The Economics of Running AI Models in Production
AI costs scale directly with usage in ways that are easy to underestimate. Here’s how token pricing, model selection, caching, and batching affect your bill.
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Vector Embeddings Explained for Developers
Vector embeddings power semantic search, RAG, and recommendation systems. Here’s what they actually are, how similarity is measured, and how to work with them well.
Evaluating LLM Outputs: Metrics That Actually Matter
Shipping AI features based on manual spot-checks doesn’t scale. Here’s how to build real evaluation infrastructure — metrics, test sets, and LLM-as-judge done well.
Building a Chatbot with Function Calling: A Practical Walkthrough
Function calling turns a language model into something that can actually take action. A practical walkthrough of building a chatbot that uses tools reliably.
Fine-Tuning vs Prompting: When Each Approach Makes Sense
Fine-tuning and prompting solve different problems and carry different costs. Here’s a practical framework for deciding which approach — or neither — fits your use case.
A Guide to Laravel Events and Listeners
Events and listeners decouple “what happened” from “what to do about it” in Laravel apps. Here’s when to use them, queueing tips, and how to test them well.
Optimizing Laravel Artisan Commands for Automation
Artisan commands are a framework for building your own CLI tools with full access to your Laravel app. Here’s how to build them well, schedule them safely, and test them.
Laravel Policies and Gates: Authorization Done Right
Gates and Policies both handle authorization in Laravel, but they suit different situations. Here’s when to use each, and how to keep permission logic organized.
Building a Real-Time Notification System with Laravel and WebSockets
A practical guide to building real-time notifications with Laravel broadcasting, WebSockets, and Reverb — channels, authorization, queueing, and scaling.
Laravel Service Container and Dependency Injection Explained
A practical explanation of Laravel’s service container — how dependency injection works, binding interfaces, contextual binding, and why it matters for testing.