{"slug": "building-an-ai-cloud-cost-intelligence-platform-that-doesn-t-let-ai-make", "title": "Building an AI Cloud Cost Intelligence Platform That Doesn't Let AI Make Infrastructure Decisions", "summary": "A developer building an Azure Cost Intelligence Platform discovered that AI-generated infrastructure recommendations often suggested non-existent VM SKUs and incorrect Azure CLI commands. To solve this, the system was redesigned so that the AI never makes decisions—it only explains verified recommendations produced by deterministic code and APIs. The project highlights that AI should augment engineering logic rather than replace it.", "body_md": "Most AI-powered cloud optimization demos follow a simple approach:\n\n```\nAzure Resources\n      ↓\nLarge Language Model\n      ↓\nRecommendations\n```\n\nAt first glance, this seems impressive.\n\nBut while building my own Azure Cost Intelligence Platform, I ran into a problem that completely changed my architecture.\n\nThe AI was generating infrastructure recommendations that looked correct—but some of them simply didn't exist.\n\nFor example, it suggested VM SKUs that Azure doesn't support and even produced Azure CLI commands with incorrect parameters. That was a wake-up call.\n\nInstead of trying to \"prompt engineer\" my way out of the problem, I redesigned the application.\n\nRather than letting AI make decisions, I split the system into independent components:\n\nThe AI never decides **what** to do—it only explains decisions that have already been made.\n\nInstead of asking the LLM:\n\n\"What should I do with this VM?\"\n\nthe backend first gathers facts:\n\n`Standard_B2ts_v2`\n\nThe recommendation engine then determines:\n\n```\nResize VM\n↓\nTarget SKU: Standard_B2ats_v2\n↓\nEstimated Savings: $0.74/month\n```\n\nFinally, the LLM produces a human-friendly explanation like:\n\n\"This virtual machine is significantly underutilized. Resizing it can reduce monthly costs without affecting current workloads.\"\n\nNotice that the AI never invents the recommendation or the command—it only explains verified data.\n\nThis project taught me an important lesson:\n\n**AI should not replace engineering logic.**\n\nCloud infrastructure decisions should come from verified APIs, business rules, and deterministic code. AI adds the most value when it helps engineers understand those decisions, not when it generates them.\n\nThat's the architecture I'll continue using as I expand this platform with historical cost trends, anomaly detection, and multi-cloud (AWS & GCP) support.\n\nIf you're building AI-assisted DevOps or FinOps tools, I'd love to hear how you're balancing automation with reliability.", "url": "https://wpnews.pro/news/building-an-ai-cloud-cost-intelligence-platform-that-doesn-t-let-ai-make", "canonical_source": "https://dev.to/upshivam786/building-an-ai-cloud-cost-intelligence-platform-that-doesnt-let-ai-make-infrastructure-decisions-5gbn", "published_at": "2026-06-29 04:11:00+00:00", "updated_at": "2026-06-29 04:27:23.511381+00:00", "lang": "en", "topics": ["artificial-intelligence", "developer-tools", "ai-products"], "entities": ["Azure", "AI", "VM", "Azure CLI"], "alternates": {"html": "https://wpnews.pro/news/building-an-ai-cloud-cost-intelligence-platform-that-doesn-t-let-ai-make", "markdown": "https://wpnews.pro/news/building-an-ai-cloud-cost-intelligence-platform-that-doesn-t-let-ai-make.md", "text": "https://wpnews.pro/news/building-an-ai-cloud-cost-intelligence-platform-that-doesn-t-let-ai-make.txt", "jsonld": "https://wpnews.pro/news/building-an-ai-cloud-cost-intelligence-platform-that-doesn-t-let-ai-make.jsonld"}}