{"id":738,"date":"2026-06-25T19:13:41","date_gmt":"2026-06-25T19:13:41","guid":{"rendered":"https:\/\/sites.clarkson.edu\/ai-institute\/workbench\/lean\/lean-talks\/"},"modified":"2026-06-26T20:16:26","modified_gmt":"2026-06-26T20:16:26","slug":"lean-talks","status":"publish","type":"page","link":"https:\/\/sites.clarkson.edu\/ai-institute\/workbench\/lean\/lean-talks\/","title":{"rendered":"Lean Talks"},"content":{"rendered":"\n<div class=\"lt\"><div class=\"lt-hero\"><a class=\"lt-bw\" href=\"https:\/\/sites.clarkson.edu\/ai-institute\/workbench\/lean\/\">&larr; Lean-AI Praxis<\/a><div class=\"lt-eyebrow\">Lean-AI Praxis &middot; Talks<\/div><h1>Lean Talks<\/h1><p class=\"lt-lead\">Talks and lectures for people building with AI the lean way &mdash; where value comes not from producing more output, but from <b>governing, reviewing, and being able to trust it<\/b>.<\/p><\/div><article class=\"lt-talk\"><div class=\"lt-video\"><iframe src=\"https:\/\/www.youtube.com\/embed\/UwHX5qRdi0U\" title=\"Software at Machine Speed \u2014 Pat Wilbur\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe><\/div><div class=\"lt-body\"><h2>Software at Machine Speed: How AI Accelerates Cybersecurity Risk and What It Foreshadows for Software Development<\/h2><div class=\"lt-speaker\">Pat Wilbur &middot; Instructor, Clarkson University<\/div><p>How is AI changing cybersecurity? How has it already transformed software engineering? And what new responsibilities do computer scientists, software engineers, and technology organizations face as AI systems become more autonomous?<\/p><p>The talk begins with a brief look back at &ldquo;classical&rdquo; zero-day defense &mdash; anomaly detection, attack-surface reduction, instrumentation, and layered controls &mdash; then argues that AI changes the risk environment by collapsing the cost of trial and error. Drawing on Anthropic&rsquo;s reported Mythos results and Nicholas Carlini&rsquo;s &ldquo;Black Hat LLMs,&rdquo; it considers how frontier models may find critical vulnerabilities, generate multi-stage exploits, support privilege escalation, and enable non-experts to perform security work that once required elite expertise.<\/p><p>It then broadens to the future of software development: as AI moves from prompt-based assistance toward autonomous agents, code production may no longer be the main bottleneck &mdash; governance, testing, security review, attribution, rollback, and recoverability become central. It closes on AI attribution practices, including emerging Linux kernel guidelines, as one way to target human review and rescan AI-assisted code as models improve.<\/p><div class=\"lt-lens\"><b>The lean lens:<\/b> as AI collapses the cost of producing code, the bottleneck moves downstream &mdash; to review, governance, and trust. That is exactly where lean thinking concentrates: not on producing more, but on flow, quality, and the slowest, most valuable step.<\/div><details class=\"lt-tr\"><summary>Read the transcript<\/summary><div class=\"body\"><p>Classically speaking &mdash; and it&rsquo;s funny to use that term, because I usually use &ldquo;classic&rdquo; to mean decades ago, but I guess classically means a few years ago in the context of security, and especially AI.<\/p><p>Classically, the best way to defend against a zero-day vulnerability would be, in my opinion, to instrument the system so that you can detect when one occurs. Hopefully you can detect anomalies &mdash; maybe based on the resources used on a system: spikes in CPU, spikes in disk activity, spikes in network activity, strange accesses to files.<\/p><p>That&rsquo;s a detection mechanism, so that you can respond after the fact &mdash; and also to have multiple layers of security to mitigate the potential attack vectors. The idea behind multiple layers is that in each layer there&rsquo;s some probability a zero-day vulnerability could occur &mdash; meaning some black hat or hacker discovers, sometime after it was introduced, that there&rsquo;s a vulnerability in the system &mdash; and they start attacking it.<\/p><p class=\"note\"><em>Excerpt from the opening of the talk.