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Inspired by Bainbridge’s Ironies of automation, this post unpacks how AI can go wrong in high-stakes situations, and shares the principles guiding our approach to building tools that make humans sharper, not sidelined."/><meta name="keywords" content="incident,incident management,incident response,post mortem,outage,slack incident,incident channel"/><meta name="slack-app-id" content="A01DEGPUHHC"/><link rel="canonical" href="https://incident.io/building-with-ai/avoiding-the-ironies-of-automation"/><meta property="og:title" content="Avoiding the ironies of automation | Building with AI | incident.io"/><meta property="og:description" content="Incidents happen when the normal playbook fails—so why would we let AI run them solo? Inspired by Bainbridge’s Ironies of automation, this post unpacks how AI can go wrong in high-stakes situations, and shares the principles guiding our approach to building tools that make humans sharper, not sidelined."/><meta property="og:image" content="https://cdn.sanity.io/images/oqy5aexb/production/288c9dfbbca46ce378f44f3e1200766d116df527-2400x1350.png?w=1200&amp;fm=jpg&amp;q=90&amp;1745953454000"/><meta property="og:image:width" content="1200"/><meta property="og:image:height" content="628"/><meta name="twitter:card" content="summary_large_image"/><meta name="twitter:site" content="@incident_io"/><meta name="twitter:creator" content="@incident_io"/><meta name="twitter:title" content="Avoiding the ironies of automation | Building with AI"/><meta name="twitter:description" content="Incidents happen when the normal playbook fails—so why would we let AI run them solo? 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group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#driving-the-incident-">Driving the incident </a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#owning-public-communication-">Owning public communication </a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#triggering-mitigating-actions">Triggering mitigating actions</a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500" href="#flipping-the-paradox-with-a-cooperative-agent">Flipping the paradox with a cooperative agent</a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#augmentation-not-replacement">Augmentation, not replacement</a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#transparency-over-black-boxes-">Transparency over black-boxes </a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#encouraging-active-engagement-">Encouraging active engagement </a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500 border-l border-dashed text-body-sm text-content-secondary ml-4 pl-4" href="#using-incidents-as-a-learning-mechanism-">Using incidents as a learning mechanism </a></li><li class="flex flex-col gap-3 relative group"><a class="flex items-center transition text-pretty py-2 hover:text-alarmalade-500" href="#building-the-next-generation-of-incident-response">Building the next generation of incident response</a></li></ul></div></div><div class="lg:max-w-[788px] grow flex flex-col gap-4 lg:gap-10" id="content-top"><div class="flex flex-col gap-4"><div class="flex flex-col gap-2"><h1 class="text-h3 text-balance">Avoiding the ironies of automation</h1></div><div class="flex flex-col gap-2 md:flex-row justify-between mt-auto"><div class="flex items-center gap-2"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"></div><a class="text-body-sm-emphasis leading-[1.1] w-min sm:w-auto transition hover:text-alarmalade-500" href="/blog/author/chris">Chris Evans</a></span></div><div class="text-body-sm text-content-secondary">March 26, 2025<span> — <!-- -->9 min read</span></div></div></div><div class="relative"><span class="relative overflow-hidden block align-top transition-opacity opacity-0 w-full rounded-lg"><img alt="" width="2400" height="1350" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent;view-transition-name:avoiding-the-ironies-of-automation" sizes="100vw" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F3758aedd77a719f3afed170d122a6b24663f0185-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=60&amp;q=75 60w, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F3758aedd77a719f3afed170d122a6b24663f0185-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=64&amp;q=75 64w, 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src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F3758aedd77a719f3afed170d122a6b24663f0185-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span><a class="transition-all group hover:brightness-90 overflow-hidden absolute size-[90px] md:size-[120px] top-[-20px] right-[-16px] lg:top-[-35px] xl:right-[-35px]" href="/careers#open-roles"><img alt="We are hiring" width="360" height="360" decoding="async" data-nimg="1" class="transition-all duration-300 group-hover:rotate-[5deg] group-hover:scale-[0.96]" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fimmutable%2Fmedia%2Fwearehiring-sticker.1oj-53t_-42st.png&amp;w=384&amp;q=90 1x, /_next/image?url=%2F_next%2Fstatic%2Fimmutable%2Fmedia%2Fwearehiring-sticker.1oj-53t_-42st.png&amp;w=750&amp;q=90 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fimmutable%2Fmedia%2Fwearehiring-sticker.1oj-53t_-42st.png&amp;w=750&amp;q=90"/><span class="sr-only">We are hiring</span></a></div><div class="prose prose-orange text-body max-w-none mb-6"><p class="">We&#x27;re using AI to build an agentic product that works collaboratively <strong>with</strong> responders to improve incident investigations and resolve incidents faster. A bold claim, I know, and I think pretty impressive to land the word “agentic” so early on—I promise it’s the last time I use it.</p><p class="">After six months of digging into this, I’m convinced: AI in incident response won’t just be helpful—it’ll be essential. As more software is built <em>with</em>, and increasingly <em>by</em>, AI, responders will have less and less context about the systems they’re operating. That shrinking understanding—combined with the ever-growing volume of software—only increases the need for tools that can assist.</p><p class="">Done right, there&#x27;s a huge upside in this approach too—faster incident resolution, reduced customer impact, and less cognitive burden on the folks putting out the fires.</p><p class="">But with more automation comes a new shape of risk—much of which is captured in Lisanne Bainbridge’s 1983 paper, <a href="http://www.complexcognition.co.uk/2021/06/ironies-of-automation.html" target="_blank" rel="noopener noreferrer" class=""><em>Ironies of automation</em></a>. In the paper, Bainbridge explains that automation meant to help can paradoxically make things harder. As routine tasks get automated, human skills fade from lack of practice, so when the system fails (and they will!), responders are left underprepared and out of context.</p><p class="">Working in tech companies, I’m yet to see these risks materialise seriously, but there are definite elements of truth here. Count the number of Kubernetes incidents where operators have no idea what’s happening and you’ll get the gist.