Codebase Tours: Explore Real AI Systems Built with PHP and LLMs

When you look at a codebase tour, a guided walkthrough of real, working AI systems showing how code is structured, secured, and scaled in production. Also known as live code walkthroughs, it's not theory—it's what happens after the demo ends and the app goes live. Most developers never see how large language models actually run inside a PHP app. They read blog posts about RAG or function calling, but rarely get to see the files, folders, and config lines that make it work. Codebase tours fix that.

These tours show you how companies use Retrieval-Augmented Generation, a method where LLMs pull answers from your own data instead of guessing from training inside PHP apps, how they secure LLM supply chain security, the process of verifying model weights, containers, and dependencies to prevent malicious code injection, and how they cut cloud costs using spot instances, low-cost cloud computing resources that can be taken away anytime, but are perfect for non-critical AI tasks. You’ll see how teams handle multi-tenancy so one customer’s data never leaks into another’s, and how they use vibe coding, a fast, AI-assisted development style where developers write less code and let tools generate the rest to ship features in days, not weeks.

These aren’t tutorials with placeholder code. These are real systems built by teams who’ve been burned by hallucinations, overpriced API calls, and compliance fines. You’ll find how one startup reduced their LLM bill by 70% using scheduling and model switching. You’ll see how a SaaS company locked down their data governance using Microsoft Purview and custom PHP filters. You’ll learn why truthfulness benchmarks like TruthfulQA matter when your users start asking medical or legal questions.

What you won’t find here are fluff pieces about "the future of AI." You’ll find exactly how to structure your PHP project when integrating LiteLLM to avoid vendor lock-in. How to write prompts that don’t accidentally leak customer data. How to set up automated SBOM scans for your Docker containers. How to measure MTTR when your AI starts giving wrong answers.

These codebase tours are for developers who want to move past proof-of-concept and actually ship. If you’ve ever stared at a working AI demo and wondered, "Okay, but how do I make this real?"—this collection shows you step by step, file by file, line by line. No theory. No hype. Just what works in production today.