Recent Posts
Advanced Prompt Engineering: Chain-of-Thought, ReAct, and Tree-of-Thoughts Explained
March 21, 2026
A comprehensive guide to advanced prompt engineering techniques including Chain-of-Thought (CoT), ReAct, Tree-of-Thoughts, self-consistency, and prompt optimization strategies for production LLM applications.
Structured Outputs in LLMs: JSON Mode, Function Calling, and Schema Validation
March 19, 2026
A comprehensive guide to getting reliable structured outputs from LLMs using JSON mode, function...
Prompt Injection Attacks: How LLMs Get Exploited and How to Defend Your Application
March 14, 2026
A comprehensive guide to LLM security vulnerabilities including prompt injection, jailbreaking, and data exfiltration,...
LLM Observability: Tracing, Logging, and Debugging AI Applications
March 12, 2026
Learn how to implement proper observability for LLM applications, including prompt tracing, cost tracking,...
All Articles
Hybrid Search: Combining Keyword and Vector Search for Better Retrieval
March 05, 2026
Learn why production RAG systems combine keyword-based BM25 and vector embeddings for superior retrieval accuracy, and...
PEFT Methods Explained: LoRA, QLoRA, and Adapter-Based Fine-Tuning
February 27, 2026
Learn how parameter-efficient fine-tuning (PEFT) methods like LoRA and QLoRA allow you to customize large language...
Why Your LLM Application Feels Slow
February 22, 2026
Production LLM applications often feel slow not because of model limitations but due to architectural pipeline...
A Beginner’s Guide to Cost Optimization in LLM Applications
February 20, 2026
A complete beginner-friendly guide to optimizing costs in large language model applications, including model selection, prompt...
How Retrieval-Augmented Generation (RAG) Works
February 19, 2026
Understanding how Retrieval-Augmented Generation works and why it is important for modern AI applications.
What is an AI Agent?
February 18, 2026
A detailed breakdown of what LLM agents really are, how they work internally, and the architecture...