</p><div class="callout"><p class="">✈️ <strong>A fatal negative consequence of automation</strong></p><p class="">In 2009, Air France Flight 447 crashed into the Atlantic Ocean after autopilot disengaged during a severe storm. The pilots, accustomed to automation handling routine flight conditions, struggled to correctly interpret the sudden barrage of unfamiliar warnings and data. Their manual flying skills and diagnostic abilities had degraded through reliance on automation, leaving them tragically underprepared for this critical scenario.</p></div><p class="">At the core, I see incidents as a <strong>fundamentally human activity</strong>. They’re what happens when all of your preventative controls have failed, leaving you entirely outside the world of normal operation. So when I think about automation in incidents, it makes no sense to me that we’d be looking to replace humans. The only sensible mode of operation is one where humans and machines cooperate to reach a resolution.</p><h2 id="the-risk-of-being-too-smart-too-soon" class=""><a class="heading-link" href="#the-risk-of-being-too-smart-too-soon"><span class="icon icon-link"></span></a>The risk of being too smart, too soon</h2><p class="">Before going any further, I want to touch on a few ideas from Bainbridge’s paper that feel especially relevant when we think about automation in incident response.</p><p class="">Let’s start with what I’d consider to be an <em>over-automated</em> vision of the future—where AI tries to take over <strong>critical work</strong> and decision-making from human responders. That’s a subjective line, sure, but an easy one to spot when you look at real examples.</p><h3 id="driving-the-incident-" class=""><a class="heading-link" href="#driving-the-incident-"><span class="icon icon-link"></span></a>Driving the incident </h3><p class="">Bainbridge actually calls this out directly. She writes that “using the computer to give [the human] instructions is inappropriate if the operator is simply acting as a transducer”—a passive channel for actions, rather than someone thinking and deciding. </p><p class="">If AI sets the direction and humans just follow along, we risk losing human judgment, context, and ultimately, effectiveness. </p><div class="callout"><p class="">✅ <strong>Rubber-stamping our way into outages</strong> </p><p class="">An engineer gets paged at 3am, half-asleep, and sees that the AI has diagnosed an issue and is asking them to “confirm” a reboot of all servers in Amsterdam. The rationale? A recent software change might be causing instability, and a reboot fixed it the last few times this kind of issue happened. <br/><br/>You hit confirm—because it’s 3am, you’re tired, and hey, the AI seems confident. <br/><br/>Except… the issue wasn’t caused by the new release. It was a noisy-but-harmless log storm triggered by a recent feature flag toggle. The reboot interrupts real customer traffic, kicks off alerts across regions, and suddenly you’ve turned a minor hiccup into a cross-regional mess. <br/><br/>The AI didn’t make the wrong call—it made a <em>reasonable</em> one, based on limited context. The problem is, you acted like a glorified button-clicker instead of a thinking responder. That’s when judgement, context, and that gut-level “wait a second…” instinct go out the window. <br/><br/>A slightly exaggerated example, granted, but it’s easy to see how a confident AI and a tired human can to drift into a world of human’s rubber-stamping decisions they didn’t actually make. </p></div><h3 id="owning-public-communication-" class=""><a class="heading-link" href="#owning-public-communication-"><span class="icon icon-link"></span></a>Owning public communication </h3><p class="">In a world where AI can write convincing human-like text, it’s tempting to delegate responsibility to an automated system to have it update a status page or send Slack messages to execs. But tone, timing, and nuance matter. Too many updates cause panic. Too few erode trust. Communication during incidents is part judgment, part empathy—still very much human territory. <br/></p><div class="callout"><p class=""> 📢 <strong>Good intentions, bad broadcast</strong> </p><p class="">An incident kicks off. Services are falling over, people are scrambling, and your trusty AI companion jumps into action: it posts to the status page, triggering a number of subscribes to get updates via email. </p><p class="">Problem is… it doesn’t quite have the full picture. </p><p class="">It mentions “data loss” based on an ambiguous log line. And then, just to keep the chaos rolling, it goes silent for three hours while humans are heads-down fixing things—leaving customers, execs, and half of LinkedIn assuming the company has fallen into the sea. </p><p class="">Technically, the AI did what it was told: communicate. But without human judgment around tone, timing, and what <em>not</em> to say, it turned a tricky situation into a reputational mess. </p></div><h3 id="triggering-mitigating-actions" class=""><a class="heading-link" href="#triggering-mitigating-actions"><span class="icon icon-link"></span></a>Triggering mitigating actions</h3><p class="">Automatically restarting services or flipping traffic sounds like an SRE’s dream. But when things go wrong, they <em>really</em> go wrong—and mitigation can end up being more destructive than the original issue. Until systems have the full context their human counterparts do, the ability to take consequential actions should be treated with caution. </p><div class="callout"><p class="">🔥 <strong>From graceful degradation to total meltdown</strong> </p><p class="">Traffic to a dashboard page is spiking, and CPU usage on its backing services is climbing fast. But the team’s not worried—they know it’s the result of a marketing email. The load is expected, and the service is degrading gracefully. </p><p class="">The AI, lacking that context, decides to scale up the service. Sounds helpful—until the shared database gets overwhelmed, and the whole product goes offline. What started as a manageable situation just became a full-blown outage. </p><p class="">The AI made a reasonable decision based on what it knew. But without the surrounding context—why the traffic was spiking, how the service handles load, the impact on shared infrastructure—it turned a non-problem into a disaster. </p><p class="">A slightly reductive example as autoscaling is a well-established practice. But it’s a good illustration of how automation, without guardrails or context, can easily go a step too far.</p></div><p class="">In the paper, Bainbridge poses two key questions that automation designers should wrestle with:</p><ol><li>What happens when the automation fails?</li><li>How does automation change the way people work?</li></ol><p class="">In incident response, effectiveness comes from <strong>repetition, exposure, and experience</strong>. People get better over time by seeing unusual and surprising failures, talking through trade-offs, and building up mental models of how systems behave. If automation quietly takes all that away, we lose opportunities for growth, learning, and curiosity.