<\/em><\/p><\/div><\/details><a class=\"lt-watch\" href=\"https:\/\/youtu.be\/UwHX5qRdi0U\" target=\"_blank\" rel=\"noopener noreferrer\">Watch on YouTube &rarr;<\/a><\/div><\/article><div class=\"lt-foot\"><a href=\"https:\/\/sites.clarkson.edu\/ai-institute\/workbench\/lean\/\">&larr; Lean-AI Praxis<\/a><a href=\"https:\/\/sites.clarkson.edu\/ai-institute\/workbench\/teach\/\">Teaching &amp; Learning<\/a><\/div><\/div>\n<style class=\"advgb-styles-renderer\">\nheader.entry-header{display:none!important}\n.lt{font-family:Georgia,\"Times New Roman\",serif;color:#17212b;line-height:1.6;max-width:1000px;margin:0 auto;padding:0 22px 90px}\n.lt *{box-sizing:border-box}\n.lt-hero{background:linear-gradient(165deg,#0b3a30 0%,#04231c 76%),#04231c;color:#fff;margin:0 -22px;padding:34px 52px 50px;position:relative;overflow:hidden}\n.lt-hero:before{content:\"\";position:absolute;inset:0;background:radial-gradient(800px 320px at 80% -20%,rgba(255,205,0,0.16),transparent 60%);pointer-events:none}\n.lt-hero>*{position:relative}\n.lt-bw{display:inline-flex;align-items:center;gap:7px;font:600 12.5px\/1 Arial,Helvetica,sans-serif;color:rgba(255,255,255,0.82);text-decoration:none;margin:0 0 22px}\n.lt-bw:hover{color:#ffcd00}\n.lt-eyebrow{font:700 12px\/1 Arial,Helvetica,sans-serif;letter-spacing:.2em;text-transform:uppercase;color:#ffcd00;margin:0 0 14px}\n.lt-hero h1{font:400 46px\/1.04 Georgia,serif;color:#fff;margin:0 0 12px;letter-spacing:-.01em}\n.lt-lead{font:400 19px\/1.55 Georgia,serif;color:#e7f0ec;max-width:720px;margin:0}\n.lt-lead b{color:#ffcd00;font-weight:400}\n.lt-talk{margin-top:40px;border:1px solid #e7e3dd;border-radius:16px;overflow:hidden;background:#fff}\n.lt-video{position:relative;padding-bottom:56.25%;height:0;background:#000}\n.lt-video iframe{position:absolute;top:0;left:0;width:100%;height:100%;border:0}\n.lt-body{padding:26px 30px 30px}\n.lt-body h2{font:400 26px\/1.2 Georgia,serif;color:#004e42;margin:0 0 6px}\n.lt-speaker{font:600 13px\/1.3 Arial,Helvetica,sans-serif;letter-spacing:.02em;color:#7a6f63;text-transform:uppercase;margin:0 0 16px}\n.lt-body p{font:400 16.5px\/1.7 Georgia,serif;color:#2b3742;margin:0 0 14px}\n.lt-lens{background:#f3f6f1;border-left:4px solid #ffcd00;border-radius:10px;padding:14px 18px;margin:6px 0 18px;font:400 15.5px\/1.6 Georgia,serif;color:#3a4750}\n.lt-lens b{color:#004e42}\n.lt-tr{margin:8px 0 18px;border-top:1px solid #ececec;padding-top:14px}\n.lt-tr summary{cursor:pointer;font:600 14px\/1.3 Arial,Helvetica,sans-serif;color:#004e42}\n.lt-tr .body{margin-top:12px;font:400 15px\/1.7 Georgia,serif;color:#2b3742}\n.lt-tr .note{font-size:13px;color:#6e6259}\n.lt-watch{display:inline-block;background:#004e42;color:#fff;font:700 13px\/1 Arial,Helvetica,sans-serif;padding:13px 19px;border-radius:8px;text-decoration:none;transition:transform .15s,box-shadow .15s}\n.lt-watch:hover{transform:translateY(-1px);box-shadow:0 0 14px rgba(255,205,0,.5)}\n.lt-foot{margin-top:42px;border-top:1px solid #e7e3dd;padding-top:20px;display:flex;gap:22px;flex-wrap:wrap}\n.lt-foot a{font:600 13px\/1 Arial,Helvetica,sans-serif;color:#004e42;text-decoration:none}\n@media (max-width:760px){.lt-hero{padding:26px 24px 38px}.lt-hero h1{font-size:32px}.lt-lead{font-size:17px}.lt-body{padding:20px 20px 24px}}\n<\/style>","protected":false},"excerpt":{"rendered":"<p>&larr; Lean-AI Praxis Lean-AI Praxis &middot; Talks Lean Talks Talks and lectures for people building with AI the lean way &mdash; where value comes not from producing more output, but from governing, reviewing, and being able to trust it. Software at Machine Speed: How AI Accelerates Cybersecurity Risk and What It Foreshadows for Software Development [&hellip;]<\/p>\n","protected":false},"author":256,"featured_media":0,"parent":253,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"class_list":["post-738","page","type-page","status-publish","hentry"],"coauthors":[],"author_meta":{"author_link":"https:\/\/sites.clarkson.edu\/ai-institute\/author\/scasper\/","display_name":"scasper"},"relative_dates":{"created":"Posted 2 months ago","modified":"Updated 2 months ago"},"absolute_dates":{"created":"Posted on June 25, 2026","modified":"Updated on June 26, 2026"},"absolute_dates_time":{"created":"Posted on June 25, 2026 7:13 pm","modified":"Updated on June 26, 2026 8:16 pm"},"featured_img_caption":"","featured_img":false,"series_order":"","_links":{"self":[{"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/pages\/738","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/users\/256"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/comments?post=738"}],"version-history":[{"count":1,"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/pages\/738\/revisions"}],"predecessor-version":[{"id":757,"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/pages\/738\/revisions\/757"}],"up":[{"embeddable":true,"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/pages\/253"}],"wp:attachment":[{"href":"https:\/\/sites.clarkson.edu\/ai-institute\/wp-json\/wp\/v2\/media?parent=738"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}