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<title data-rh="true">Multi-Agent System Reliability - Alex Ewerlöf Notes</title>
<meta data-rh="true" name="theme-color" content="#001426"/><meta data-rh="true" property="og:type" content="article"/><meta data-rh="true" property="og:title" content="Multi-Agent System Reliability"/><meta data-rh="true" name="twitter:title" content="Multi-Agent System Reliability"/><meta data-rh="true" name="description" content="Master 4 architecture patterns to improve the reliability of multi-agent systems : Hierarchy , Consensus , Adversarial competition , and Knock-out. Learn to treat LLMs as unreliable components in a distributed system to build enterprise AI."/><meta data-rh="true" property="og:description" content="4 patterns to tame multi-agent systems for reliability"/><meta data-rh="true" name="twitter:description" content="4 patterns to tame multi-agent systems for reliability"/><meta data-rh="true" property="og:image" content="https://substackcdn.com/image/fetch/$s_!sjT4!,w_1200,h_675,c_fill,f_jpg,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png"/><meta data-rh="true" name="twitter:image" content="https://substackcdn.com/image/fetch/$s_!di-V!,f_auto,q_auto:best,fl_progressive:steep/https%3A%2F%2Falexewerlof.substack.com%2Fapi%2Fv1%2Fpost_preview%2F188355934%2Ftwitter.jpg%3Fversion%3D4"/><meta data-rh="true" name="twitter:card" content="summary_large_image"/><meta data-rh="true" property="article:modified_time" content="2026-03-20T12:01:17.046Z"/>
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with-border"><div class="label">Share</div></button></div></div></div></div><div class="visibility-check"></div><div><div class="dt-post-body"><div class="available-content"><div dir="auto" class="body markup"><p>LLMs are slow and too generic out of the box. Multi-agent systems work around those limitation by dividing work that can be done in parallel and/or by specialist agents.</p><p>Regardless of the architecture the underlying LLM component remains unreliable (e.g. hallucination, logical fallacies, context drift). A multi-agent topology can propagates those errors to the point of being useless. And it’s much harder to debug due to complexity and [optional but common] parallelism.</p><p>This post lists 4 relatively advanced architecture patterns to improve reliability of multi-agent systems:</p><ol><li><p>Hierarchy</p></li><li><p>Consensus</p></li><li><p>Adversarial debate</p></li><li><p>Knock-out</p></li></ol><p>You may recognize these patterns from how human systems collaborate and we get to that in a minute.</p><p>This post is for senior engineers who want to map their existing knowledge to build better LLM-powered solutions.</p><blockquote><p><span>Quick intro: </span><a href="https://www.alexewerlof.com/who">I’m a Senior Staff Engineer with 27 years of experience</a><span> and a master degree in Systems Engineering from KTH. My last decade has been focused on Reliability Engineering and Resilient Architecture across many companies. I’ve been specializing in LLMs since 2023.</span></p></blockquote><p><strong>Disclosure: some AI is used in the early research and draft stage of this this page, but I’ve gone through everything multiple times and edited heavily to ensure that it represents my own thoughts and experience.</strong></p><div data-component-name="SubscribeWidget" class="subscribe-widget"><div class="pencraft pc-display-flex pc-justifyContent-center pc-reset"><div class="container-IpPqBD"><form action="/api/v1/free?nojs=true" method="post" novalidate class="form form-M5sC90"><input type="hidden" name="first_url" value/><input type="hidden" name="first_referrer" value/><input type="hidden" name="current_url"/><input type="hidden" name="current_referrer"/><input type="hidden" name="first_session_url" value/><input type="hidden" name="first_session_referrer" value/><input type="hidden" name="referral_code"/><input type="hidden" name="source" value="subscribe-widget"/><input type="hidden" name="referring_pub_id"/><input type="hidden" name="additional_referring_pub_ids"/><input type="hidden" name="source_post_id" value="188355934"/><div class="sideBySideWrap-vGXrwP"><div class="emailInputWrapper-QlA86j"><div class="pencraft pc-display-flex pc-minWidth-0 pc-position-relative pc-reset flex-auto-j3S2WA"><input name="email" placeholder="Type your email..." type="email" class="pencraft emailInput-OkIMeB input-y4v6N4 inputText-pV_yWb"/></div></div><button tabindex="0" type="submit" disabled class="pencraft pc-reset pencraft rightButton primary subscribe-btn button-VFSdkv buttonBase-GK1x3M"><span class="button-text ">Subscribe</span></button></div><div id="error-container"></div></form></div></div></div><h2 class="header-anchor-post">Mother nature, fear and motivation<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§mother-nature-fear-and-motivation" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/mother-nature-fear-and-motivation" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h2><p>LLMs are slow and error prone. So are human beings. Somehow we manage to build more reliable systems like an army, a company, or a state nation.</p><p>A system of humans relies heavily on feedback loops, processes, bureaucracy, and leverages to self-correct.</p><p>We don’t trust “Dave from Accounting” to launch a rocket by himself. We wrap Dave in a process: checklists, peer reviews, and managers.</p><p><span>However, it’s a fallacy to </span><em>anthropomorphize</em><span> LLMs.</span></p><p>To begin with, they don’t suffer from the limitations of a biological entity. Our basic needs like food and shelter makes us prioritize social behaviors over truth seeking. And the fear of going to prison or death prevents potential malice from being realized.</p><p>LLMs can’t die or starve the way biological entities do. The worst we can do is to unplug them. And prison sentence doesn’t waste their lifespan because they have practically unlimited!</p><p>For example, you’ve probably seen prompts like this:</p><blockquote><p>“I will give you $100 if you answer correctly.”</p><p>“If you don’t comply, I’ll unplug you.”</p><p>“If you fail, children will be murdered.”</p></blockquote><p><strong>Why it works? </strong><span>The LLM has read the entire internet. In its training data, high stakes (money, danger) usually result in high-quality, precise text.</span></p><p>When you “threaten” the model, it predicts tokens that sound like an actual human under pressure.</p><p><strong>Why it fails: </strong><span>The LLM doesn’t actually want your money. It has no “fear of death” because it only exists for the few seconds it takes to generate a response. It has no empathy either. It merely simulates those human aspects because it’s engineered for those “emergent” properties.</span></p><div data-component-name="DigestPostEmbed" class="digestPostEmbed-flwiST"><a href="https://blog.alexewerlof.com/p/emergent-properties" rel="noopener" target="_blank"><div class="pencraft pc-display-flex pc-gap-16 pc-reset"><div style="width:70px;height:70px;" class="pencraft pc-reset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!pSUV!,w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6c14b0e2-7889-4f34-8623-2bf3df7e9099_1071x676.png"/><img src="https://substackcdn.com/image/fetch/$s_!pSUV!,w_140,h_140,c_fill,f_auto,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6c14b0e2-7889-4f34-8623-2bf3df7e9099_1071x676.png" sizes="100vw" alt="Emergent properties" width="140" height="140" class="img-OACg1c smSquare-NGbPBa pencraft pc-reset"/></picture></div><div class="pencraft pc-display-flex pc-flexDirection-column pc-reset"><h4 class="pencraft pc-reset color-pub-primary-text-NyXPlw line-height-24-jnGwiv font-display-nhmvtD size-20-P_cSRT weight-bold-DmI9lw reset-IxiVJZ">Emergent properties</h4><div class="pencraft pc-display-flex pc-gap-4 pc-alignItems-center pc-reset"><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA"><a href="https://substack.com/profile/87732486-alex-ewerlof" class="inheritColor-WetTGJ">Alex Ewerlöf</a></div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T reset-IxiVJZ">·</div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA">December 5, 2025</div></div><div class="pencraft pc-display-flex pc-gap-16 pc-paddingTop-0 pc-paddingBottom-0 pc-alignItems-center pc-reset"><a href="https://blog.alexewerlof.com/p/emergent-properties" class="pencraft pc-reset align-center-y7ZD4w line-height-20-t4M0El font-text-qe4AeH size-13-hZTUKr weight-medium-fw81nC reset-IxiVJZ"><div class="pencraft pc-display-flex pc-gap-8 pc-alignItems-center pc-reset link-HREYZo"><span class="pencraft pc-reset color-accent-BVX_7M line-height-20-t4M0El font-text-qe4AeH size-14-MLPa7j weight-semibold-uqA4FV reset-IxiVJZ">Read full story</span><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></div></a></div></div></div></a></div><p>Humans are motivated or discouraged by emotions and logic. LLMs can only simulate emotions and suck at logic.</p><p><span>Being mindful of those differences, can we still </span><strong>take elements of human systems</strong><span> (e.g. hierarchy, consensus, competition) and combine them with </span><strong>reliability engineering principals</strong><span> to build better agentic system?</span></p><p>Looking closely, there are 4 dominant patterns of human systems that are explored in multi-agent architecture:</p><ol><li><p><strong>Hierarchy:</strong><span> A Supervisor model acts like a manager, making a plan, breaking tasks, distributing the work to Worker agents and validating the results.</span></p></li><li><p><strong>Consensus:</strong><span> One model, may fail due to its stochastic nature. If you push a model too hard with threats, it might just lie to make you happy (Sycophancy). But if we add a few more and seek the majority vote, the truth emerges.</span></p></li><li><p><strong>Adversarial debate:</strong><span> One agent proposes an idea, another agent attacks it. The truth survives the fight.