</p><p class="">And that’s the real long-term risk: a future where incidents are “handled” by machines, responders disengage, local knowledge fades, and no one wants to supervise a machine solving problems they don’t understand. And when automation breaks you’ll be relying on humans whose skills have quietly eroded, right when you need them most.</p><h2 id="flipping-the-paradox-with-a-cooperative-agent" class=""><a class="heading-link" href="#flipping-the-paradox-with-a-cooperative-agent"><span class="icon icon-link"></span></a>Flipping the paradox with a cooperative agent</h2><p class="">Fortunately it’s not all doom-and-gloom. I believe there’s a bright future for AI automation in incident response. As someone building it I would say that, of course, but setting aside the obvious incentives and biases it’s something I truly believe.</p><p class="">I think success lies in a few key principles that shape both the technical implementation and the overall interaction model (i.e. the UX) of the system. When we talk about what we&#x27;re building internally, we&#x27;re firmly anchored to the notion of cooperative agent rather than replacement for work. The vibe we&#x27;re aiming for is &quot;your best engineer in every incident&quot;, where <em>best</em> covers both technical and social excellence. </p><p class="">Here’s how I think about the “good future”...</p><h3 id="augmentation-not-replacement" class=""><a class="heading-link" href="#augmentation-not-replacement"><span class="icon icon-link"></span></a>Augmentation, not replacement</h3><p class="">incident.io will not automate away critical human decision-making. Our goal is to strengthen it with humans remaining central, and AI tools providing supportive context. </p><p class="">Practically speaking, we repeatedly ask ourselves the questions “what would we want an experienced human collaborator to do here?”. Rarely do you draft in extra people only for them to take over and leave you on the sidelines. Our agents should act similarly.</p><div class="callout"><p class="">❌ I’ve reverted the PR and hotfixed it in production<br/><br/>✅ This PR (#2709) was merged just before this incident. It adds error handling that looks incorrect, and could lead to an alert like this</p></div><h3 id="transparency-over-black-boxes-" class=""><a class="heading-link" href="#transparency-over-black-boxes-"><span class="icon icon-link"></span></a>Transparency over black-boxes </h3><p class="">We’re not building black-box automation that hides complexity and reasoning—we’re doing the opposite. As we build out our cooperative automation, trust is one of the biggest hurdles we face, and we believe transparency is the way through it. </p><p class="">Just like with a human teammate, we’re far more willing to forgive a bad call if we can understand the reasoning behind it. When our agent reaches a conclusion, it will show its working: what it looked at, why it thinks it’s relevant, and where there’s uncertainty. No “just trust me” vibes.</p><div class="callout"><p class="">❌ Service-X is the problem. Click here to page them.<br/><br/>✅ From this graph, it looks like error rates are spiking in service-X. The logs show an uptick in ‘timeout’ errors starting at 14:23, which coincides with this config change. If that looks correct, you can page the team by clicking below.</p></div><h3 id="encouraging-active-engagement-" class=""><a class="heading-link" href="#encouraging-active-engagement-"><span class="icon icon-link"></span></a>Encouraging active engagement </h3><p class="">We want responders to stay actively involved, not fall into the trap of deferring to the AI just because it sounds confident. That means keeping humans in the loop—and responsible—when it comes to meaningful decisions. Language and UX matter a lot here. </p><p class="">We aim to be loud enough to offer useful input, but quiet enough not to bulldoze the conversation or imply there&#x27;s a single &quot;correct&quot; path. Our goal is to present credible theories, relevant data, and paths worth exploring—<em>not</em> to steer people into autopilot mode.</p><div class="callout"><p class="">❌ This is a regression from PR #456.<br/><br/>✅ One possibility: PR #456 modified retry logic in this area. I could be worth checking if that’s related?</p></div><h3 id="using-incidents-as-a-learning-mechanism-" class=""><a class="heading-link" href="#using-incidents-as-a-learning-mechanism-"><span class="icon icon-link"></span></a>Using incidents as a learning mechanism </h3><p class="">Humans aren’t great at trawling through piles of incident data to spot patterns—but machines are. Our goal is to surface the right context at the right time, helping responders build and refine their mental models in real time. </p><p class="">By handling the retrieval, synthesis, and pattern-matching, our tools free responders up to focus on the hard stuff: making judgement calls, thinking strategically, asking “what now?” Ironically, the more context we surface, the sharper responders become.</p><div class="callout"><p class="">❌ This alert has fired 12 times in the past.<br/><br/>✅ This alert fired during incidents in Feb and Oct last year—both related to queue backlogs in service-X after deploys. Might be worth checking if that’s happening again. See INC-2412 and INC-2508 for more details.</p></div><hr class="clear-both border-solid"/><h2 id="building-the-next-generation-of-incident-response" class=""><a class="heading-link" href="#building-the-next-generation-of-incident-response"><span class="icon icon-link"></span></a>Building the next generation of incident response</h2><p class="">Automation ironies show up when humans become passive, unskilled observers. And if your goal is to take meaningful work away from responders during incidents, you&#x27;d have a legitimate case for those issues showing up. But that’s not what we’re building.</p><p class="">We expect humans to stay deeply involved—working alongside the machine to gather context, explore problems, form hypotheses, and choose sensible paths to resolution. Lofty claims, sure—but ones we believe we’ll ship in the next few months.</p><p class="">Bainbridge’s paper calls out critical pitfalls in automation. We’ve read them, we’ve talked about them, and we’re actively building to avoid them.</p><p class="">If we get it right—and I’m confident we will—our product won’t just avoid these automation pitfalls; it’ll amplify the human skills we rely on when everything else has failed, providing timely advice, useful hypotheses and critical context exactly when it’s needed the most.