Deep dives into agentic AI, LLM evaluation, synthetic data generation, model selection, and production AI engineering best practices.
9 of 314 articles
A complete guide to building a production-grade AI documentation assistant using Retrieval-Augmented Generation, covering chunking strategies, embedding models, vector stores, and answer synthesis.
Practical security guide for production LLM applications -- prompt injection, jailbreak techniques, and layered defenses that work in production.
Learn how to design and implement multi-agent systems using the Claude API and Agent SDK. Covers architecture patterns, inter-agent communication, task delegation, and real-world production examples.
Deep dive into the orchestrator-subagent architecture pattern used in Claude Code and the Claude Agent SDK. Learn how task decomposition, delegation, and result synthesis work under the hood.
Complete guide to implementing tool use (function calling) with the Claude API. Covers tool definitions, execution patterns, multi-turn conversations, and production best practices.
Explore the architecture, limitations, and practical patterns for running LLM inference and AI workloads on serverless platforms like AWS Lambda and Google Cloud Functions.
A step-by-step guide to building a production-grade LLM evaluation framework that measures accuracy, safety, and quality across model versions and prompt changes.
How to implement end-to-end observability for AI agents using OpenTelemetry traces, LangSmith, and custom instrumentation to debug failures and optimize performance.
