-development.md>)

## AI overview

Instacart describes Blueberry, a Slack-native on-call reasoning harness that auto-triages qualifying alerts and supports follow-up investigations. It is designed to help teams reach a shared understanding and test theories more quickly during on-call work.

## Source excerpt

How we built a Slack-native on-call reasoning harness at Instacart that shortens time to first insight, speeds up theory testing, and turns tribal knowledge into reusable infrastructure. Key Contributors: Karthik Halukurike, Gabe de Oliveira, Hassan Jallad, Alan Wong On-call work is a race to turn noisy signals into shared judgment. The hardest minutes of that race aren't the ones spent fixing the bug -- they're the ones spent figuring out what the bug even is, while everyone in the thread is asking the same question from a slightly different angle. Blueberry is the system we built at Instacart for those several minutes. It lives in the Slack thread where the team is already coordinating, picks up each alert as it fires, and lands a grounded explanation back in the thread in about three minutes -- thousands of times a month. On-call is mostly a clarity and speed problem Most on-call pain does not start with a major incident. It starts in the noisy window right after a page fires, when the thread fills with links, dashboards, guesses, and partial context. Someone asks whether a deployment caused it. Someone else asks how broad it is. A third engineer joins and asks what is going on. In that moment, the hardest problem is often not deep root-cause analysis. It is getting to a shared understanding quickly enough that the team can make a good next move. For us, that made two metrics matter most: time to first insight (TTFI) and time to test theories (TTTT). TTFI comes from auto-triaging every qualifying alert the moment it lands. TTTT comes from engineer-initiated on-demand investigations and follow-ups as the investigation deepens. Blueberry is a Slack-native on-call reasoning harness Blueberry was built for that first window of confusion. Blueberry lives in Slack because that is where on-call engineers already coordinate, ask clarifying questions, and make decisions under pressure. We wanted the system to work inside the shared operational conversation so the full team