</p></div><div class="flex justify-between"><div class="flex gap-3"><button class="relative inline-flex gap-2 items-center justify-center rounded-full focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-offset-2 disabled:opacity-60 group/button cursor-pointer transition-[color,background-color,border-color,opacity,transform] bg-surface-secondary hover:bg-surface-tertiary active:bg-surface-quaternary text-content-primary text-body-emphasis h-[41px] px-4 py-2"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="none" class="transition ease-in-out inline-block rotate-180 size-5"><path d="M12.8 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11.8-39.3 28.5-39.3 31.2 16.6 32.1 38.3zm-48.1 56.7c-10.3 24.6-34.6 41.9-63 41.9s-52.7-17.3-63-41.9c-1.2-2.9.8-6.2 3.9-6.5 18.4-1.9 38.3-2.9 59.1-2.9s40.7 1 59.1 2.9c3.1.3 5.1 3.6 3.9 6.5"></path></svg></button></div></div></div></section><section class="flex flex-col gap-6"><div class="flex flex-col md:flex-row justify-between gap-4"><h2 class="text-h3">More articles</h2><a class="relative gap-2 items-center justify-center rounded-full focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-offset-2 disabled:opacity-60 group/button cursor-pointer transition-[color,background-color,border-color,opacity,transform] bg-surface-secondary hover:bg-surface-tertiary active:bg-surface-quaternary text-content-primary text-body-emphasis h-[41px] px-4 py-2 hidden md:block" href="/building-with-ai">View all<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="none" class="transition ease-in-out inline-block size-5 group-hover/button:translate-x-1"><path d="M12.8 8.59965H3.00002C2.66882 8.59965 2.40002 8.33085 2.40002 7.99965C2.40002 7.66845 2.66882 7.39965 3.00002 7.39965H12.8C13.1312 7.39965 13.4 7.66845 13.4 7.99965C13.4 8.33085 13.1312 8.59965 12.8 8.59965Z" fill="currentColor"></path><path d="M9.60002 11.9996C9.53122 11.9996 9.46082 11.9876 9.39202 11.9628C9.08082 11.8476 8.92242 11.5028 9.03682 11.1924C9.66242 9.49645 10.7328 8.53005 11.5816 8.00045C10.7328 7.47085 9.66322 6.50445 9.03682 4.80845C8.92162 4.49725 9.08082 4.15245 9.39202 4.03805C9.70322 3.92125 10.048 4.08285 10.1624 4.39325C11.0656 6.84205 13.0656 7.39805 13.1496 7.42045C13.4144 7.49085 13.5992 7.73085 13.5976 8.00365C13.596 8.27725 13.412 8.51565 13.1464 8.58285C13.0648 8.60445 11.0656 9.16045 10.1624 11.6092C10.0728 11.8516 9.84402 12.0012 9.59922 12.0012L9.60002 11.9996Z" fill="currentColor"></path></svg></a></div><div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-8 md:gap-4"><a id="cea9a6eb-3549-4d99-bdfe-b4d479e121df" class="group flex flex-col" href="/building-with-ai/weaving-ai-into-the-fabric-of-incident-io"><div class="bg-surface-tertiary rounded-lg mb-3 md:mb-6 p-0 relative aspect-video"><span class="block align-top w-full overflow-hidden transition-all ease-in-out duration-300 mx-auto absolute inset-0 group-hover:w-[calc(100%-16px)] group-hover:py-2 [&amp;_img]:transition-all [&amp;_img]:rounded-lg group-hover:[&amp;_img]:rounded"><img alt="Weaving AI into the fabric of incident.io" loading="lazy" width="2400" height="1350" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F04f8711a8a763d2527ef98ce5685107669c2d5c2-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 1x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F04f8711a8a763d2527ef98ce5685107669c2d5c2-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="max-w-[546px] grow flex flex-col gap-2"><h3 class="text-h4 text-pretty">Weaving AI into the fabric of incident.io</h3><p class="text-body-sm line-clamp-2">How incident.io became an AI-native company — building reliable AI for reliability itself, and transforming how teams manage and resolve incidents.</p><div class="flex flex-wrap items-center gap-x-4 gap-y-1"><div class="flex items-center gap-2 flex-wrap"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"><span class="relative overflow-hidden block align-top"><img alt="Pete Hamilton" loading="lazy" width="100" height="100" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F4884ed999f884514b6fc1571af01407f7c78c286-512x512.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=128&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F4884ed999f884514b6fc1571af01407f7c78c286-512x512.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F4884ed999f884514b6fc1571af01407f7c78c286-512x512.png%3Fw%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75"/></span></div><span class="text-body-sm-emphasis leading-[1.1]">Pete Hamilton</span></span></div><div class="text-body-sm text-content-secondary">November 10, 2025</div></div></div></a><a id="cf3c4805-e561-4c41-a3f9-4d37c93a24a6" class="group flex flex-col" href="/building-with-ai/the-timeline-to-fully-automated-incident-response"><div class="bg-surface-tertiary rounded-lg mb-3 md:mb-6 p-0 relative aspect-video"><span class="block align-top w-full overflow-hidden transition-all ease-in-out duration-300 mx-auto absolute inset-0 group-hover:w-[calc(100%-16px)] group-hover:py-2 [&amp;_img]:transition-all [&amp;_img]:rounded-lg group-hover:[&amp;_img]:rounded"><img alt="The timeline to fully automated incident response" loading="lazy" width="2400" height="1350" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F7910aa6792a59314d664f5c10cb10e27f5c19e35-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 1x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F7910aa6792a59314d664f5c10cb10e27f5c19e35-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="max-w-[546px] grow flex flex-col gap-2"><h3 class="text-h4 text-pretty">The timeline to fully automated incident response</h3><p class="text-body-sm line-clamp-2">AI is rapidly transforming incident response, automating manual tasks, and helping engineers tackle incidents faster and more effectively. We&#x27;re building the future of incident management, starting with tools like Scribe for real-time summaries and Investigations to pinpoint root causes instantly. Here&#x27;s a deep dive into our vision.</p><div class="flex flex-wrap items-center gap-x-4 gap-y-1"><div class="flex items-center gap-2 flex-wrap"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"><span class="relative overflow-hidden block align-top"><img alt="Ed Dean" loading="lazy" width="100" height="100" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F47574bc43bd13e32eb1ce20e4664dbe37ceeca63-4899x4899.png%3Frect%3D852%2C0%2C3003%2C3003%26w%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=128&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F47574bc43bd13e32eb1ce20e4664dbe37ceeca63-4899x4899.png%3Frect%3D852%2C0%2C3003%2C3003%26w%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F47574bc43bd13e32eb1ce20e4664dbe37ceeca63-4899x4899.png%3Frect%3D852%2C0%2C3003%2C3003%26w%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75"/></span></div><span class="text-body-sm-emphasis leading-[1.1]">Ed Dean</span></span></div><div class="text-body-sm text-content-secondary">April 9, 2025</div></div></div></a><a id="448e4d92-dc2b-4363-9a65-22dcd5a4307b" class="group flex flex-col" href="/building-with-ai/you-cant-vibe-code-a-prompt"><div class="bg-surface-tertiary rounded-lg mb-3 md:mb-6 p-0 relative aspect-video"><span class="block align-top w-full overflow-hidden transition-all ease-in-out duration-300 mx-auto absolute inset-0 group-hover:w-[calc(100%-16px)] group-hover:py-2 [&amp;_img]:transition-all [&amp;_img]:rounded-lg group-hover:[&amp;_img]:rounded"><img alt="You can’t vibe code a prompt" loading="lazy" width="2400" height="1350" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fcf3570cfbff8893e2d06ce6852a8d02807459174-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75 1x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2Fcf3570cfbff8893e2d06ce6852a8d02807459174-2400x1350.png%3Fw%3D2000%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=3840&amp;q=75"/></span></div><div class="max-w-[546px] grow flex flex-col gap-2"><h3 class="text-h4 text-pretty">You can’t vibe code a prompt</h3><p class="text-body-sm line-clamp-2">Why blindly trusting AI to optimize your prompts can backfire, and human intuition is still essential when building intelligent agents.