After 2 failed attempts in early 2024, Claude 3.5 Sonnet (October 2024) finally had the instruction-following capability needed. Built a production deployment orchestrator in 3 days that saved weeks per use.
I’ve learned through experience that there’s a fundamental truth about AI-assisted development: AI enforcement is not assured. You can write the most detailed skill file. You can craft the perfect system prompt. You can set up MCP servers with every tool imaginable. But here’s the uncomfortable truth: the AI decides whether to follow any of it. That’s not enforcement. That’s hope. TL;DR: LLMs are probabilistic and can’t guarantee workflow compliance. Skills and MCP tools extend capabilities but don’t enforce behavior. Claude Code Hooks solve this by providing deterministic control points—SessionStart, PreToolUse, and PostToolUse—that ensure critical actions always happen. As AI-generated code scales, you need automated validation systems that codify architectural rules, business constraints, and design patterns. Workflow orchestration must live outside the AI. ...
Instructions and tools tell LLMs what to do, but guardrails ensure they do it. Discover how to build validation feedback loops that make LLM outputs reliable through automated guardrails—with a 10-minute quick start guide.
After multiple failed attempts, I finally cracked the code for using LLMs to generate complex, production-ready software. Learn how AI went from a frustrating tool to a revolutionary development partner.