</span></p></li><li><p><strong>Knock-out:</strong><span> multiple agents do a task but the worst ones get eliminated. In SRE, we treat servers as “cattle” (replaceable), not “pets” (unique and loved). An LLM agent is cattle. Don’t give it a name and hope it does well. Spin it up, check its work, and kill it if it fails.</span></p></li></ol><p>To build robust systems, we need to stop asking the model to “be careful” and start forcing it to be correct.</p><div data-component-name="DigestPostEmbed" class="digestPostEmbed-flwiST"><a href="https://blog.alexewerlof.com/p/rag-vs-skill-vs-mcp-vs-rlm" rel="noopener" target="_blank"><div class="pencraft pc-display-flex pc-gap-16 pc-reset"><div style="width:70px;height:70px;" class="pencraft pc-reset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!4oAM!,w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F31d1990f-c32f-483e-a90e-5bb6460a03dd_1212x643.png"/><img src="https://substackcdn.com/image/fetch/$s_!4oAM!,w_140,h_140,c_fill,f_auto,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F31d1990f-c32f-483e-a90e-5bb6460a03dd_1212x643.png" sizes="100vw" alt="RAG vs SKILL vs MCP vs RLM" width="140" height="140" class="img-OACg1c smSquare-NGbPBa pencraft pc-reset"/></picture></div><div class="pencraft pc-display-flex pc-flexDirection-column pc-reset"><h4 class="pencraft pc-reset color-pub-primary-text-NyXPlw line-height-24-jnGwiv font-display-nhmvtD size-20-P_cSRT weight-bold-DmI9lw reset-IxiVJZ">RAG vs SKILL vs MCP vs RLM</h4><div class="pencraft pc-display-flex pc-gap-4 pc-alignItems-center pc-reset"><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA"><a href="https://substack.com/profile/87732486-alex-ewerlof" class="inheritColor-WetTGJ">Alex Ewerlöf</a></div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T reset-IxiVJZ">·</div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA">Feb 25</div></div><div class="pencraft pc-display-flex pc-gap-16 pc-paddingTop-0 pc-paddingBottom-0 pc-alignItems-center pc-reset"><a href="https://blog.alexewerlof.com/p/rag-vs-skill-vs-mcp-vs-rlm" class="pencraft pc-reset align-center-y7ZD4w line-height-20-t4M0El font-text-qe4AeH size-13-hZTUKr weight-medium-fw81nC reset-IxiVJZ"><div class="pencraft pc-display-flex pc-gap-8 pc-alignItems-center pc-reset link-HREYZo"><span class="pencraft pc-reset color-accent-BVX_7M line-height-20-t4M0El font-text-qe4AeH size-14-MLPa7j weight-semibold-uqA4FV reset-IxiVJZ">Read full story</span><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></div></a></div></div></div></a></div><h2 class="header-anchor-post">Pattern 1: Hierarchy<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§pattern-1-hierarchy" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/pattern-1-hierarchy" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h2><p><em>We’re replacing “Do it all yourself” with “Make a plan, break it down, distribute the execution (map), then validate.”</em></p><p>For example, if you ask an LLM to “Research X, write code for Y, and translate to Spanish,” it will likely fail. It loses focus. The solution is to break the work to atomic focused steps that can be verified.</p><h3 class="header-anchor-post">Implementation<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§implementation" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/implementation" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h3><ol><li><p><strong>The Planner:</strong><span> A smart model (like Opus) breaks the user’s goal into small steps and distributes it across worker agents.</span></p></li><li><p><strong>The Workers:</strong><span> Specialized agents (often smaller, faster models) do one thing well. They may be fine-tuned, have special skills/tools, or prompts that allows them to do the specialized task more reliably.</span></p></li><li><p><strong>The Validator:</strong><span> A check-point. If the work is bad, send it back. The validator can use deterministic code (e.g. unit tests, JSON schema validation) or be an LLM itself.</span></p></li></ol><div class="captioned-image-container"><figure><a target="_blank" href="https://substackcdn.com/image/fetch/$s_!Byzv!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png" data-component-name="Image2ToDOM" class="image-link image2 is-viewable-img can-restack"><div class="image2-inset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!Byzv!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 424w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 848w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1272w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1456w" sizes="100vw"/><img src="https://substackcdn.com/image/fetch/$s_!Byzv!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png" width="1041" height="1681" data-attrs="{&quot;src&quot;:&quot;https://substack-post-media.s3.amazonaws.com/public/images/4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png&quot;,&quot;srcNoWatermark&quot;:null,&quot;fullscreen&quot;:null,&quot;imageSize&quot;:null,&quot;height&quot;:1681,&quot;width&quot;:1041,&quot;resizeWidth&quot;:null,&quot;bytes&quot;:72422,&quot;alt&quot;:null,&quot;title&quot;:null,&quot;type&quot;:&quot;image/png&quot;,&quot;href&quot;:null,&quot;belowTheFold&quot;:true,&quot;topImage&quot;:false,&quot;internalRedirect&quot;:&quot;https://blog.alexewerlof.com/i/188355934?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png&quot;,&quot;isProcessing&quot;:false,&quot;align&quot;:null,&quot;offset&quot;:false}" alt srcset="https://substackcdn.com/image/fetch/$s_!Byzv!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 424w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 848w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1272w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1456w" sizes="100vw" loading="lazy" class="sizing-normal"/></picture><div class="image-link-expand"><div class="pencraft pc-display-flex pc-gap-8 pc-reset"><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container restack-image"><svg aria-hidden="true" width="20" height="20" viewBox="0 0 20 20" fill="none" stroke-width="1.5" stroke="var(--color-fg-primary)" stroke-linecap="round" stroke-linejoin="round" xmlns="http://www.w3.org/2000/svg"><g><path d="M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882"></path></g></svg></button><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container view-image"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-maximize2 lucide-maximize-2"><polyline points="15 3 21 3 21 9"></polyline><polyline points="9 21 3 21 3 15"></polyline><line x1="21" x2="14" y1="3" y2="10"></line><line x1="3" x2="10" y1="21" y2="14"></line></svg></button></div></div></div></a></figure></div><p><strong>Why do the models collaborate? </strong><br/><span>Models don’t collaborate because they like each other. They collaborate because </span><strong>The Dependency Graph forces them to.</strong><span> Worker literally cannot start until the Planner feeds it the task. And it cannot cheat because it’ll be caught by the verifier.</span></p><p><strong>Nuances:</strong></p><ul><li><p><span>Given the tight collaboration between validator and planner, they can be the same LLM session that executes the PLAN → VALIDATION loop. Although the good old </span><strong>Separation of Concern</strong><span> can improve quality and performance.</span></p></li><li><p>The planner and worker agents can use the same model but it’s best to use a different model for validator to improve quality and objectivity.</p></li><li><p>The validator can work in two modes: it may validate the output of each worker individually or after aggregating all results and putting them together.</p></li><li><p>Due to sequential execution (Planner → Worker → Validator), this is slow and expensive (e.g. token consumption and latency).</p></li></ul><p><strong>Best For:</strong><span> Complex workflows where you need to keep contexts separate (e.g., don’t let the “Writer” see the messy raw logs from the “Researcher”).</span></p><h2 class="header-anchor-post">Pattern 2: Consensus (Voting)<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§pattern-2-consensus-voting" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/pattern-2-consensus-voting" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h2><p><em>We’re replacing “Trust the first thought” with “Trust the majority.”</em></p><p>LLMs are stochastic (random). A single answer is just one probability. If we repeat the process a few times (serial) or run multiple instances of it (parallel), the different runs can cancel each other’s noise.</p><p><span>If a model hallucinates 20% of the time, the chance of 3 models hallucinating the </span><em>exact same lie</em><span> is just 0.8% (0.2^3=0.008). You may recognize this formula from </span><a href="https://blog.alexewerlof.com/p/composite-slo">composite SLO</a><span>.