</p><div class="flex flex-wrap items-center gap-x-4 gap-y-1"><div class="flex items-center gap-2 flex-wrap"><span class="flex items-center gap-2"><div class="size-[22px] rounded-full overflow-hidden shrink-0"><span class="relative overflow-hidden block align-top"><img alt="Milly Leadley" loading="lazy" width="100" height="100" decoding="async" data-nimg="1" class="!m-0 w-full h-full object-cover" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F82ce0ba12c45fb8eac20b0abd789b514f2c9a2b2-1198x1197.png%3Frect%3D1%2C0%2C1197%2C1197%26w%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=128&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F82ce0ba12c45fb8eac20b0abd789b514f2c9a2b2-1198x1197.png%3Frect%3D1%2C0%2C1197%2C1197%26w%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fcdn.sanity.io%2Fimages%2Foqy5aexb%2Fproduction%2F82ce0ba12c45fb8eac20b0abd789b514f2c9a2b2-1198x1197.png%3Frect%3D1%2C0%2C1197%2C1197%26w%3D100%26h%3D100%26q%3D80%26fit%3Dmax%26auto%3Dformat&amp;w=256&amp;q=75"/></span></div><span class="text-body-sm-emphasis leading-[1.1]">Milly Leadley</span></span></div><div class="text-body-sm text-content-secondary">March 25, 2025</div></div></div></a></div><a class="relative inline-flex gap-2 items-center justify-center rounded-full focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-offset-2 disabled:opacity-60 group/button cursor-pointer transition-[color,background-color,border-color,opacity,transform] bg-surface-secondary hover:bg-surface-tertiary active:bg-surface-quaternary text-content-primary text-body-emphasis h-[41px] px-4 py-2 md:hidden" href="/building-with-ai">View all<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="none" class="transition ease-in-out inline-block size-5 group-hover/button:translate-x-1"><path d="M12.8 8.59965H3.00002C2.66882 8.59965 2.40002 8.33085 2.40002 7.99965C2.40002 7.66845 2.66882 7.39965 3.00002 7.39965H12.8C13.1312 7.39965 13.4 7.66845 13.4 7.99965C13.4 8.33085 13.1312 8.59965 12.8 8.59965Z" 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the ironies of automation\\\",\\\"url\\\":\\\"https://incident.io/building-with-ai/avoiding-the-ironies-of-automation\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"name\\\":\\\"Chris Evans\\\"}],\\\"datePublished\\\":\\\"2025-03-26T09:11:45.954Z\\\",\\\"dateModified\\\":\\\"2025-03-26T09:11:45.954Z\\\",\\\"image\\\":[\\\"https://cdn.sanity.io/images/oqy5aexb/production/3758aedd77a719f3afed170d122a6b24663f0185-2400x1350.png?w=2000\u0026fit=max\u0026auto=format\\\"],\\\"publisher\\\":{\\\"@type\\\":\\\"Organization\\\",\\\"name\\\":\\\"incident.io\\\",\\\"url\\\":\\\"https://incident.io\\\"},\\\"description\\\":\\\"Incidents happen when the normal playbook fails—so why would we let AI run them solo? Inspired by Bainbridge’s Ironies of automation, this post unpacks how AI can go wrong in high-stakes situations, and shares the principles guiding our approach to building tools that make humans sharper, not sidelined.\\\"}\"}}]],null],\"$L2c\",\"$L2d\",[\"$\",\"div\",null,{\"className\":\"relative mx-auto max-w-[1192px] max-xl:px-4 flex flex-col gap-12 md:gap-20 lg:pt-20\",\"style\":\"$undefined\",\"children\":[false,[[\"$\",\"$L2e\",null,{\"allPostsPath\":\"/building-with-ai\",\"post\":{\"_id\":\"4e233517-1529-47f4-86a7-24b68de5ae91\",\"_type\":\"aiblog\",\"authors\":[{\"avatar\":{\"_type\":\"image\",\"asset\":{\"_ref\":\"image-7971ec7063054a94ed2d9a96e15bf10cb25a3e8d-3397x3397-jpg\",\"_type\":\"reference\"}},\"bio\":[{\"_key\":\"d8a3d1a9e648\",\"_type\":\"block\",\"children\":[{\"_key\":\"d437416bd863\",\"_type\":\"span\",\"marks\":[],\"text\":\"I'm one of the co-founders, and Field CTO here at incident.io.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"bb3fda6e342f\",\"_type\":\"block\",\"children\":[{\"_key\":\"7c40bc31bbbe\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"3d5ca43c28d6\",\"_type\":\"block\",\"children\":[{\"_key\":\"ea3db9e4ae01\",\"_type\":\"span\",\"marks\":[],\"text\":\"Words here are my own, unless they get me in trouble, in which case they're all generated by AI.\"}],\"markDefs\":[],\"style\":\"normal\"}],\"id\":\"chris\",\"name\":\"Chris Evans\",\"title\":\"Co-Founder \u0026 Field CTO\"}],\"body\":[{\"_key\":\"729a7cd1ccf1\",\"_type\":\"block\",\"children\":[{\"_key\":\"bbf2865cad6e\",\"_type\":\"span\",\"marks\":[],\"text\":\"We're using AI to build an agentic product that works collaboratively \"},{\"_key\":\"068854a52e93\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"with\"},{\"_key\":\"72b0753f78f3\",\"_type\":\"span\",\"marks\":[],\"text\":\" responders to improve incident investigations and resolve incidents faster. A bold claim, I know, and I think pretty impressive to land the word “agentic” so early on—I promise it’s the last time I use it.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"ebed61c502b5\",\"_type\":\"block\",\"children\":[{\"_key\":\"f96a4b1b7a81\",\"_type\":\"span\",\"marks\":[],\"text\":\"After six months of digging into this, I’m convinced: AI in incident response won’t just be helpful—it’ll be essential. As more software is built \"},{\"_key\":\"a708c8bf7f25\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"with\"},{\"_key\":\"9be861b0acfe\",\"_type\":\"span\",\"marks\":[],\"text\":\", and increasingly \"},{\"_key\":\"8f678d3383fa\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"by\"},{\"_key\":\"c35be72792b9\",\"_type\":\"span\",\"marks\":[],\"text\":\", AI, responders will have less and less context about the systems they’re operating. That shrinking understanding—combined with the ever-growing volume of software—only increases the need for tools that can assist.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"a785e709e05d\",\"_type\":\"block\",\"children\":[{\"_key\":\"2aa2049b2f98\",\"_type\":\"span\",\"marks\":[],\"text\":\"Done right, there's a huge upside in this approach too—faster incident resolution, reduced customer impact, and less cognitive burden on the folks putting out the fires.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"d954313c5dc6\",\"_type\":\"block\",\"children\":[{\"_key\":\"0d08ba4313cf\",\"_type\":\"span\",\"marks\":[],\"text\":\"But with more automation comes a new shape of risk—much of which is captured in Lisanne Bainbridge’s 1983 paper, \"},{\"_key\":\"527794229699\",\"_type\":\"span\",\"marks\":[\"em\",\"8f5d135bbe4f\"],\"text\":\"Ironies of automation\"},{\"_key\":\"6ed759896c49\",\"_type\":\"span\",\"marks\":[],\"text\":\". In the paper, Bainbridge explains that automation meant to help can paradoxically make things harder. As routine tasks get automated, human skills fade from lack of practice, so when the system fails (and they will!), responders are left underprepared and out of context.