--- title: Developers should be aware of these two AI engineering... description: Two emerging engineering practices for building reliable AI agentic systems are introduced: Graph Engineering, which breaks work into smaller connected tasks... canonical: https://daily.dev/posts/developers-should-be-aware-of-these-two-ai-engineering-approaches-lgfvrktej twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Developers should be aware of these two AI engineering approaches | daily.dev og:description: Two emerging engineering practices for building reliable AI agentic systems are introduced: Graph Engineering, which breaks work into smaller connected tasks... og:url: https://daily.dev/posts/developers-should-be-aware-of-these-two-ai-engineering-approaches-lgfvrktej og:image: https://api.daily.dev/og/posts/LgFVrktej.png og:image:alt: Developers should be aware of these two AI engineering approaches 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. # Developers should be aware of these two AI engineering approaches **[Pavan Belagatti](https://daily.dev/sources/dfa0u7-fs)** · [@johhnypav](https://daily.dev/johhnypav) · 2 min read · 50 upvotes · 10 comments ## Summary Two emerging engineering practices for building reliable AI agentic systems are introduced: Graph Engineering, which breaks work into smaller connected tasks with explicit inputs/outputs instead of one massive prompt, and Harness Engineering, which gives AI coding agents the broader context (service ownership, dependencies, rules, permissions, verification methods) needed beyond mere code generation. Links to video guides covering a payment bug fix example and a scorecard-based deployment gate are included. ## Content As a developer, there are two engineering practices you should be aware of - Harness Engineering & Graph Engineering, to build reliable agentic systems. **Graph Engineering** is becoming one of the most useful ways to build reliable AI-native engineering systems. Instead of putting everything into one massive prompt and hoping an AI model handles every detail correctly, I design the work as a connected system of smaller, explicit tasks. Each task has a purpose, a defined input, an output, and a route to the next step. That is the core idea behind Graph Engineering. It gives AI agents structure, makes their decisions easier to inspect, and lets independent work happen in parallel. Similarly, Harness Engineering is becoming essential because AI coding agents are getting very good at generating code, but code generation is only one small part of real software engineering. A useful agent must also understand the service it is working on, the team that owns it, its dependencies, the engineering rules it must follow, what it is allowed to change, and how to verify that its work is correct. That complete environment is what makes an AI agent reliable. In this guide, I will explain Harness Engineering in a simple way, then walk through two practical implementations: a controlled payment bug fix and a scorecard-based deployment gate. Well, I would like to share the guides around these two engineering approaches. Here is my video guide on harness engineering: [https://youtu.be/vAHnGUWPPNY](https://youtu.be/vAHnGUWPPNY?si=kMliPXcr6L3Jp6N5) Here is my video guide on graph engineering: [https://youtu.be/g3C7mudBURA](https://youtu.be/g3C7mudBURA?si=xrF8qOMFNjovsV7j) ## Community discussion Top comments from developers on daily.dev. **@andrewduncan** · 3 upvotes > interesting article! Small edit @johhnypav your thumbnail has the descriptions backwards. the description for graph engineering appears under harness engineering, and the description for harness engineering appears under graph engineering. > > Graph engineering has fascinating potential **@harshitmanepally** · 1 upvotes > A great article. Helpful for beginners. **@swarnasharmin** · 1 upvotes > Graph architecture paired with strict harness rules is exactly how we move from flaky LLM demos to production-grade agents. **@jeremiahcharles69** · 1 upvotes > Hey > > Thanks for bringing this here, it was really helpful. **@itskiranrao** · 0 upvotes > Smaller tasks also make debugging easier. You can see which step went wrong instead of digging through one huge agent run. ## Similar posts on daily.dev - [The rise of agentic engineering](https://daily.dev/posts/the-rise-of-agentic-engineering-arnnwynck) · Data Science Central · 3 upvotes · 0 comments - [Graph Engineering for AI Agents: From Prompts and Loops to Workflows](https://daily.dev/posts/graph-engineering-for-ai-agents-from-prompts-and-loops-to-workflows-dblplaofw) · Towards Data Science · 0 upvotes · 0 comments - [From MCP and Vibe Coding to Harness Engineering: How Did AI Native Engineering Evolve in One