Onboarding Playbooks for AI-Powered PHP Apps

When you're building AI features into PHP apps, onboarding playbooks, structured guides that standardize how teams set up, test, and deploy AI tools in production. Also known as AI integration playbooks, they turn chaotic setup processes into repeatable, secure workflows that keep developers moving fast without breaking things. Without them, teams waste weeks debugging permission errors, misconfigured APIs, or mismatched model versions—especially when using OpenAI, Anthropic, or local LLMs through Composer packages.

These playbooks aren’t just for big companies. Even small PHP teams using LLM deployment, the process of running large language models in production environments with proper scaling, monitoring, and security need clear steps for handling tokens, rate limits, and cost controls. You’ll find real examples in this collection: how one team cut their LLM billing by 60% using scheduling and spot instances, or how another locked down data privacy with confidential computing and TEEs. These aren’t theories—they’re battle-tested routines from developers who’ve been burned before.

What makes these playbooks powerful is how they connect to other critical pieces. AI integration, the act of embedding AI capabilities like chatbots, content moderation, or RAG into existing PHP systems doesn’t happen in a vacuum. It needs secure multi-tenancy, proper error analysis for prompts, and clear KPIs to measure success. That’s why this collection includes guides on vendor lock-in avoidance with LiteLLM, how to audit model weights for supply chain risks, and how to design design systems that keep AI-generated UI consistent. You won’t find fluff here—just the exact steps teams use to go from a working prototype to a production-ready AI feature in PHP.

Whether you’re a founder trying to ship fast with vibe coding or a senior dev managing enterprise LLM governance, these playbooks give you the structure to move confidently. Below, you’ll find detailed breakdowns of real deployments—from how to compose pretraining corpora for domain-specific models to how to measure policy adherence with MTTR and review coverage. Every post here solves a real problem that comes up when AI meets PHP in the wild.