\"}],\"markDefs\":[{\"_key\":\"8f5d135bbe4f\",\"_type\":\"link\",\"autoDownloadFile\":false,\"displayMode\":\"normal\",\"href\":\"http://www.complexcognition.co.uk/2021/06/ironies-of-automation.html\",\"openInNewWindow\":true}],\"style\":\"normal\"},{\"_key\":\"c24671464b1d\",\"_type\":\"block\",\"children\":[{\"_key\":\"face1363e787\",\"_type\":\"span\",\"marks\":[],\"text\":\"Working in tech companies, I’m yet to see these risks materialise seriously, but there are definite elements of truth here. 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Their manual flying skills and diagnostic abilities had degraded through reliance on automation, leaving them tragically underprepared for this critical scenario.\"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"92f71bc1644a\",\"_type\":\"block\",\"children\":[{\"_key\":\"b71a7abafbc6\",\"_type\":\"span\",\"marks\":[],\"text\":\"At the core, I see incidents as a \"},{\"_key\":\"803acbfd9859\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"fundamentally human activity\"},{\"_key\":\"4b0ba015bb06\",\"_type\":\"span\",\"marks\":[],\"text\":\". They’re what happens when all of your preventative controls have failed, leaving you entirely outside the world of normal operation. So when I think about automation in incidents, it makes no sense to me that we’d be looking to replace humans. The only sensible mode of operation is one where humans and machines cooperate to reach a resolution.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"94ac1286a2db\",\"_type\":\"block\",\"children\":[{\"_key\":\"a4efe1026541\",\"_type\":\"span\",\"marks\":[],\"text\":\"The risk of being too smart, too soon\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-the-risk-of-being-too-smart-too-soon\",\"slug\":\"the-risk-of-being-too-smart-too-soon\"}],\"style\":\"h2\"},{\"_key\":\"f04d92d276a7\",\"_type\":\"block\",\"children\":[{\"_key\":\"4e6247aefc9b\",\"_type\":\"span\",\"marks\":[],\"text\":\"Before going any further, I want to touch on a few ideas from Bainbridge’s paper that feel especially relevant when we think about automation in incident response.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"88fe19309610\",\"_type\":\"block\",\"children\":[{\"_key\":\"097d806a473f\",\"_type\":\"span\",\"marks\":[],\"text\":\"Let’s start with what I’d consider to be an \"},{\"_key\":\"d37e6b022cf7\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"over-automated\"},{\"_key\":\"fefbae85cced\",\"_type\":\"span\",\"marks\":[],\"text\":\" vision of the future—where AI tries to take over \"},{\"_key\":\"9e0cd37b43ae\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"critical work\"},{\"_key\":\"0ca8580641bc\",\"_type\":\"span\",\"marks\":[],\"text\":\" and decision-making from human responders. That’s a subjective line, sure, but an easy one to spot when you look at real examples.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"764656b4a8c1\",\"_type\":\"block\",\"children\":[{\"_key\":\"20e4c8fb9934\",\"_type\":\"span\",\"marks\":[],\"text\":\"Driving the incident \"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-driving-the-incident-\",\"slug\":\"driving-the-incident-\"}],\"style\":\"h3\"},{\"_key\":\"f77f93578bc4\",\"_type\":\"block\",\"children\":[{\"_key\":\"89aecdee859f\",\"_type\":\"span\",\"marks\":[],\"text\":\"Bainbridge actually calls this out directly. 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The rationale? A recent software change might be causing instability, and a reboot fixed it the last few times this kind of issue happened. \\n\\nYou hit confirm—because it’s 3am, you’re tired, and hey, the AI seems confident. \\n\\nExcept… the issue wasn’t caused by the new release. It was a noisy-but-harmless log storm triggered by a recent feature flag toggle. The reboot interrupts real customer traffic, kicks off alerts across regions, and suddenly you’ve turned a minor hiccup into a cross-regional mess. \\n\\nThe AI didn’t make the wrong call—it made a \"},{\"_key\":\"c6af9e2b0541\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"reasonable\"},{\"_key\":\"ae38507d9bf8\",\"_type\":\"span\",\"marks\":[],\"text\":\" one, based on limited context. The problem is, you acted like a glorified button-clicker instead of a thinking responder. That’s when judgement, context, and that gut-level “wait a second…” instinct go out the window. \\n\\nA slightly exaggerated example, granted, but it’s easy to see how a confident AI and a tired human can to drift into a world of human’s rubber-stamping decisions they didn’t actually make. \"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"52082e460858\",\"_type\":\"block\",\"children\":[{\"_key\":\"680cd8a516e5\",\"_type\":\"span\",\"marks\":[],\"text\":\"Owning public communication \"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-owning-public-communication-\",\"slug\":\"owning-public-communication-\"}],\"style\":\"h3\"},{\"_key\":\"4baef1b45ab4\",\"_type\":\"block\",\"children\":[{\"_key\":\"bec23124a11f\",\"_type\":\"span\",\"marks\":[],\"text\":\"In a world where AI can write convincing human-like text, it’s tempting to delegate responsibility to an automated system to have it update a status page or send Slack messages to execs. But tone, timing, and nuance matter. Too many updates cause panic. Too few erode trust. Communication during incidents is part judgment, part empathy—still very much human territory. \\n\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"ff22e4dac2d8\",\"_type\":\"callout\",\"body\":[{\"_key\":\"fe5a39b4fcf7\",\"_type\":\"block\",\"children\":[{\"_key\":\"612df6027ef3\",\"_type\":\"span\",\"marks\":[],\"text\":\" 📢 \"},{\"_key\":\"61a66e3da1ef\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Good intentions, bad broadcast\"},{\"_key\":\"92c631126775\",\"_type\":\"span\",\"marks\":[],\"text\":\" \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"265e5cd8ac20\",\"_type\":\"block\",\"children\":[{\"_key\":\"bdad8a242190\",\"_type\":\"span\",\"marks\":[],\"text\":\"An incident kicks off. Services are falling over, people are scrambling, and your trusty AI companion jumps into action: it posts to the status page, triggering a number of subscribes to get updates via email. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"ca8f3105a0e2\",\"_type\":\"block\",\"children\":[{\"_key\":\"0577a0db4d68\",\"_type\":\"span\",\"marks\":[],\"text\":\"Problem is… it doesn’t quite have the full picture. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"639896536bc4\",\"_type\":\"block\",\"children\":[{\"_key\":\"5a776b4e893a\",\"_type\":\"span\",\"marks\":[],\"text\":\"It mentions “data loss” based on an ambiguous log line. And then, just to keep the chaos rolling, it goes silent for three hours while humans are heads-down fixing things—leaving customers, execs, and half of LinkedIn assuming the company has fallen into the sea. