--- title: AI Is Transforming Incident Response - but the Hardest... description: AI is reshaping incident response by automating routine tasks like summarizing channels, analyzing code, and suggesting fixes — but this creates a paradox. The... canonical: https://daily.dev/posts/ai-is-transforming-incident-response---but-the-hardest-problems-may-still-belong-to-humans-ialn9bwnf twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans | daily.dev og:description: AI is reshaping incident response by automating routine tasks like summarizing channels, analyzing code, and suggesting fixes — but this creates a paradox. The... og:url: https://daily.dev/posts/ai-is-transforming-incident-response---but-the-hardest-problems-may-still-belong-to-humans-ialn9bwnf og:image: https://api.daily.dev/og/posts/IaLN9BwNf.png og:image:alt: AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans **[InfoQ](https://daily.dev/sources/infoq)** · 4 min read · 3 upvotes · 1 comments ## Summary AI is reshaping incident response by automating routine tasks like summarizing channels, analyzing code, and suggesting fixes — but this creates a paradox. The more AI handles, the harder the remaining problems become for humans, and the more human expertise risks atrophying. Drawing on research from Uptime Labs, NIST, and discussions involving Chime and Rootly, the piece explores the Leftover Principle: automation leaves humans with only the novel, ambiguous, high-stakes failures. Incorrect AI recommendations can degrade human performance worse than no AI at all. Organizations are urged to invest in game days, chaos engineering, and simulations to maintain responder skills, while also strengthening deployment controls, observability, feature flags, and rollback mechanisms as AI accelerates the pace of code changes. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is the Leftover Principle in the context of AI and incident response? The Leftover Principle describes how, as automation takes over routine tasks, the work remaining for humans increasingly consists of the unusual, ambiguous, and difficult problems that automation cannot solve. In incident response, this means engineers face fewer routine incidents for practice, so when a truly complex failure occurs, responders may have less hands-on experience to draw on. _Teams weighing how much incident work to automate can follow ongoing coverage of AI and incident response on daily.dev._ ### What happens to human performance when AI gives incorrect incident diagnosis recommendations? Incorrect AI diagnostic recommendations can significantly degrade human performance compared with working without AI assistance at all, according to research cited from J. Paul Reed. Conversely, when AI recommendations are correct, responders perform substantially better than without AI. This asymmetry means teams need clear practices for knowing when to trust or challenge AI output during incidents. _Engineers building trust calibration into AI-assisted workflows can track this debate on daily.dev._ ### How might AI-assisted development change the frequency of production incidents? AI-assisted coding could increase incident frequency by raising the volume of changes shipped to production, since incident count depends on both change volume and the probability any change introduces a failure. Whether overall incidents rise depends on the quality of AI-generated code, tests, dependencies, and configs, making deployment controls, observability, feature flags, and rollback mechanisms more critical safeguards. _Teams scaling AI-generated deployments can follow related resilience-engineering discussion on daily.dev._ ## Community discussion Top comments from developers on daily.dev. **@jhon3484** · 0 upvotes > The Leftover Principle is the right frame, but the piece should name its lineage — this is Lisa Bainbridge's "Ironies of Automation" from 1983, and citing it turns a trend observation into a forty-year-old, well-validated result that operators ignored once already. The finding that _wrong_ AI recommendations degrade performance below the no-AI baseline is the most counterintuitive and actionable thing here, and it's buried; it deserves the lead, because it reframes the risk from "AI might not help" to "AI can actively cost you the incident." The prescription section reaches for the standard... ## Similar posts on daily.dev - [When AI fails: The new reality of incident management](https://daily.dev/posts/when-ai-fails-the-new-reality-of-incident-management-rsgw6au1i) · The New Stack · 1 upvotes · 0 comments - [AI changed how you respond to incidents. Your tabletops haven’t caught up.](https://daily.dev/posts/ai-changed-how-you-respond-to-incidents-your-tabletops-haven-t-caught-up--s0okuauci) · The New Stack · 0 upvotes · 0 comments - [AI made software development unrecognizable. Is cybersecurity next?](https://daily.dev/posts/ai-made-software-development-unrecognizable-is-cybersecurity-next--tmxghrlts) · CSO Online · 1 upvotes · 0 comments - [Human‑Centred AI for SRE: Multi‑Agent Incident Response without Losing Control](https://daily.dev/posts/human-centred-ai-for-sre-multi-agent-incident-response-without-losing-control-t6l4ggvwh) · InfoQ · 1 upvotes · 0 comments - [Is the human the bug or the feature of AI development?](https://daily.dev/posts/is-the-human-the-bug-or-the-feature-of-ai-development--0xscsqnws) · Codemotion · 2 upvotes · 0 comments --- Tags: [#devops](https://daily.dev/tags/devops), [#ai-agents](https://daily.dev/tags/ai-agents), [#observability](https://daily.dev/tags/observability) [View this post on daily.dev](https://daily.dev/posts/ai-is-transforming-incident-response---but-the-hardest-problems-may-still-belong-to-humans-ialn9bwnf) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans","url":"https://daily.dev/posts/ai-is-transforming-incident-response---but-the-hardest-problems-may-still-belong-to-humans-ialn9bwnf","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/ai-is-transforming-incident-response---but-the-hardest-problems-may-still-belong-to-humans-ialn9bwnf"},"datePublished":"2026-08-07T12:05:59.615Z","dateModified":"2026-09-14T07:06:00.018Z","description":"AI is reshaping incident response by automating routine tasks like summarizing channels, analyzing code, and suggesting fixes — but this creates a paradox. 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The finding that wrong AI recommendations degrade performance below the no-AI baseline is the most counterintuitive and actionable thing here, and it’s buried; it deserves the lead, because it reframes the risk from “AI might not help” to “AI can actively cost you the incident.” The prescription section reaches for the standard answers — game days, chaos engineering — without confronting the harder problem, which is skill acquisition rather than maintenance: seniors keep intuition built on years of routine incidents, while juniors who never handle those incidents never build it, and simulations don’t reproduce real stakes. The piece also treats AI purely as a responder aid when it is increasingly the cause — AI-authored changes shipping at higher volume means the incident rate rises exactly as the expertise pool thins, and that compounding is the real thesis, currently understated. Finally, add one measurable control to the recommendations: track AI suggestion accuracy and responder override rate per incident, because without those numbers an organization cannot distinguish healthy trust from complacency until an outage proves it.","datePublished":"2026-08-08T02:17:23.875Z","url":"https://daily.dev/posts/IaLN9BwNf#c-NzqPMkQTD","author":{"@type":"Person","name":"jhon34","url":"https://daily.dev/jhon3484"}}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/ai-is-transforming-incident-response---but-the-hardest-problems-may-still-belong-to-humans-ialn9bwnf#faq","mainEntity":[{"@type":"Question","name":"What is the Leftover Principle in the context of AI and incident response?","acceptedAnswer":{"@type":"Answer","text":"The Leftover Principle describes how, as automation takes over routine tasks, the work remaining for humans increasingly consists of the unusual, ambiguous, and difficult problems that automation cannot solve. 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