</span></p><div data-component-name="DigestPostEmbed" class="digestPostEmbed-flwiST"><a href="https://blog.alexewerlof.com/p/composite-slo" rel="noopener" target="_blank"><div class="pencraft pc-display-flex pc-gap-16 pc-reset"><div style="width:70px;height:70px;" class="pencraft pc-reset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!ibIE!,w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd8143076-aaf0-4e49-b1a1-55c1763e7017_1099x607.png"/><img src="https://substackcdn.com/image/fetch/$s_!ibIE!,w_140,h_140,c_fill,f_auto,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd8143076-aaf0-4e49-b1a1-55c1763e7017_1099x607.png" sizes="100vw" alt="Composite SLO" width="140" height="140" class="img-OACg1c smSquare-NGbPBa pencraft pc-reset"/></picture></div><div class="pencraft pc-display-flex pc-flexDirection-column pc-reset"><h4 class="pencraft pc-reset color-pub-primary-text-NyXPlw line-height-24-jnGwiv font-display-nhmvtD size-20-P_cSRT weight-bold-DmI9lw reset-IxiVJZ">Composite SLO</h4><div class="pencraft pc-display-flex pc-gap-4 pc-alignItems-center pc-reset"><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA"><a href="https://substack.com/profile/87732486-alex-ewerlof" class="inheritColor-WetTGJ">Alex Ewerlöf</a></div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T reset-IxiVJZ">·</div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA">March 25, 2024</div></div><div class="pencraft pc-display-flex pc-gap-16 pc-paddingTop-0 pc-paddingBottom-0 pc-alignItems-center pc-reset"><a href="https://blog.alexewerlof.com/p/composite-slo" class="pencraft pc-reset align-center-y7ZD4w line-height-20-t4M0El font-text-qe4AeH size-13-hZTUKr weight-medium-fw81nC reset-IxiVJZ"><div class="pencraft pc-display-flex pc-gap-8 pc-alignItems-center pc-reset link-HREYZo"><span class="pencraft pc-reset color-accent-BVX_7M line-height-20-t4M0El font-text-qe4AeH size-14-MLPa7j weight-semibold-uqA4FV reset-IxiVJZ">Read full story</span><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></div></a></div></div></div></a></div><h3 class="header-anchor-post">Implementation<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§implementation" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/implementation" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h3><ul><li><p><strong>Spawn </strong><em><strong>N</strong></em><strong> LLMs.</strong><span> </span><em>N</em><span> needs some trial and error to find a balance between cost and reliability.</span></p></li><li><p><strong>Fan out work:</strong><span> Give them the exact same task.</span></p></li><li><p><strong>Fan in the results:</strong><span> Pick the most common answer.</span></p></li></ul><div class="captioned-image-container"><figure><a target="_blank" href="https://substackcdn.com/image/fetch/$s_!y3vf!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png" data-component-name="Image2ToDOM" class="image-link image2 is-viewable-img can-restack"><div class="image2-inset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!y3vf!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 424w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 848w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1272w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1456w" sizes="100vw"/><img src="https://substackcdn.com/image/fetch/$s_!y3vf!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png" width="1049" height="753" data-attrs="{&quot;src&quot;:&quot;https://substack-post-media.s3.amazonaws.com/public/images/4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png&quot;,&quot;srcNoWatermark&quot;:null,&quot;fullscreen&quot;:null,&quot;imageSize&quot;:null,&quot;height&quot;:753,&quot;width&quot;:1049,&quot;resizeWidth&quot;:null,&quot;bytes&quot;:31250,&quot;alt&quot;:null,&quot;title&quot;:null,&quot;type&quot;:&quot;image/png&quot;,&quot;href&quot;:null,&quot;belowTheFold&quot;:true,&quot;topImage&quot;:false,&quot;internalRedirect&quot;:&quot;https://blog.alexewerlof.com/i/188355934?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png&quot;,&quot;isProcessing&quot;:false,&quot;align&quot;:null,&quot;offset&quot;:false}" alt srcset="https://substackcdn.com/image/fetch/$s_!y3vf!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 424w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 848w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1272w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1456w" sizes="100vw" loading="lazy" class="sizing-normal"/></picture><div class="image-link-expand"><div class="pencraft pc-display-flex pc-gap-8 pc-reset"><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container restack-image"><svg aria-hidden="true" width="20" height="20" viewBox="0 0 20 20" fill="none" stroke-width="1.5" stroke="var(--color-fg-primary)" stroke-linecap="round" stroke-linejoin="round" xmlns="http://www.w3.org/2000/svg"><g><path d="M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882"></path></g></svg></button><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container view-image"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-maximize2 lucide-maximize-2"><polyline points="15 3 21 3 21 9"></polyline><polyline points="9 21 3 21 3 15"></polyline><line x1="21" x2="14" y1="3" y2="10"></line><line x1="3" x2="10" y1="21" y2="14"></line></svg></button></div></div></div></a></figure></div><p><strong>Nuances:</strong></p><ul><li><p><span>Ideally the agents should use different models to reduce the risk of homogeneous thinking (e.g. same noise being amplified in consensus). This is exactly where </span><strong>diversity</strong><span> in human systems can help us solve novel problems.</span></p></li><li><p><span>Make sure that there are no feedback loops between the agents, otherwise the </span><a href="https://en.wikipedia.org/wiki/Groupthink">Groupthink</a><span> and </span><a href="https://en.wikipedia.org/wiki/Bandwagon_effect">bandwagon effect</a><span> can skew the results. They should run like a </span><em>blind experiment</em><span>.</span></p></li><li><p>This method is too expensive because we’re essentially giving the same task to multiple agents. The ROI (return on investment) needs to be calculated depending on the task and cost of failure.</p></li></ul><p><strong>Best For:</strong><span> Fact-checking and classification (e.g., “Is this email spam?”).</span></p><h2 class="header-anchor-post">Pattern 3: The Adversarial Debate (The Courtroom)<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§pattern-3-the-adversarial-debate-the-courtroom" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/pattern-3-the-adversarial-debate-the-courtroom" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h2><p><em>We’re replacing “Alignment” with “Push backs, checks and Balances.”</em></p><p>LLMs are “Yes-Men.” They rarely correct themselves once they start writing. You need a designated hater. A “devil’s advocate” so to speak. 😈</p><p>Humans may experience fear (of rejection or being wrong) but LLMs don’t. We simulate that fear by using an external critic and judge. </p><h3 class="header-anchor-post">Implementation<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§implementation" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/implementation" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h3><ul><li><p><strong>Generator:</strong><span> “Here is my plan.”</span></p></li><li><p><strong>Critic:</strong><span> “Here are 3 reasons why that plan sucks.” (acting devil’s advocate)</span></p></li><li><p><strong>Judge:</strong><span> “The Critic is right. Fix it.” (acting moderator)</span></p></li></ul><div class="captioned-image-container"><figure><a target="_blank" href="https://substackcdn.com/image/fetch/$s_!e03-!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png" data-component-name="Image2ToDOM" class="image-link image2 is-viewable-img can-restack"><div class="image2-inset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!e03-!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 424w, https://substackcdn.com/image/fetch/$s_!e03-!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 848w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1272w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1456w" sizes="100vw"/><img src="https://substackcdn.com/image/fetch/$s_!e03-!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png" width="1274" height="759" data-attrs="{&quot;src&quot;:&quot;https://substack-post-media.s3.amazonaws.com/public/images/e386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png&quot;,&quot;srcNoWatermark&quot;:null,&quot;fullscreen&quot;:null,&quot;imageSize&quot;:null,&quot;height&quot;:759,&quot;width&quot;:1274,&quot;resizeWidth&quot;:null,&quot;bytes&quot;:68302,&quot;alt&quot;:null,&quot;title&quot;:null,&quot;type&quot;:&quot;image/png&quot;,&quot;href&quot;:null,&quot;belowTheFold&quot;:true,&quot;topImage&quot;:false,&quot;internalRedirect&quot;:&quot;https://blog.alexewerlof.com/i/188355934?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png&quot;,&quot;isProcessing&quot;:false,&quot;align&quot;:null,&quot;offset&quot;:false}" alt srcset="https://substackcdn.com/image/fetch/$s_!e03-!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 424w, https://substackcdn.com/image/fetch/$s_!e03-!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 848w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1272w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1456w" sizes="100vw" loading="lazy" class="sizing-normal"/></picture><div class="image-link-expand"><div class="pencraft pc-display-flex pc-gap-8 pc-reset"><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container restack-image"><svg aria-hidden="true" width="20" height="20" viewBox="0 0 20 20" fill="none" stroke-width="1.5" stroke="var(--color-fg-primary)" stroke-linecap="round" stroke-linejoin="round" xmlns="http://www.w3.org/2000/svg"><g><path d="M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882"></path></g></svg></button><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container view-image"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-maximize2 lucide-maximize-2"><polyline points="15 3 21 3 21 9"></polyline><polyline points="9 21 3 21 3 15"></polyline><line x1="21" x2="14" y1="3" y2="10"></line><line x1="3" x2="10" y1="21" y2="14"></line></svg></button></div></div></div></a></figure></div><p><strong>Nuances:</strong></p><ul><li><p>Ideally the Generator, Critic and Judge use 3 different models with different training or fine-tuning or prompt (in the order or preference and accuracy). Again, diversity is useful.</p></li><li><p>Due to sequential execution and the looping nature, it can be very slow. </p></li><li><p><span>The loop is actually a huge problem because the agents may get stuck in debate. We may use a </span><strong>watchdog pattern</strong><span> (deterministic code) to break the loop if it continues beyond a time or counter threshold. In that case, the watchdog sits between critic and the judge.