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"20f7d73b91e1\",\"_type\":\"block\",\"children\":[{\"_key\":\"b310716161cc\",\"_type\":\"span\",\"marks\":[],\"text\":\"Technically, the AI did what it was told: communicate. But without human judgment around tone, timing, and what \"},{\"_key\":\"276e626e532f\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"not\"},{\"_key\":\"7837d2a07d91\",\"_type\":\"span\",\"marks\":[],\"text\":\" to say, it turned a tricky situation into a reputational mess. \"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"fbe74b19ea55\",\"_type\":\"block\",\"children\":[{\"_key\":\"d096d746f8ff\",\"_type\":\"span\",\"marks\":[],\"text\":\"Triggering mitigating actions\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-triggering-mitigating-actions\",\"slug\":\"triggering-mitigating-actions\"}],\"style\":\"h3\"},{\"_key\":\"524f194b05ac\",\"_type\":\"block\",\"children\":[{\"_key\":\"b55d169eecf1\",\"_type\":\"span\",\"marks\":[],\"text\":\"Automatically restarting services or flipping traffic sounds like an SRE’s dream. But when things go wrong, they \"},{\"_key\":\"921ed92429f5\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"really\"},{\"_key\":\"032d8711b39d\",\"_type\":\"span\",\"marks\":[],\"text\":\" go wrong—and mitigation can end up being more destructive than the original issue. Until systems have the full context their human counterparts do, the ability to take consequential actions should be treated with caution. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"806a960dcf0d\",\"_type\":\"callout\",\"body\":[{\"_key\":\"d95a5d122633\",\"_type\":\"block\",\"children\":[{\"_key\":\"dbedd29399e3\",\"_type\":\"span\",\"marks\":[],\"text\":\"🔥 \"},{\"_key\":\"f07b48b23696\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"From graceful degradation to total meltdown\"},{\"_key\":\"9c480dba6022\",\"_type\":\"span\",\"marks\":[],\"text\":\" \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"4643ba4c8cc9\",\"_type\":\"block\",\"children\":[{\"_key\":\"9b96e53296bc\",\"_type\":\"span\",\"marks\":[],\"text\":\"Traffic to a dashboard page is spiking, and CPU usage on its backing services is climbing fast. But the team’s not worried—they know it’s the result of a marketing email. The load is expected, and the service is degrading gracefully. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"6ada97af00fd\",\"_type\":\"block\",\"children\":[{\"_key\":\"cd88322431cc\",\"_type\":\"span\",\"marks\":[],\"text\":\"The AI, lacking that context, decides to scale up the service. Sounds helpful—until the shared database gets overwhelmed, and the whole product goes offline. What started as a manageable situation just became a full-blown outage. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"30376e706fe3\",\"_type\":\"block\",\"children\":[{\"_key\":\"d06c93aeaad6\",\"_type\":\"span\",\"marks\":[],\"text\":\"The AI made a reasonable decision based on what it knew. But without the surrounding context—why the traffic was spiking, how the service handles load, the impact on shared infrastructure—it turned a non-problem into a disaster. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c9d1c43186dc\",\"_type\":\"block\",\"children\":[{\"_key\":\"f72b4d6698e4\",\"_type\":\"span\",\"marks\":[],\"text\":\"A slightly reductive example as autoscaling is a well-established practice. But it’s a good illustration of how automation, without guardrails or context, can easily go a step too far.\"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"ac9a2f33391a\",\"_type\":\"block\",\"children\":[{\"_key\":\"5bc7c179e4de\",\"_type\":\"span\",\"marks\":[],\"text\":\"In the paper, Bainbridge poses two key questions that automation designers should wrestle with:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"017dd2060a4a\",\"_type\":\"block\",\"children\":[{\"_key\":\"3c1ce4a91b7a\",\"_type\":\"span\",\"marks\":[],\"text\":\"What happens when the automation fails?\"}],\"level\":1,\"listItem\":\"number\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"18c897fa76a0\",\"_type\":\"block\",\"children\":[{\"_key\":\"bfebc0753bb9\",\"_type\":\"span\",\"marks\":[],\"text\":\"How does automation change the way people work?\"}],\"level\":1,\"listItem\":\"number\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f7c125a9947e\",\"_type\":\"block\",\"children\":[{\"_key\":\"48a123a8d40a\",\"_type\":\"span\",\"marks\":[],\"text\":\"In incident response, effectiveness comes from \"},{\"_key\":\"76c7890cbad0\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"repetition, exposure, and experience\"},{\"_key\":\"f436e2580e6e\",\"_type\":\"span\",\"marks\":[],\"text\":\". People get better over time by seeing unusual and surprising failures, talking through trade-offs, and building up mental models of how systems behave. If automation quietly takes all that away, we lose opportunities for growth, learning, and curiosity.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"dd87f7808955\",\"_type\":\"block\",\"children\":[{\"_key\":\"ec9eaf8542c1\",\"_type\":\"span\",\"marks\":[],\"text\":\"And that’s the real long-term risk: a future where incidents are “handled” by machines, responders disengage, local knowledge fades, and no one wants to supervise a machine solving problems they don’t understand. And when automation breaks you’ll be relying on humans whose skills have quietly eroded, right when you need them most.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"9b2a3dc2db1b\",\"_type\":\"block\",\"children\":[{\"_key\":\"244f2e9f0647\",\"_type\":\"span\",\"marks\":[],\"text\":\"Flipping the paradox with a cooperative agent\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-flipping-the-paradox-with-a-cooperative-agent\",\"slug\":\"flipping-the-paradox-with-a-cooperative-agent\"}],\"style\":\"h2\"},{\"_key\":\"fb372e6e4360\",\"_type\":\"block\",\"children\":[{\"_key\":\"4d5837f9ec3a\",\"_type\":\"span\",\"marks\":[],\"text\":\"Fortunately it’s not all doom-and-gloom. I believe there’s a bright future for AI automation in incident response. As someone building it I would say that, of course, but setting aside the obvious incentives and biases it’s something I truly believe.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"40a87f00c50e\",\"_type\":\"block\",\"children\":[{\"_key\":\"1f3f599cb9d1\",\"_type\":\"span\",\"marks\":[],\"text\":\"I think success lies in a few key principles that shape both the technical implementation and the overall interaction model (i.e. the UX) of the system. When we talk about what we're building internally, we're firmly anchored to the notion of cooperative agent rather than replacement for work. The vibe we're aiming for is \\\"your best engineer in every incident\\\", where \"},{\"_key\":\"3c09674bcbdc\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"best\"},{\"_key\":\"dbf76f64c928\",\"_type\":\"span\",\"marks\":[],\"text\":\" covers both technical and social excellence. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"af323fc8e22f\",\"_type\":\"block\",\"children\":[{\"_key\":\"579b73afb70f\",\"_type\":\"span\",\"marks\":[],\"text\":\"Here’s how I think about the “good future”...\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c414de5be0b9\",\"_type\":\"block\",\"children\":[{\"_key\":\"9e0974f0c134\",\"_type\":\"span\",\"marks\":[],\"text\":\"Augmentation, not replacement\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-augmentation-not-replacement\",\"slug\":\"augmentation-not-replacement\"}],\"style\":\"h3\"},{\"_key\":\"5f215c56ac78\",\"_type\":\"block\",\"children\":[{\"_key\":\"38136be72709\",\"_type\":\"span\",\"marks\":[],\"text\":\"incident.io will not automate away critical human decision-making. Our goal is to strengthen it with humans remaining central, and AI tools providing supportive context. