{"id":192917,"date":"2025-11-21T17:12:14","date_gmt":"2025-11-21T17:12:14","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/192917\/"},"modified":"2025-11-21T17:12:14","modified_gmt":"2025-11-21T17:12:14","slug":"qconsf-2025-humans-in-the-loop-engineering-leadership-in-a-chaotic-industry","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/192917\/","title":{"rendered":"QConSF 2025: Humans in the Loop: Engineering Leadership in a Chaotic Industry"},"content":{"rendered":"

At QCon San Francisco 2025<\/a>, Michelle Brush<\/a>, engineering director of Site Reliability Engineering (SRE) at Google, delivered the closing keynote \u201cHumans in the Loop: Engineering Leadership in a Chaotic Industry\u201d<\/a> on November 19, 2025. Speaking to a room of software leaders, she explored the broader changes underway in software engineering, systems thinking, and leadership through complexity.<\/p>\n

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She opened by acknowledging the uncertainty that many practitioners feel, affirming that this was a shared experience and an expected part of navigating today\u2019s technological landscape. Brush, who contributed two chapters to \u201c97 Things Every SRE Should Know\u201d<\/a>, argued that the nature of software engineering work is shifting, not disappearing. She noted that she had explored similar themes in an earlier keynote at the InfoQ Dev Summit in Boston<\/a>, and stressed that as AI systems automate pieces of software development, engineers will face harder and more complex challenges.<\/p>\n


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\u201cLarge language models are, by their nature, unconsciously competent\u2014they know a lot, but they can\u2019t explain it. When they hallucinate, that\u2019s just the model being unconsciously incompetent for a moment and filling in the blanks with something that sounds plausible.\u201d<\/p>\n

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Citing Lisanne Bainbridge\u2019s classic paper \u201cIronies of Automation\u201d<\/a>, she explained that \u201cwhen you automate some piece of work, the job that you leave behind for humans to do is actually harder.\u201d The result is a landscape where engineers must monitor, debug, and validate automated systems, even as their direct responsibilities evolve.<\/p>\n

She illustrated this point with a simple analogy: \u201cDishwashers are great\u2026 but we didn\u2019t get rid of all the work.\u201d While machines may handle routine tasks, humans are left with responsibility for exception handling, quality assurance, and system maintenance. In software, this translates into higher-level abstraction work, deeper troubleshooting, and a reliance on engineering judgment. \u201cOur brains are going to start working on higher and higher abstractions,\u201d she said, emphasizing the cognitive shift required in modern development.<\/p>\n

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Brush explained that large language models (LLMs) today operate with a kind of \u201cunconscious competence.\u201d They can produce impressive results but lack explainability and awareness of their limitations. \u201cThey don\u2019t know what they don\u2019t know,\u201d she said, framing hallucinations as a natural byproduct of this architecture. By contrast, humans sit in the space of \u201cconscious competence\u201d\u2014we understand what we know and can explain it, which is essential for teaching, mentoring, and validating machine outputs.<\/p>\n

A central concept in her talk was the importance of \u201cchunking,\u201d or cognitive encapsulation, as engineers deal with increasing complexity. She argued that the ability to move between abstraction layers\u2014while still being able to drill into the underlying systems\u2014is crucial. \u201cAll abstractions leak,\u201d she reminded the audience, \u201cespecially our hardware abstractions.\u201d<\/p>\n


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\u201cDishwashers are great; we love them. But we didn\u2019t get rid of all the work\u2014now we have to know when the dishwasher is done, check whether every dish is actually clean, debug why it isn\u2019t, and sometimes become amateur dishwasher repair technicians.\u201d<\/p>\n

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She connected these themes to the current economic and hardware landscape: the end of zero-interest rates, renewed cost pressure, and fierce competition for specialized AI hardware such as GPUs and TPUs. Referencing Jevons\u2019 paradox<\/a>, Brush argued that as AI makes software development faster and cheaper, organizations will not do less engineering work but dramatically more\u2014and that leaders must use techniques like non-abstract system design and back-of-the-envelope modeling to understand the real compute, storage, and reliability costs of their architectures before they build them.<\/p>\n

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Brush went on to frame reliability and complexity management as core leadership responsibilities. Drawing on Richard Cook\u2019s essay \u201cHow Complex Systems Fail\u201d<\/a>, she described outages as emerging from hidden interactions in systems that are \u201cworking as designed,\u201d and advocated investing in generic mitigations\u2014safe rollbacks, traffic shedding, moving workloads off bad hardware, and other fast levers that restore service even when the exact failure mode is unknown. She closed by emphasizing experimentation, hypothesis-driven change, and deliberate mentoring and delegation as essential ways to grow the next generation of engineers who will have to operate these increasingly autonomous, opaque systems.<\/p>\n

Sharing a case study from Google, where the SRE organization has been evolving for more than two decades, Brush detailed a 2019 outage that brought down two data centers due to runaway automation. The assumption that geographic distribution was sufficient proved wrong when a third data center also failed under the load of recovery traffic. The takeaway? \u201cWe realized we needed to be in more than just three data centers,\u201d she said. The response involved not just more capacity, but smarter design\u2014using latency injection testing and intent-based rollout systems to surface risks before deployment and reflecting the lessons highlighted in resources like Google\u2019s \u201c20 Years of SRE\u201d retrospectives<\/a>.<\/p>\n

Developers looking to learn more can follow InfoQ\u2019s coverage of the event and watch for videos to appear in the coming weeks.<\/p>\n","protected":false},"excerpt":{"rendered":"At QCon San Francisco 2025, Michelle Brush, engineering director of Site Reliability Engineering (SRE) at Google, delivered the…\n","protected":false},"author":2,"featured_media":192918,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[74],"tags":[291,1705,289,7266,18,823,19,17,1946,14630,107394,90321,82],"class_list":{"0":"post-192917","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-technology","8":"tag-ai","9":"tag-architecture-design","10":"tag-artificial-intelligence","11":"tag-development","12":"tag-eire","13":"tag-google","14":"tag-ie","15":"tag-ireland","16":"tag-leadership","17":"tag-ml-data-engineering","18":"tag-qcon-engineering-leadership","19":"tag-qcon-san-francisco-2025","20":"tag-technology"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ie\/115588808911954115","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/192917","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=192917"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/192917\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/192918"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=192917"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=192917"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=192917"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}