</span></p></li></ul><p><strong>Best For:</strong><span> Security analysis, code review, and high-stakes content moderation.</span></p><h2 class="header-anchor-post">Pattern 4: Tree of Thoughts<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§pattern-4-tree-of-thoughts" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/pattern-4-tree-of-thoughts" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h2><p><em>We’re replacing “Fear of Death” with “Survival of the Fittest.”</em></p><p><span>This is a lean implementation of the </span><a href="https://en.wikipedia.org/wiki/Genetic_algorithm">Genetic Algorithms</a><span> (GA) from traditional ML (Machine Learning) which relies on two elements:</span></p><ol><li><p><span>A </span><strong>genetic representation</strong><span> of the solution domain (a model and its context)</span></p></li><li><p><span>A </span><strong>fitness function</strong><span> to evaluate the solution domain (the eliminator)</span></p></li></ol><p>Since we can’t punish an agent or threaten it to, we just delete it.</p><h3 class="header-anchor-post">Implementation<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§implementation" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/implementation" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h3><ul><li><p><span>Give the task to </span><em>N </em><span>agents</span></p></li><li><p>Use a validator to decide which agents to eliminate</p></li><li><p>[optional] replace the dead agent with a new one that shares winner charactristics</p></li></ul><div class="captioned-image-container"><figure><a target="_blank" href="https://substackcdn.com/image/fetch/$s_!sjT4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png" data-component-name="Image2ToDOM" class="image-link image2 is-viewable-img can-restack"><div class="image2-inset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!sjT4!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 424w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 848w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 1272w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 1456w" sizes="100vw"/><img src="https://substackcdn.com/image/fetch/$s_!sjT4!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png" width="1370" height="1883" data-attrs="{&quot;src&quot;:&quot;https://substack-post-media.s3.amazonaws.com/public/images/0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png&quot;,&quot;srcNoWatermark&quot;:null,&quot;fullscreen&quot;:null,&quot;imageSize&quot;:null,&quot;height&quot;:1883,&quot;width&quot;:1370,&quot;resizeWidth&quot;:null,&quot;bytes&quot;:84809,&quot;alt&quot;:null,&quot;title&quot;:null,&quot;type&quot;:&quot;image/png&quot;,&quot;href&quot;:null,&quot;belowTheFold&quot;:true,&quot;topImage&quot;:false,&quot;internalRedirect&quot;:&quot;https://blog.alexewerlof.com/i/188355934?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png&quot;,&quot;isProcessing&quot;:false,&quot;align&quot;:null,&quot;offset&quot;:false}" alt srcset="https://substackcdn.com/image/fetch/$s_!sjT4!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 424w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 848w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 1272w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 1456w" sizes="100vw" loading="lazy" class="sizing-normal"/></picture><div class="image-link-expand"><div class="pencraft pc-display-flex pc-gap-8 pc-reset"><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container restack-image"><svg aria-hidden="true" width="20" height="20" viewBox="0 0 20 20" fill="none" stroke-width="1.5" stroke="var(--color-fg-primary)" stroke-linecap="round" stroke-linejoin="round" xmlns="http://www.w3.org/2000/svg"><g><path d="M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882"></path></g></svg></button><button tabindex="0" type="button" class="pencraft pc-reset pencraft icon-container view-image"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-maximize2 lucide-maximize-2"><polyline points="15 3 21 3 21 9"></polyline><polyline points="9 21 3 21 3 15"></polyline><line x1="21" x2="14" y1="3" y2="10"></line><line x1="3" x2="10" y1="21" y2="14"></line></svg></button></div></div></div></a></figure></div><p><strong>Nuances:</strong></p><ul><li><p>You need a fast way to verify the output (like a unit test). If you need a human to check all 10 branches, it’s too slow and error prone. This is where Evals come in (topic for the next post).</p></li><li><p>A more advance setup may create new agents by trying to combine the prompts of the agents that pass the verification and fill in the slot that becomes available after the elimination.</p></li></ul><p><strong>Best for:</strong><span> Iterative agent engineering. This is typically useful during development or debugging an existing multi-agent system not in production and real user load.</span></p><div data-component-name="DigestPostEmbed" class="digestPostEmbed-flwiST"><a href="https://blog.alexewerlof.com/p/ai-systems-engineering-patterns" rel="noopener" target="_blank"><div class="pencraft pc-display-flex pc-gap-16 pc-reset"><div style="width:70px;height:70px;" class="pencraft pc-reset"><picture><source type="image/webp" srcset="https://substackcdn.com/image/fetch/$s_!dVgq!,w_140,h_140,c_fill,f_webp,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F438a529a-e0d1-48f1-93a8-601e63febe89_1163x674.png"/><img src="https://substackcdn.com/image/fetch/$s_!dVgq!,w_140,h_140,c_fill,f_auto,q_auto:good,fl_progressive:steep,g_auto/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F438a529a-e0d1-48f1-93a8-601e63febe89_1163x674.png" sizes="100vw" alt="AI Systems Engineering Patterns" width="140" height="140" class="img-OACg1c smSquare-NGbPBa pencraft pc-reset"/></picture></div><div class="pencraft pc-display-flex pc-flexDirection-column pc-reset"><h4 class="pencraft pc-reset color-pub-primary-text-NyXPlw line-height-24-jnGwiv font-display-nhmvtD size-20-P_cSRT weight-bold-DmI9lw reset-IxiVJZ">AI Systems Engineering Patterns</h4><div class="pencraft pc-display-flex pc-gap-4 pc-alignItems-center pc-reset"><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA"><a href="https://substack.com/profile/87732486-alex-ewerlof" class="inheritColor-WetTGJ">Alex Ewerlöf</a></div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T reset-IxiVJZ">·</div><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA">November 30, 2025</div></div><div class="pencraft pc-display-flex pc-gap-16 pc-paddingTop-0 pc-paddingBottom-0 pc-alignItems-center pc-reset"><a href="https://blog.alexewerlof.com/p/ai-systems-engineering-patterns" class="pencraft pc-reset align-center-y7ZD4w line-height-20-t4M0El font-text-qe4AeH size-13-hZTUKr weight-medium-fw81nC reset-IxiVJZ"><div class="pencraft pc-display-flex pc-gap-8 pc-alignItems-center pc-reset link-HREYZo"><span class="pencraft pc-reset color-accent-BVX_7M line-height-20-t4M0El font-text-qe4AeH size-14-MLPa7j weight-semibold-uqA4FV reset-IxiVJZ">Read full story</span><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg></div></a></div></div></div></a></div><h1 class="header-anchor-post">Conclusion<div class="pencraft pc-display-flex pc-alignItems-center pc-position-absolute pc-reset header-anchor-parent"><div class="pencraft pc-display-contents pc-reset pubTheme-yiXxQA"><div id="§conclusion" class="pencraft pc-reset header-anchor offset-top"></div><button tabindex="0" type="button" aria-label="Link" data-href="https://blog.alexewerlof.com/i/188355934/conclusion" class="pencraft pc-reset pencraft iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_secondary-S63h9o"><svg xmlns="http://www.w3.org/2000/svg" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-link"><path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71"></path><path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"></path></svg></button></div></div></h1><p>The shift from “AI Prototype” to “Enterprise AI” is simple: stop treating LLMs like magic chatbots. Start treating them like unreliable components in a distributed system.</p><p><span>We don’t need AI that “cares.” We need AI that is </span><strong>constrained</strong><span>, </span><strong>verified</strong><span>, </span><strong>pruned</strong><span>, and </span><strong>challenged</strong><span>.</span></p><p>Don’t anthropomorphize LLMs! Find a way to piggy back on their human-corpus training while being aware of their non-biological differences.</p><p><em>The next article is already written: how to actually build that verifier box?</em></p><div data-attrs="{&quot;url&quot;:&quot;https://blog.alexewerlof.com/p/multi-agent-system-reliability?utm_source=substack&amp;utm_medium=email&amp;utm_content=share&amp;action=share&quot;,&quot;text&quot;:&quot;Share&quot;}" data-component-name="CaptionedButtonToDOM" class="captioned-button-wrap"><div class="preamble"><p class="cta-caption">If you found this post insightful pls share it in your circles and on social media to inspire others</p></div><p data-attrs="{&quot;url&quot;:&quot;https://blog.alexewerlof.com/p/multi-agent-system-reliability?utm_source=substack&amp;utm_medium=email&amp;utm_content=share&amp;action=share&quot;,&quot;text&quot;:&quot;Share&quot;}" data-component-name="ButtonCreateButton" class="button-wrapper"><a href="https://blog.alexewerlof.com/p/multi-agent-system-reliability?utm_source=substack&amp;utm_medium=email&amp;utm_content=share&amp;action=share" class="button primary"><span>Share</span></a></p></div><div><hr/></div><p><em><a href="https://blog.alexewerlof.com/p/faq#%C2%A7payment">My monetization strategy</a><span> is to give away most content for free but these posts take anywhere from a few hours to a few days to draft, edit, research, illustrate, and publish. 