Year](https://daily.dev/posts/from-mcp-and-vibe-coding-to-harness-engineering-how-did-ai-native-engineering-evolve-in-one-year-7maibegpy) · InfoQ · 0 upvotes · 0 comments --- Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#architecture](https://daily.dev/tags/architecture), [#prompt-engineering](https://daily.dev/tags/prompt-engineering) [View this post on daily.dev](https://daily.dev/posts/developers-should-be-aware-of-these-two-ai-engineering-approaches-lgfvrktej) ```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":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/developers-should-be-aware-of-these-two-ai-engineering-approaches-lgfvrktej","headline":"Developers should be aware of these two AI engineering approaches","text":"Two emerging engineering practices for building reliable AI agentic systems are introduced: Graph Engineering, which breaks work into smaller connected tasks with explicit inputs/outputs instead of one massive prompt, and Harness Engineering, which gives AI coding agents the broader context (service ownership, dependencies, rules, permissions, verification methods) needed beyond mere code generation. Links to video guides covering a payment bug fix example and a scorecard-based deployment gate are included.","url":"https://daily.dev/posts/developers-should-be-aware-of-these-two-ai-engineering-approaches-lgfvrktej","datePublished":"2026-10-11T16:58:28.770Z","dateModified":"2026-10-12T04:45:09.223Z","author":{"@type":"Person","name":"Pavan Belagatti","url":"https://daily.dev/johhnypav","image":"https://media.daily.dev/image/upload/s--r9dshbly--/f_auto/v1776930121/avatars/avatar_DFA0U7-fS?_a=BAMAMiWQ0","description":"Developer Evangelist","interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"EndorseAction"},"userInteractionCount":3230}},"image":"https://media.daily.dev/image/upload/s--bKMdkuJE--/f_auto/v1791780308/posts/LgFVrktej?_a=BAMAMicg0","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":50},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":10}],"comment":[{"@type":"Comment","text":"interesting article! Small edit @johhnypav your thumbnail has the descriptions backwards. the description for graph engineering appears under harness engineering, and the description for harness engineering appears under graph engineering.\nGraph engineering has fascinating potential","datePublished":"2026-10-12T02:19:07.353Z","url":"https://daily.dev/posts/LgFVrktej#c-RtMV71QT6","author":{"@type":"Person","name":"Andrew Duncan","url":"https://daily.dev/andrewduncan","image":"https://lh3.googleusercontent.com/a/ACg8ocIOpyCFieHnXPAc199x8b2A7uhSGmRANbdNykfN9iOaYPIG6vU=s96-c"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3}},{"@type":"Comment","text":"A great article. Helpful for beginners.","datePublished":"2026-10-12T05:36:14.922Z","url":"https://daily.dev/posts/LgFVrktej#c-aeflBehyu","author":{"@type":"Person","name":"HARSHIT MANEPALLY","url":"https://daily.dev/harshitmanepally","image":"https://media.daily.dev/image/upload/s--O0TOmw4y--/f_auto/v1715772965/public/noProfile"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}},{"@type":"Comment","text":"Graph architecture paired with strict harness rules is exactly how we move from flaky LLM demos to production-grade agents.","datePublished":"2026-10-12T05:51:56.891Z","url":"https://daily.dev/posts/LgFVrktej#c-w84UkgIml","author":{"@type":"Person","name":"Swarna Sharmin","url":"https://daily.dev/swarnasharmin","image":"https://media.daily.dev/image/upload/s--joHEq_jD--/f_auto/v1791022797/avatars/avatar_ZL6bebyCVkszL2cr0g8ab?_a=BAMAMicg0"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}},{"@type":"Comment","text":"Hey\nThanks for bringing this here, it was really helpful.","datePublished":"2026-10-12T07:13:56.089Z","url":"https://daily.dev/posts/LgFVrktej#c-RVskB6yNW","author":{"@type":"Person","name":"Jeremiah Charles","url":"https://daily.dev/jeremiahcharles69","image":"https://lh3.googleusercontent.com/a/ACg8ocJTFqBp-LCXy1SjhWhMIt18sz1Fwq9ON0v5KqVsaYRcZVfg-pPW=s96-c"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}},{"@type":"Comment","text":"Smaller tasks also make debugging easier. You can see which step went wrong instead of digging through one huge agent run.","datePublished":"2026-10-12T11:21:38.985Z","url":"https://daily.dev/posts/LgFVrktej#c-yLFq7AClq","author":{"@type":"Person","name":"Kiran Rao","url":"https://daily.dev/itskiranrao","image":"https://media.daily.dev/image/upload/s--hQa8XkPK--/f_auto/v1789152231/avatars/avatar_AmGE2HhTmmKGwLMuVkqQz?_a=BAMAMicg0"}}],"isPartOf":{"@type":"WebPage","url":"https://daily.dev/sources/dfa0u7-fs","name":"Pavan Belagatti"}} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Pavan Belagatti","item":"https://daily.dev/sources/dfa0u7-fs"},{"@type":"ListItem","position":3,"name":"Developers should be aware of these two AI engineering approaches"}]} ```