--- title: Learn System Design for AI Agents: Build a... description: A free three-hour freeCodeCamp YouTube course by Ayush Singh teaches how to design and build a production-grade, multi-agent automated pull request review... canonical: https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Learn System Design for AI Agents: Build a Production-Ready Multi-Agent PR Reviewer | daily.dev og:description: A free three-hour freeCodeCamp YouTube course by Ayush Singh teaches how to design and build a production-grade, multi-agent automated pull request review... og:url: https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7 og:image: https://api.daily.dev/og/posts/8n8UXrys7.png og:image:alt: Learn System Design for AI Agents: Build a Production-Ready Multi-Agent PR Reviewer og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Learn System Design for AI Agents: Build a Production-Ready Multi-Agent PR Reviewer **[freeCodeCamp](https://daily.dev/sources/freecodecamp)** · 2 min read · 2 upvotes · 0 comments ## Summary A free three-hour freeCodeCamp YouTube course by Ayush Singh teaches how to design and build a production-grade, multi-agent automated pull request review system. It covers orchestrating parallel domain agents (security, code quality, testing, documentation) with LangGraph, unifying semantic search, relational data, and event traces in Tiger Cloud, securely decoupling GitHub webhooks with HMAC verification and Redis queuing, and adding verification gates, confidence-threshold approval queues, and token spend dashboards to guard against hallucinations and runaway cloud costs. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How can I orchestrate multiple AI agents to review pull requests for different concerns like security and code quality? Parallel domain agents can be orchestrated using LangGraph workflow patterns, with separate specialist agents assigned to security, code quality, testing, and documentation concerns. Their findings are then aggregated with explicit confidence scoring, mirroring how a senior engineer selectively applies judgment across a PR review. _Developers designing multi-agent review pipelines can track LangGraph patterns and agent orchestration techniques on daily.dev._ ### How do I securely handle GitHub webhooks for an automated PR review agent? Incoming GitHub webhooks should be decoupled using cryptographic HMAC verification to confirm authenticity, combined with idempotency deduplication to avoid processing duplicate events, and fast-acknowledgment queuing with Redis so the webhook responds quickly while processing happens asynchronously. _Anyone wiring AI agents into GitHub workflows can follow webhook security practices like these on daily.dev._ ### How can I prevent AI coding agents from causing unexpected cloud costs or acting on hallucinated results? Confidence-threshold approval queues can gate low-confidence agent findings before they take effect, while real-time token economics dashboards track spend as it happens, together safeguarding against both hallucinated outputs and runaway cloud costs from agent activity. _Teams guarding against agent cost overruns and hallucinations can follow this kind of guidance on daily.dev._ ## Similar posts on daily.dev - [Mastering AI Agents with LangGraph: Build Production-Ready Multi-Agent Systems](https://daily.dev/posts/mastering-ai-agents-with-langgraph-build-production-ready-multi-agent-systems-q67rjbwgf) · Medium · 0 upvotes · 0 comments - [AI Agents For Beginners](https://daily.dev/posts/ai-agents-for-beginners-99gpz92au) · freeCodeCamp · 1 upvotes · 0 comments - [Open Code Review: free, self-hosted AI code review agent](https://daily.dev/posts/open-code-review-free-self-hosted-ai-code-review-agent-5pu5mxvci) · FireUp · 0 upvotes · 0 comments - [AI Code Review at Scale: LinkedIn's Multi-Agent Approach](https://daily.dev/posts/ai-code-review-at-scale-linkedin-s-multi-agent-approach-7lpkuhkzi) · InfoQ · 0 upvotes · 0 comments --- Tags: [#career](https://daily.dev/tags/career), [#ai-agents](https://daily.dev/tags/ai-agents), [#redis](https://daily.dev/tags/redis), [#langgraph](https://daily.dev/tags/langgraph) [View this post on daily.dev](https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Learn System Design for AI Agents: Build a Production-Ready Multi-Agent PR Reviewer","url":"https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7"},"datePublished":"2026-08-20T16:56:22.508Z","dateModified":"2026-09-14T07:18:14.201Z","description":"A free three-hour freeCodeCamp YouTube course by Ayush Singh teaches how to design and build a production-grade, multi-agent automated pull request review...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/cfee0b3d7723c69604e91cdc6d8368b5?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/cfee0b3d7723c69604e91cdc6d8368b5?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"freeCodeCamp","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"freeCodeCamp","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1628412854/logos/freecodecamp","url":"https://daily.dev/sources/freecodecamp"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"career,ai-agents,redis,langgraph","timeRequired":"PT2M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"freeCodeCamp","item":"https://daily.dev/sources/freecodecamp"},{"@type":"ListItem","position":3,"name":"Learn System Design for AI Agents: Build a Production-Ready Multi-Agent PR Reviewer"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/learn-system-design-for-ai-agents-build-a-production-ready-multi-agent-pr-reviewer-8n8uxrys7#faq","mainEntity":[{"@type":"Question","name":"How can I orchestrate multiple AI agents to review pull requests for different concerns like security and code quality?","acceptedAnswer":{"@type":"Answer","text":"Parallel domain agents can be orchestrated using LangGraph workflow patterns, with separate specialist agents assigned to security, code quality, testing, and documentation concerns. 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