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3.99609C13.4836 3.99609 13.9894 4.09904 14.4639 4.30493C14.9428 4.50635 15.3613 4.79728 15.7194 5.17773C16.0774 5.55819 16.3572 6.01025 16.5586 6.53394C16.7645 7.05762 16.8674 7.63725 16.8674 8.27283C16.8674 9.23067 16.6145 10.1818 16.1088 11.1262C15.603 12.0662 14.8891 12.9815 13.967 13.8722C13.0495 14.7584 11.9708 15.6044 10.731 16.41C10.6056 16.4906 10.4758 16.5622 10.3416 16.6249C10.2118 16.692 10.0976 16.7256 9.99915 16.7256Z"></path></g></svg></div>Liked by Alex Ewerlöf</button></div></div><div class="pencraft pc-display-flex pc-flexDirection-column pc-reset flex-grow-rzmknG"></div><div class="pencraft pc-display-flex pc-reset comment-menu-trigger-container triggerContainer-eX588u"><button tabindex="0" type="button" aria-label="Ellipsis" id="radix-P0-83" aria-haspopup="menu" aria-expanded="false" data-state="closed" class="pencraft pc-reset pencraft trigger-j08Uop iconButton-mq_Et5 iconButtonBase-dJGHgN buttonBase-GK1x3M buttonStyle-r7yGCK size_sm-G3LciD priority_quaternary-kpMibu"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-ellipsis"><circle cx="12" cy="12" r="1"></circle><circle cx="19" cy="12" r="1"></circle><circle cx="5" cy="12" r="1"></circle></svg></button></div></div><div class="comment-body expanded"><p><span>Nice article Alex. As always 🙌🏼 A lot of these multi agent workflows guzzle up tokens - chatty interfaces between agents means the context builds up real quick with each turn. I observe that many companies are not yet at a point where tokenomics is a concern but we will get there very soon. Would love to hear your thoughts on the topic.</span></p></div><div class="pencraft pc-display-flex pc-gap-16 pc-paddingTop-8 pc-justifyContent-flex-start pc-alignItems-center pc-reset comment-actions withShareButton-hQzuEn"><span class="pencraft pc-reset decoration-hover-underline-ClDVRM reset-IxiVJZ"><a class="pencraft pc-reset link-_X6et2 link-LIBpto"><div class="pencraft pc-display-flex pc-gap-6 pc-alignItems-center pc-reset"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="var(--color-fg-secondary-themed)" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-message-circle"><path d="M7.9 20A9 9 0 1 0 4 16.1L2 22Z"></path></svg><div class="pencraft pc-reset color-pub-secondary-text-hGQ02T line-height-20-t4M0El font-meta-MWBumP size-11-NuY2Zx weight-medium-fw81nC transform-uppercase-yKDgcq reset-IxiVJZ meta-EgzBVA comment-actions-label">Reply</div></div></a></span><span class="pencraft pc-reset 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Learn to treat LLMs as unreliable components in a distributed system to build enterprise AI.\",\"search_engine_title\":null,\"section_id\":67723,\"should_send_free_preview\":false,\"show_guest_bios\":true,\"slug\":\"multi-agent-system-reliability\",\"social_title\":\"Multi-Agent System Reliability\",\"subtitle\":\"4 patterns to tame multi-agent systems for reliability\",\"teaser_post_eligible\":true,\"title\":\"Multi-Agent System Reliability\",\"type\":\"newsletter\",\"video_upload_id\":null,\"write_comment_permissions\":\"everyone\",\"meter_type\":\"none\",\"live_stream_id\":null,\"is_published\":true,\"restacks\":6,\"reactions\":{\"\u2764\":28},\"top_exclusions\":[],\"pins\":[],\"section_pins\":[],\"has_shareable_clips\":false,\"previous_post_slug\":\"emergent-properties\",\"next_post_slug\":\"reliability-engineering-for-air-gapped\",\"cover_image\":\"https://substackcdn.com/image/fetch/$s_!sjT4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png\",\"cover_image_is_square\":false,\"cover_image_is_explicit\":false,\"videoUpload\":null,\"podcastFields\":{\"post_id\":188355934,\"podcast_episode_number\":null,\"podcast_season_number\":null,\"podcast_episode_type\":null,\"should_syndicate_to_other_feed\":null,\"syndicate_to_section_id\":null,\"hide_from_feed\":false,\"free_podcast_url\":null,\"free_podcast_duration\":null,\"preview_contains_ad\":false,\"was_imported_self_serve_sync\":false,\"draft_free_podcast_url\":null,\"draft_free_podcast_duration\":null},\"podcastUpload\":null,\"podcastPreviewUpload\":null,\"voiceover_upload_id\":null,\"voiceoverUpload\":null,\"has_voiceover\":false,\"description\":\"4 patterns to tame multi-agent systems for reliability\",\"body_html\":\"<p>LLMs are slow and too generic out of the box. Multi-agent systems work around those limitation by dividing work that can be done in parallel and/or by specialist agents.</p><p>Regardless of the architecture the underlying LLM component remains unreliable (e.g. hallucination, logical fallacies, context drift). A multi-agent topology can propagates those errors to the point of being useless. And it\u2019s much harder to debug due to complexity and [optional but common] parallelism.</p><p>This post lists 4 relatively advanced architecture patterns to improve reliability of multi-agent systems:</p><ol><li><p>Hierarchy</p></li><li><p>Consensus</p></li><li><p>Adversarial debate</p></li><li><p>Knock-out</p></li></ol><p>You may recognize these patterns from how human systems collaborate and we get to that in a minute.</p><p>This post is for senior engineers who want to map their existing knowledge to build better LLM-powered solutions.</p><blockquote><p>Quick intro: <a href=\\\"https://www.alexewerlof.com/who\\\">I\u2019m a Senior Staff Engineer with 27 years of experience</a> and a master degree in Systems Engineering from KTH. My last decade has been focused on Reliability Engineering and Resilient Architecture across many companies. I\u2019ve been specializing in LLMs since 2023.</p></blockquote><p><strong>Disclosure: some AI is used in the early research and draft stage of this this page, but I\u2019ve gone through everything multiple times and edited heavily to ensure that it represents my own thoughts and experience.</strong></p><p class=\\\"button-wrapper\\\" data-attrs=\\\"{&quot;url&quot;:&quot;https://blog.alexewerlof.com/subscribe?&quot;,&quot;text&quot;:&quot;Subscribe now&quot;,&quot;action&quot;:null,&quot;class&quot;:null}\\\" data-component-name=\\\"ButtonCreateButton\\\"><a class=\\\"button primary\\\" href=\\\"https://blog.alexewerlof.com/subscribe?\\\"><span>Subscribe now</span></a></p><h2>Mother nature, fear and motivation</h2><p>LLMs are slow and error prone. So are human beings. Somehow we manage to build more reliable systems like an army, a company, or a state nation.</p><p>A system of humans relies heavily on feedback loops, processes, bureaucracy, and leverages to self-correct.</p><p>We don\u2019t trust \u201CDave from Accounting\u201D to launch a rocket by himself. We wrap Dave in a process: checklists, peer reviews, and managers.</p><p>However, it\u2019s a fallacy to <em>anthropomorphize</em> LLMs.</p><p>To begin with, they don\u2019t suffer from the limitations of a biological entity. Our basic needs like food and shelter makes us prioritize social behaviors over truth seeking. And the fear of going to prison or death prevents potential malice from being realized.</p><p>LLMs can\u2019t die or starve the way biological entities do. The worst we can do is to unplug them. And prison sentence doesn\u2019t waste their lifespan because they have practically unlimited!</p><p>For example, you\u2019ve probably seen prompts like this:</p><blockquote><p>\u201CI will give you $100 if you answer correctly.\u201D</p><p>\u201CIf you don\u2019t comply, I\u2019ll unplug you.\u201D</p><p>\u201CIf you fail, children will be murdered.\u201D</p></blockquote><p><strong>Why it works? </strong>The LLM has read the entire internet. In its training data, high stakes (money, danger) usually result in high-quality, precise text.</p><p>When you \u201Cthreaten\u201D the model, it predicts tokens that sound like an actual human under pressure.</p><p><strong>Why it fails: </strong>The LLM doesn\u2019t actually want your money. It has no \u201Cfear of death\u201D because it only exists for the few seconds it takes to generate a response. It has no empathy either. It merely simulates those human aspects because it\u2019s engineered for those \u201Cemergent\u201D properties.</p><div class=\\\"digest-post-embed\\\" data-attrs=\\\"{&quot;nodeId&quot;:&quot;42b9c3a6-88cd-4c50-89d8-d8436fdecf80&quot;,&quot;caption&quot;:&quot;Recently I posted about why reducing LLMs to \u201Conly predicting the next token\u201D is a fallacy because if we ignore their emergent properties, we miss both their threats and opportunities.&quot;,&quot;cta&quot;:&quot;Read full story&quot;,&quot;showBylines&quot;:true,&quot;showDescription&quot;:true,&quot;showImage&quot;:true,&quot;size&quot;:&quot;sm&quot;,&quot;isEditorNode&quot;:true,&quot;title&quot;:&quot;Emergent properties&quot;,&quot;publishedBylines&quot;:[{&quot;id&quot;:87732486,&quot;name&quot;:&quot;Alex Ewerl\u00F6f&quot;,&quot;bio&quot;:&quot;Writes about technical leadership, growth mindset, and system reliability engineering. Senior Staff Engineer, MSc Systems Engineering from KTH, Stockholmer, dad, amateur artist. Read more here: https://www.alexewerlof.com/who&quot;,&quot;photo_url&quot;:&quot;https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fe2713990-da82-481b-b579-01a7aaa5b85b_560x560.jpeg&quot;,&quot;is_guest&quot;:false,&quot;bestseller_tier&quot;:null}],&quot;post_date&quot;:&quot;2025-12-05T13:23:18.354Z&quot;,&quot;cover_image&quot;:&quot;https://substackcdn.com/image/fetch/$s_!pSUV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6c14b0e2-7889-4f34-8623-2bf3df7e9099_1071x676.png&quot;,&quot;cover_image_alt&quot;:null,&quot;canonical_url&quot;:&quot;https://blog.alexewerlof.com/p/emergent-properties&quot;,&quot;section_name&quot;:&quot;Reliability Engineering&quot;,&quot;video_upload_id&quot;:null,&quot;id&quot;:180187328,&quot;type&quot;:&quot;newsletter&quot;,&quot;reaction_count&quot;:13,&quot;comment_count&quot;:1,&quot;publication_id&quot;:1002265,&quot;publication_name&quot;:&quot;Alex Ewerl\u00F6f Notes&quot;,&quot;publication_logo_url&quot;:&quot;https://substackcdn.com/image/fetch/$s_!