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"87e9f5c77670\",\"_type\":\"block\",\"children\":[{\"_key\":\"39ce3cbfd4b0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Practically speaking, we repeatedly ask ourselves the questions “what would we want an experienced human collaborator to do here?”. Rarely do you draft in extra people only for them to take over and leave you on the sidelines. Our agents should act similarly.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"8a8af65fa80a\",\"_type\":\"callout\",\"body\":[{\"_key\":\"fa40258d9e49\",\"_type\":\"block\",\"children\":[{\"_key\":\"80cc46b52e52\",\"_type\":\"span\",\"marks\":[],\"text\":\"❌ I’ve reverted the PR and hotfixed it in production\\n\\n✅ This PR (#2709) was merged just before this incident. 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As we build out our cooperative automation, trust is one of the biggest hurdles we face, and we believe transparency is the way through it. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"0e3674f03f7d\",\"_type\":\"block\",\"children\":[{\"_key\":\"69fc3e4b7550\",\"_type\":\"span\",\"marks\":[],\"text\":\"Just like with a human teammate, we’re far more willing to forgive a bad call if we can understand the reasoning behind it. When our agent reaches a conclusion, it will show its working: what it looked at, why it thinks it’s relevant, and where there’s uncertainty. No “just trust me” vibes.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"9c19ca2c5a64\",\"_type\":\"callout\",\"body\":[{\"_key\":\"8898d2827eb1\",\"_type\":\"block\",\"children\":[{\"_key\":\"f857b10138a6\",\"_type\":\"span\",\"marks\":[],\"text\":\"❌ Service-X is the problem. Click here to page them.\\n\\n✅ From this graph, it looks like error rates are spiking in service-X. The logs show an uptick in ‘timeout’ errors starting at 14:23, which coincides with this config change. If that looks correct, you can page the team by clicking below.\"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"b7aea5d22139\",\"_type\":\"block\",\"children\":[{\"_key\":\"fef6044bf80b\",\"_type\":\"span\",\"marks\":[],\"text\":\"Encouraging active engagement \"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-encouraging-active-engagement-\",\"slug\":\"encouraging-active-engagement-\"}],\"style\":\"h3\"},{\"_key\":\"054eef0caa65\",\"_type\":\"block\",\"children\":[{\"_key\":\"649c7ea8871a\",\"_type\":\"span\",\"marks\":[],\"text\":\"We want responders to stay actively involved, not fall into the trap of deferring to the AI just because it sounds confident. That means keeping humans in the loop—and responsible—when it comes to meaningful decisions. Language and UX matter a lot here. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"28edae7bc213\",\"_type\":\"block\",\"children\":[{\"_key\":\"edf9b12b2be9\",\"_type\":\"span\",\"marks\":[],\"text\":\"We aim to be loud enough to offer useful input, but quiet enough not to bulldoze the conversation or imply there's a single \\\"correct\\\" path. Our goal is to present credible theories, relevant data, and paths worth exploring—\"},{\"_key\":\"f86400f06910\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"not\"},{\"_key\":\"db8905204358\",\"_type\":\"span\",\"marks\":[],\"text\":\" to steer people into autopilot mode.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"80e51705b545\",\"_type\":\"callout\",\"body\":[{\"_key\":\"99cdb29132b7\",\"_type\":\"block\",\"children\":[{\"_key\":\"c7982c8b6c7d\",\"_type\":\"span\",\"marks\":[],\"text\":\"❌ This is a regression from PR #456.\\n\\n✅ One possibility: PR #456 modified retry logic in this area. I could be worth checking if that’s related?\"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"234efbf38bbd\",\"_type\":\"block\",\"children\":[{\"_key\":\"3b9b333ce98b\",\"_type\":\"span\",\"marks\":[],\"text\":\"Using incidents as a learning mechanism \"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-using-incidents-as-a-learning-mechanism-\",\"slug\":\"using-incidents-as-a-learning-mechanism-\"}],\"style\":\"h3\"},{\"_key\":\"48877c21c8b7\",\"_type\":\"block\",\"children\":[{\"_key\":\"1944e3584e27\",\"_type\":\"span\",\"marks\":[],\"text\":\"Humans aren’t great at trawling through piles of incident data to spot patterns—but machines are. Our goal is to surface the right context at the right time, helping responders build and refine their mental models in real time. \"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"dc080ed17908\",\"_type\":\"block\",\"children\":[{\"_key\":\"9b70193456e0\",\"_type\":\"span\",\"marks\":[],\"text\":\"By handling the retrieval, synthesis, and pattern-matching, our tools free responders up to focus on the hard stuff: making judgement calls, thinking strategically, asking “what now?” Ironically, the more context we surface, the sharper responders become.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"478a78702ccf\",\"_type\":\"callout\",\"body\":[{\"_key\":\"97a1479a8d45\",\"_type\":\"block\",\"children\":[{\"_key\":\"17fc776cece1\",\"_type\":\"span\",\"marks\":[],\"text\":\"❌ This alert has fired 12 times in the past.\\n\\n✅ This alert fired during incidents in Feb and Oct last year—both related to queue backlogs in service-X after deploys. Might be worth checking if that’s happening again. See INC-2412 and INC-2508 for more details.\"}],\"markDefs\":[],\"style\":\"normal\"}],\"displayMode\":\"\",\"markDefs\":null},{\"_key\":\"1aa011de9752\",\"_type\":\"horizontalRule\",\"markDefs\":null,\"style\":\"solid\"},{\"_key\":\"35f2603ca991\",\"_type\":\"block\",\"children\":[{\"_key\":\"b9351633cdb8\",\"_type\":\"span\",\"marks\":[],\"text\":\"Building the next generation of incident response\"}],\"markDefs\":[{\"_type\":\"slug\",\"_key\":\"slug-building-the-next-generation-of-incident-response\",\"slug\":\"building-the-next-generation-of-incident-response\"}],\"style\":\"h2\"},{\"_key\":\"c4b50dd71d1d\",\"_type\":\"block\",\"children\":[{\"_key\":\"e37df98915e8\",\"_type\":\"span\",\"marks\":[],\"text\":\"Automation ironies show up when humans become passive, unskilled observers. And if your goal is to take meaningful work away from responders during incidents, you'd have a legitimate case for those issues showing up. But that’s not what we’re building.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"a623003aa30e\",\"_type\":\"block\",\"children\":[{\"_key\":\"4c839ea4c33b\",\"_type\":\"span\",\"marks\":[],\"text\":\"We expect humans to stay deeply involved—working alongside the machine to gather context, explore problems, form hypotheses, and choose sensible paths to resolution. Lofty claims, sure—but ones we believe we’ll ship in the next few months.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"398b42a79903\",\"_type\":\"block\",\"children\":[{\"_key\":\"d68f8f17ce67\",\"_type\":\"span\",\"marks\":[],\"text\":\"Bainbridge’s paper calls out critical pitfalls in automation. 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