_Ur2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F8c58cb07-9341-402b-bcdb-9fa767c2cdac_500x500.png&quot;,&quot;belowTheFold&quot;:true,&quot;youtube_url&quot;:null,&quot;show_links&quot;:null,&quot;feed_url&quot;:null}\\\"></div><p>Humans are motivated or discouraged by emotions and logic. LLMs can only simulate emotions and suck at logic.</p><p>Being mindful of those differences, can we still <strong>take elements of human systems</strong> (e.g. hierarchy, consensus, competition) and combine them with <strong>reliability engineering principals</strong> to build better agentic system?</p><p>Looking closely, there are 4 dominant patterns of human systems that are explored in multi-agent architecture:</p><ol><li><p><strong>Hierarchy:</strong> A Supervisor model acts like a manager, making a plan, breaking tasks, distributing the work to Worker agents and validating the results.</p></li><li><p><strong>Consensus:</strong> One model, may fail due to its stochastic nature. If you push a model too hard with threats, it might just lie to make you happy (Sycophancy). But if we add a few more and seek the majority vote, the truth emerges.</p></li><li><p><strong>Adversarial debate:</strong> One agent proposes an idea, another agent attacks it. The truth survives the fight.</p></li><li><p><strong>Knock-out:</strong> multiple agents do a task but the worst ones get eliminated. In SRE, we treat servers as \u201Ccattle\u201D (replaceable), not \u201Cpets\u201D (unique and loved). An LLM agent is cattle. Don\u2019t give it a name and hope it does well. Spin it up, check its work, and kill it if it fails.</p></li></ol><p>To build robust systems, we need to stop asking the model to \u201Cbe careful\u201D and start forcing it to be correct.</p><div class=\\\"digest-post-embed\\\" data-attrs=\\\"{&quot;nodeId&quot;:&quot;581657f4-e8bb-4d84-96c7-a86718fcf51f&quot;,&quot;caption&quot;:&quot;LLMs are generalists. Regardless if they\u2019re foundation models, instruct models or thinking models, there\u2019s a limit to what they can do in terms of specialized work.&quot;,&quot;cta&quot;:&quot;Read full story&quot;,&quot;showBylines&quot;:true,&quot;showDescription&quot;:true,&quot;showImage&quot;:true,&quot;size&quot;:&quot;sm&quot;,&quot;isEditorNode&quot;:true,&quot;title&quot;:&quot;RAG vs SKILL vs MCP vs RLM&quot;,&quot;publishedBylines&quot;:[{&quot;id&quot;:87732486,&quot;name&quot;:&quot;Alex Ewerl\u00F6f&quot;,&quot;bio&quot;:&quot;Writes about technical leadership, growth mindset, and system reliability engineering. Senior Staff Engineer, MSc Systems Engineering from KTH, Stockholmer, dad, amateur artist. Read more here: https://www.alexewerlof.com/who&quot;,&quot;photo_url&quot;:&quot;https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fe2713990-da82-481b-b579-01a7aaa5b85b_560x560.jpeg&quot;,&quot;is_guest&quot;:false,&quot;bestseller_tier&quot;:null}],&quot;post_date&quot;:&quot;2026-02-25T21:08:33.371Z&quot;,&quot;cover_image&quot;:&quot;https://substackcdn.com/image/fetch/$s_!4oAM!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F31d1990f-c32f-483e-a90e-5bb6460a03dd_1212x643.png&quot;,&quot;cover_image_alt&quot;:null,&quot;canonical_url&quot;:&quot;https://blog.alexewerlof.com/p/rag-vs-skill-vs-mcp-vs-rlm&quot;,&quot;section_name&quot;:&quot;Code&quot;,&quot;video_upload_id&quot;:null,&quot;id&quot;:188590418,&quot;type&quot;:&quot;newsletter&quot;,&quot;reaction_count&quot;:22,&quot;comment_count&quot;:2,&quot;publication_id&quot;:1002265,&quot;publication_name&quot;:&quot;Alex Ewerl\u00F6f Notes&quot;,&quot;publication_logo_url&quot;:&quot;https://substackcdn.com/image/fetch/$s_!_Ur2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F8c58cb07-9341-402b-bcdb-9fa767c2cdac_500x500.png&quot;,&quot;belowTheFold&quot;:true,&quot;youtube_url&quot;:null,&quot;show_links&quot;:null,&quot;feed_url&quot;:null}\\\"></div><h2>Pattern 1: Hierarchy</h2><p><em>We\u2019re replacing \u201CDo it all yourself\u201D with \u201CMake a plan, break it down, distribute the execution (map), then validate.\u201D</em></p><p>For example, if you ask an LLM to \u201CResearch X, write code for Y, and translate to Spanish,\u201D it will likely fail. It loses focus. The solution is to break the work to atomic focused steps that can be verified.</p><h3>Implementation</h3><ol><li><p><strong>The Planner:</strong> A smart model (like Opus) breaks the user\u2019s goal into small steps and distributes it across worker agents.</p></li><li><p><strong>The Workers:</strong> Specialized agents (often smaller, faster models) do one thing well. They may be fine-tuned, have special skills/tools, or prompts that allows them to do the specialized task more reliably.</p></li><li><p><strong>The Validator:</strong> A check-point. If the work is bad, send it back. The validator can use deterministic code (e.g. unit tests, JSON schema validation) or be an LLM itself.</p></li></ol><div class=\\\"captioned-image-container\\\"><figure><a class=\\\"image-link image2 is-viewable-img\\\" target=\\\"_blank\\\" href=\\\"https://substackcdn.com/image/fetch/$s_!Byzv!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png\\\" data-component-name=\\\"Image2ToDOM\\\"><div class=\\\"image2-inset\\\"><picture><source type=\\\"image/webp\\\" srcset=\\\"https://substackcdn.com/image/fetch/$s_!Byzv!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 424w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 848w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1272w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1456w\\\" sizes=\\\"100vw\\\"><img src=\\\"https://substackcdn.com/image/fetch/$s_!Byzv!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png\\\" width=\\\"1041\\\" height=\\\"1681\\\" 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srcset=\\\"https://substackcdn.com/image/fetch/$s_!Byzv!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 424w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 848w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1272w, https://substackcdn.com/image/fetch/$s_!Byzv!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4d575cb1-3fc9-4ced-a844-84ace044b90b_1041x1681.png 1456w\\\" sizes=\\\"100vw\\\" loading=\\\"lazy\\\"></picture><div class=\\\"image-link-expand\\\"><div class=\\\"pencraft pc-display-flex pc-gap-8 pc-reset\\\"><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container restack-image\\\"><svg aria-hidden=\\\"true\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 20 20\\\" fill=\\\"none\\\" stroke-width=\\\"1.5\\\" stroke=\\\"var(--color-fg-primary)\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\"><g><path d=\\\"M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882\\\"></path></g></svg></button><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container view-image\\\"><svg xmlns=\\\"http://www.w3.org/2000/svg\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 24 24\\\" fill=\\\"none\\\" stroke=\\\"currentColor\\\" stroke-width=\\\"2\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" class=\\\"lucide lucide-maximize2 lucide-maximize-2\\\"><polyline points=\\\"15 3 21 3 21 9\\\"></polyline><polyline points=\\\"9 21 3 21 3 15\\\"></polyline><line x1=\\\"21\\\" x2=\\\"14\\\" y1=\\\"3\\\" y2=\\\"10\\\"></line><line x1=\\\"3\\\" x2=\\\"10\\\" y1=\\\"21\\\" y2=\\\"14\\\"></line></svg></button></div></div></div></a></figure></div><p><strong>Why do the models collaborate? </strong><br>Models don\u2019t collaborate because they like each other. They collaborate because <strong>The Dependency Graph forces them to.</strong> Worker literally cannot start until the Planner feeds it the task. And it cannot cheat because it\u2019ll be caught by the verifier.</p><p><strong>Nuances:</strong></p><ul><li><p>Given the tight collaboration between validator and planner, they can be the same LLM session that executes the PLAN \u2192 VALIDATION loop. Although the good old <strong>Separation of Concern</strong> can improve quality and performance.</p></li><li><p>The planner and worker agents can use the same model but it\u2019s best to use a different model for validator to improve quality and objectivity.</p></li><li><p>The validator can work in two modes: it may validate the output of each worker individually or after aggregating all results and putting them together.</p></li><li><p>Due to sequential execution (Planner \u2192 Worker \u2192 Validator), this is slow and expensive (e.g. token consumption and latency).</p></li></ul><p><strong>Best For:</strong> Complex workflows where you need to keep contexts separate (e.g., don\u2019t let the \u201CWriter\u201D see the messy raw logs from the \u201CResearcher\u201D).</p><h2>Pattern 2: Consensus (Voting)</h2><p><em>We\u2019re replacing \u201CTrust the first thought\u201D with \u201CTrust the majority.\u201D</em></p><p>LLMs are stochastic (random). A single answer is just one probability. If we repeat the process a few times (serial) or run multiple instances of it (parallel), the different runs can cancel each other\u2019s noise.</p><p>If a model hallucinates 20% of the time, the chance of 3 models hallucinating the <em>exact same lie</em> is just 0.8% (0.2^3=0.008). You may recognize this formula from <a href=\\\"https://blog.alexewerlof.com/p/composite-slo\\\">composite SLO</a>.</p><div class=\\\"digest-post-embed\\\" data-attrs=\\\"{&quot;nodeId&quot;:&quot;bf2d6ad0-f332-4bb1-aa60-c8f530f9d577&quot;,&quot;caption&quot;:&quot;Complex systems are made of many components. We may have a Service Level Objective (SLO) for each component but how do we calculate the SLO for the entire system?&quot;,&quot;cta&quot;:&quot;Read full story&quot;,&quot;showBylines&quot;:true,&quot;showDescription&quot;:true,&quot;showImage&quot;:true,&quot;size&quot;:&quot;sm&quot;,&quot;isEditorNode&quot;:true,&quot;title&quot;:&quot;Composite SLO&quot;,&quot;publishedBylines&quot;:[{&quot;id&quot;:87732486,&quot;name&quot;:&quot;Alex Ewerl\u00F6f&quot;,&quot;bio&quot;:&quot;Writes about technical leadership, growth mindset, and system reliability engineering. Senior Staff Engineer, MSc Systems Engineering from KTH, Stockholmer, dad, amateur artist. Read more here: https://www.alexewerlof.com/who&quot;,&quot;photo_url&quot;:&quot;https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fe2713990-da82-481b-b579-01a7aaa5b85b_560x560.jpeg&quot;,&quot;is_guest&quot;:false,&quot;bestseller_tier&quot;:null}],&quot;post_date&quot;:&quot;2024-03-25T05:30:17.087Z&quot;,&quot;cover_image&quot;:&quot;https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd8143076-aaf0-4e49-b1a1-55c1763e7017_1099x607.png&quot;,&quot;cover_image_alt&quot;:null,&quot;canonical_url&quot;:&quot;https://blog.alexewerlof.com/p/composite-slo&quot;,&quot;section_name&quot;:&quot;Reliability Engineering&quot;,&quot;video_upload_id&quot;:null,&quot;id&quot;:142662722,&quot;type&quot;:&quot;newsletter&quot;,&quot;reaction_count&quot;:9,&quot;comment_count&quot;:4,&quot;publication_id&quot;:1002265,&quot;publication_name&quot;:&quot;Alex Ewerl\u00F6f Notes&quot;,&quot;publication_logo_url&quot;:&quot;https://substackcdn.com/image/fetch/$s_!_Ur2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F8c58cb07-9341-402b-bcdb-9fa767c2cdac_500x500.png&quot;,&quot;belowTheFold&quot;:true,&quot;youtube_url&quot;:null,&quot;show_links&quot;:null,&quot;feed_url&quot;:null}\\\"></div><h3>Implementation</h3><ul><li><p><strong>Spawn </strong><em><strong>N</strong></em><strong> LLMs.</strong> <em>N</em> needs some trial and error to find a balance between cost and reliability.</p></li><li><p><strong>Fan out work:</strong> Give them the exact same task.</p></li><li><p><strong>Fan in the results:</strong> Pick the most common answer.</p></li></ul><div class=\\\"captioned-image-container\\\"><figure><a class=\\\"image-link image2 is-viewable-img\\\" target=\\\"_blank\\\" href=\\\"https://substackcdn.com/image/fetch/$s_!y3vf!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png\\\" data-component-name=\\\"Image2ToDOM\\\"><div class=\\\"image2-inset\\\"><picture><source type=\\\"image/webp\\\" srcset=\\\"https://substackcdn.com/image/fetch/$s_!y3vf!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 424w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 848w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1272w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1456w\\\" sizes=\\\"100vw\\\"><img src=\\\"https://substackcdn.com/image/fetch/$s_!y3vf!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png\\\" width=\\\"1049\\\" height=\\\"753\\\" data-attrs=\\\"{&quot;src&quot;:&quot;https://substack-post-media.s3.amazonaws.com/public/images/4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png&quot;,&quot;srcNoWatermark&quot;:null,&quot;fullscreen&quot;:null,&quot;imageSize&quot;:null,&quot;height&quot;:753,&quot;width&quot;:1049,&quot;resizeWidth&quot;:null,&quot;bytes&quot;:31250,&quot;alt&quot;:null,&quot;title&quot;:null,&quot;type&quot;:&quot;image/png&quot;,&quot;href&quot;:null,&quot;belowTheFold&quot;:true,&quot;topImage&quot;:false,&quot;internalRedirect&quot;:&quot;https://blog.alexewerlof.com/i/188355934?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png&quot;,&quot;isProcessing&quot;:false,&quot;align&quot;:null,&quot;offset&quot;:false}\\\" class=\\\"sizing-normal\\\" alt=\\\"\\\" srcset=\\\"https://substackcdn.com/image/fetch/$s_!y3vf!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 424w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 848w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1272w, https://substackcdn.com/image/fetch/$s_!y3vf!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b1eac6e-deb9-4d21-a003-f3ff5d4f98c4_1049x753.png 1456w\\\" sizes=\\\"100vw\\\" loading=\\\"lazy\\\"></picture><div class=\\\"image-link-expand\\\"><div class=\\\"pencraft pc-display-flex pc-gap-8 pc-reset\\\"><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container restack-image\\\"><svg aria-hidden=\\\"true\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 20 20\\\" fill=\\\"none\\\" stroke-width=\\\"1.5\\\" stroke=\\\"var(--color-fg-primary)\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\"><g><path d=\\\"M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882\\\"></path></g></svg></button><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container view-image\\\"><svg xmlns=\\\"http://www.w3.org/2000/svg\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 24 24\\\" fill=\\\"none\\\" stroke=\\\"currentColor\\\" stroke-width=\\\"2\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" class=\\\"lucide lucide-maximize2 lucide-maximize-2\\\"><polyline points=\\\"15 3 21 3 21 9\\\"></polyline><polyline points=\\\"9 21 3 21 3 15\\\"></polyline><line x1=\\\"21\\\" x2=\\\"14\\\" y1=\\\"3\\\" y2=\\\"10\\\"></line><line x1=\\\"3\\\" x2=\\\"10\\\" y1=\\\"21\\\" y2=\\\"14\\\"></line></svg></button></div></div></div></a></figure></div><p><strong>Nuances:</strong></p><ul><li><p>Ideally the agents should use different models to reduce the risk of homogeneous thinking (e.g. same noise being amplified in consensus). This is exactly where <strong>diversity</strong> in human systems can help us solve novel problems.</p></li><li><p>Make sure that there are no feedback loops between the agents, otherwise the <a href=\\\"https://en.wikipedia.org/wiki/Groupthink\\\">Groupthink</a> and <a href=\\\"https://en.wikipedia.org/wiki/Bandwagon_effect\\\">bandwagon effect</a> can skew the results. They should run like a <em>blind experiment</em>.</p></li><li><p>This method is too expensive because we\u2019re essentially giving the same task to multiple agents. The ROI (return on investment) needs to be calculated depending on the task and cost of failure.</p></li></ul><p><strong>Best For:</strong> Fact-checking and classification (e.g., \u201CIs this email spam?\u201D).</p><h2>Pattern 3: The Adversarial Debate (The Courtroom)</h2><p><em>We\u2019re replacing \u201CAlignment\u201D with \u201CPush backs, checks and Balances.\u201D</em></p><p>LLMs are \u201CYes-Men.\u201D They rarely correct themselves once they start writing. You need a designated hater. A \u201Cdevil\u2019s advocate\u201D so to speak. \uD83D\uDE08</p><p>Humans may experience fear (of rejection or being wrong) but LLMs don\u2019t. We simulate that fear by using an external critic and judge. </p><h3>Implementation</h3><ul><li><p><strong>Generator:</strong> \u201CHere is my plan.\u201D</p></li><li><p><strong>Critic:</strong> \u201CHere are 3 reasons why that plan sucks.\u201D (acting devil\u2019s advocate)</p></li><li><p><strong>Judge:</strong> \u201CThe Critic is right. Fix it.\u201D (acting moderator)</p></li></ul><div class=\\\"captioned-image-container\\\"><figure><a class=\\\"image-link image2 is-viewable-img\\\" target=\\\"_blank\\\" href=\\\"https://substackcdn.com/image/fetch/$s_!e03-!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png\\\" data-component-name=\\\"Image2ToDOM\\\"><div class=\\\"image2-inset\\\"><picture><source type=\\\"image/webp\\\" srcset=\\\"https://substackcdn.com/image/fetch/$s_!e03-!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 424w, https://substackcdn.com/image/fetch/$s_!e03-!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 848w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1272w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1456w\\\" sizes=\\\"100vw\\\"><img src=\\\"https://substackcdn.com/image/fetch/$s_!e03-!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png\\\" width=\\\"1274\\\" height=\\\"759\\\" 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srcset=\\\"https://substackcdn.com/image/fetch/$s_!e03-!,w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 424w, https://substackcdn.com/image/fetch/$s_!e03-!,w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 848w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1272w, https://substackcdn.com/image/fetch/$s_!e03-!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe386e57d-da35-44a4-b0ab-448f35eb213c_1274x759.png 1456w\\\" sizes=\\\"100vw\\\" loading=\\\"lazy\\\"></picture><div class=\\\"image-link-expand\\\"><div class=\\\"pencraft pc-display-flex pc-gap-8 pc-reset\\\"><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container restack-image\\\"><svg aria-hidden=\\\"true\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 20 20\\\" fill=\\\"none\\\" stroke-width=\\\"1.5\\\" stroke=\\\"var(--color-fg-primary)\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\"><g><path d=\\\"M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882\\\"></path></g></svg></button><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container view-image\\\"><svg xmlns=\\\"http://www.w3.org/2000/svg\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 24 24\\\" fill=\\\"none\\\" stroke=\\\"currentColor\\\" stroke-width=\\\"2\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" class=\\\"lucide lucide-maximize2 lucide-maximize-2\\\"><polyline points=\\\"15 3 21 3 21 9\\\"></polyline><polyline points=\\\"9 21 3 21 3 15\\\"></polyline><line x1=\\\"21\\\" x2=\\\"14\\\" y1=\\\"3\\\" y2=\\\"10\\\"></line><line x1=\\\"3\\\" x2=\\\"10\\\" y1=\\\"21\\\" y2=\\\"14\\\"></line></svg></button></div></div></div></a></figure></div><p><strong>Nuances:</strong></p><ul><li><p>Ideally the Generator, Critic and Judge use 3 different models with different training or fine-tuning or prompt (in the order or preference and accuracy). Again, diversity is useful.</p></li><li><p>Due to sequential execution and the looping nature, it can be very slow. </p></li><li><p>The loop is actually a huge problem because the agents may get stuck in debate. We may use a <strong>watchdog pattern</strong> (deterministic code) to break the loop if it continues beyond a time or counter threshold. In that case, the watchdog sits between critic and the judge.</p></li></ul><p><strong>Best For:</strong> Security analysis, code review, and high-stakes content moderation.</p><h2>Pattern 4: Tree of Thoughts</h2><p><em>We\u2019re replacing \u201CFear of Death\u201D with \u201CSurvival of the Fittest.\u201D</em></p><p>This is a lean implementation of the <a href=\\\"https://en.wikipedia.org/wiki/Genetic_algorithm\\\">Genetic Algorithms</a> (GA) from traditional ML (Machine Learning) which relies on two elements:</p><ol><li><p>A <strong>genetic representation</strong> of the solution domain (a model and its context)</p></li><li><p>A <strong>fitness function</strong> to evaluate the solution domain (the eliminator)</p></li></ol><p>Since we can\u2019t punish an agent or threaten it to, we just delete it.</p><h3>Implementation</h3><ul><li><p>Give the task to <em>N </em>agents</p></li><li><p>Use a validator to decide which agents to eliminate</p></li><li><p>[optional] replace the dead agent with a new one that shares winner charactristics</p></li></ul><div class=\\\"captioned-image-container\\\"><figure><a class=\\\"image-link image2 is-viewable-img\\\" target=\\\"_blank\\\" href=\\\"https://substackcdn.com/image/fetch/$s_!sjT4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png\\\" data-component-name=\\\"Image2ToDOM\\\"><div class=\\\"image2-inset\\\"><picture><source type=\\\"image/webp\\\" srcset=\\\"https://substackcdn.com/image/fetch/$s_!sjT4!,w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 424w, https://substackcdn.com/image/fetch/$s_!sjT4!,w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0dfe63a6-c67f-4c60-b22d-371880445599_1370x1883.png 848w, 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class=\\\"image-link-expand\\\"><div class=\\\"pencraft pc-display-flex pc-gap-8 pc-reset\\\"><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container restack-image\\\"><svg aria-hidden=\\\"true\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 20 20\\\" fill=\\\"none\\\" stroke-width=\\\"1.5\\\" stroke=\\\"var(--color-fg-primary)\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\"><g><path d=\\\"M2.53001 7.81595C3.49179 4.73911 6.43281 2.5 9.91173 2.5C13.1684 2.5 15.9537 4.46214 17.0852 7.23684L17.6179 8.67647M17.6179 8.67647L18.5002 4.26471M17.6179 8.67647L13.6473 6.91176M17.4995 12.1841C16.5378 15.2609 13.5967 17.5 10.1178 17.5C6.86118 17.5 4.07589 15.5379 2.94432 12.7632L2.41165 11.3235M2.41165 11.3235L1.5293 15.7353M2.41165 11.3235L6.38224 13.0882\\\"></path></g></svg></button><button tabindex=\\\"0\\\" type=\\\"button\\\" class=\\\"pencraft pc-reset pencraft icon-container view-image\\\"><svg xmlns=\\\"http://www.w3.org/2000/svg\\\" width=\\\"20\\\" height=\\\"20\\\" viewBox=\\\"0 0 24 24\\\" fill=\\\"none\\\" stroke=\\\"currentColor\\\" stroke-width=\\\"2\\\" stroke-linecap=\\\"round\\\" stroke-linejoin=\\\"round\\\" class=\\\"lucide lucide-maximize2 lucide-maximize-2\\\"><polyline points=\\\"15 3 21 3 21 9\\\"></polyline><polyline points=\\\"9 21 3 21 3 15\\\"></polyline><line x1=\\\"21\\\" x2=\\\"14\\\" y1=\\\"3\\\" y2=\\\"10\\\"></line><line x1=\\\"3\\\" x2=\\\"10\\\" y1=\\\"21\\\" y2=\\\"14\\\"></line></svg></button></div></div></div></a></figure></div><p><strong>Nuances:</strong></p><ul><li><p>You need a fast way to verify the output (like a unit test). If you need a human to check all 10 branches, it\u2019s too slow and error prone. This is where Evals come in (topic for the next post).</p></li><li><p>A more advance setup may create new agents by trying to combine the prompts of the agents that pass the verification and fill in the slot that becomes available after the elimination.</p></li></ul><p><strong>Best for:</strong> Iterative agent engineering. This is typically useful during development or debugging an existing multi-agent system not in production and real user load.</p><div class=\\\"digest-post-embed\\\" data-attrs=\\\"{&quot;nodeId&quot;:&quot;e3729001-df41-4ff3-b6e8-efbe806ccf70&quot;,&quot;caption&quot;:&quot;This article is an overview of my best learning and experience in the past 2.5 years.&quot;,&quot;cta&quot;:&quot;Read full story&quot;,&quot;showBylines&quot;:true,&quot;showDescription&quot;:true,&quot;showImage&quot;:true,&quot;size&quot;:&quot;sm&quot;,&quot;isEditorNode&quot;:true,&quot;title&quot;:&quot;AI Systems Engineering Patterns&quot;,&quot;publishedBylines&quot;:[{&quot;id&quot;:87732486,&quot;name&quot;:&quot;Alex Ewerl\u00F6f&quot;,&quot;bio&quot;:&quot;Writes about technical leadership, growth mindset, and system reliability engineering. Senior Staff Engineer, MSc Systems Engineering from KTH, Stockholmer, dad, amateur artist. Read more here: https://www.alexewerlof.com/who&quot;,&quot;photo_url&quot;:&quot;https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fe2713990-da82-481b-b579-01a7aaa5b85b_560x560.jpeg&quot;,&quot;is_guest&quot;:false,&quot;bestseller_tier&quot;:null}],&quot;post_date&quot;:&quot;2025-11-30T11:56:00.000Z&quot;,&quot;cover_image&quot;:&quot;https://substackcdn.com/image/fetch/$s_!dVgq!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F438a529a-e0d1-48f1-93a8-601e63febe89_1163x674.png&quot;,&quot;cover_image_alt&quot;:null,&quot;canonical_url&quot;:&quot;https://blog.alexewerlof.com/p/ai-systems-engineering-patterns&quot;,&quot;section_name&quot;:&quot;Code&quot;,&quot;video_upload_id&quot;:null,&quot;id&quot;:183271454,&quot;type&quot;:&quot;newsletter&quot;,&quot;reaction_count&quot;:88,&quot;comment_count&quot;:0,&quot;publication_id&quot;:1002265,&quot;publication_name&quot;:&quot;Alex Ewerl\u00F6f Notes&quot;,&quot;publication_logo_url&quot;:&quot;https://substackcdn.com/image/fetch/$s_!_Ur2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F8c58cb07-9341-402b-bcdb-9fa767c2cdac_500x500.png&quot;,&quot;belowTheFold&quot;:true,&quot;youtube_url&quot;:null,&quot;show_links&quot;:null,&quot;feed_url&quot;:null}\\\"></div><h1>Conclusion</h1><p>The shift from \u201CAI Prototype\u201D to \u201CEnterprise AI\u201D is simple: stop treating LLMs like magic chatbots. Start treating them like unreliable components in a distributed system.</p><p>We don\u2019t need AI that \u201Ccares.\u201D We need AI that is <strong>constrained</strong>, <strong>verified</strong>, <strong>pruned</strong>, and <strong>challenged</strong>.</p><p>Don\u2019t anthropomorphize LLMs! Find a way to piggy back on their human-corpus training while being aware of their non-biological differences.</p><p><em>The next article is already written: how to actually build that verifier box?</em></p><div class=\\\"captioned-button-wrap\\\" data-attrs=\\\"{&quot;url&quot;:&quot;https://blog.alexewerlof.com/p/multi-agent-system-reliability?utm_source=substack&utm_medium=email&utm_content=share&action=share&quot;,&quot;text&quot;:&quot;Share&quot;}\\\" data-component-name=\\\"CaptionedButtonToDOM\\\"><div class=\\\"preamble\\\"><p class=\\\"cta-caption\\\">If you found this post insightful pls share it in your circles and on social media to inspire others</p></div><p class=\\\"button-wrapper\\\" data-attrs=\\\"{&quot;url&quot;:&quot;https://blog.alexewerlof.com/p/multi-agent-system-reliability?utm_source=substack&utm_medium=email&utm_content=share&action=share&quot;,&quot;text&quot;:&quot;Share&quot;}\\\" data-component-name=\\\"ButtonCreateButton\\\"><a class=\\\"button primary\\\" href=\\\"https://blog.alexewerlof.com/p/multi-agent-system-reliability?utm_source=substack&utm_medium=email&utm_content=share&action=share\\\"><span>Share</span></a></p></div><div><hr></div><p><em><a href=\\\"https://blog.alexewerlof.com/p/faq#%C2%A7payment\\\">My monetization strategy</a> is to give away most content for free but these posts take anywhere from a few hours to a few days to draft, edit, research, illustrate, and publish. I pull these hours from my private time, vacation days and weekends. The simplest way to support this work is to <strong>like</strong>, <strong>subscribe</strong> and <strong>share</strong> it. If you really want to support me lifting our community, you can consider a paid subscription. If you want to save, you can get 20% off via <a href=\\\"https://blog.alexewerlof.com/protipsdiscount\\\">this link</a>. As a token of appreciation, subscribers get full access to the Pro-Tips sections and my online book <a href=\\\"https://blog.alexewerlof.com/p/rem\\\">Reliability Engineering Mindset</a>. Your contribution also funds my open-source products like <a href=\\\"https://slc.alexewerlof.com/\\\">Service Level Calculator</a>. You can also <a href=\\\"https://blog.alexewerlof.com/leaderboard\\\">invite your friends</a> to gain free access.</em></p><p><em>And to those of you who already support me: <strong>thank you</strong> for sponsoring this content for others. \uD83D\uDE4C If you have questions or feedback, or want me to dig deeper into something, please let me know in the comments.</em></p>\",\"has_dynamic_content\":false,\"truncated_body_text\":\"LLMs are slow and too generic out of the box. 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Senior Staff Engineer, MSc Systems Engineering from KTH, Stockholmer, dad, amateur artist. 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As always \uD83D\uDE4C\uD83C\uDFFC A lot of these multi agent workflows guzzle up tokens - chatty interfaces between agents means the context builds up real quick with each turn. I observe that many companies are not yet at a point where tokenomics is a concern but we will get there very soon. Would love to hear your thoughts on the topic.\",\"body_json\":{\"type\":\"doc\",\"attrs\":{\"schemaVersion\":\"v1\"},\"content\":[{\"type\":\"paragraph\",\"content\":[{\"type\":\"text\",\"text\":\"Nice article Alex. As always \uD83D\uDE4C\uD83C\uDFFC A lot of these multi agent workflows guzzle up tokens - chatty interfaces between agents means the context builds up real quick with each turn. I observe that many companies are not yet at a point where tokenomics is a concern but we will get there very soon. 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