Practical guides on using AI tools like ChatGPT, GitHub Copilot in your workflow
101 articles
System prompts define how AI assistants behave, but they aren't always as secret as developers assume. Learn what system prompt leakage is, why it happens, the risks it creates, and how to build AI applications that remain secure even if prompts become exposed.
Is your deep learning model performing well during training but failing during inference? Learn why Batch Normalization causes inconsistent predictions, how training and inference modes differ, and the best practices for building reliable production models.
Aider is an AI-powered pair programmer designed to work directly with your existing codebase. Learn how to use Aider to diagnose bugs, understand unfamiliar projects, generate targeted fixes, and collaborate safely without losing control of your code.
Function calling enables LLM agents to interact with APIs, databases, and external tools, but poorly formed arguments can cause unexpected failures. Learn why tool calls break, common causes of invalid parameters, and proven techniques for building reliable AI agents.
Many Cursor AI users struggle with inaccurate code suggestions because they're providing the wrong context. Learn the difference between Notepads and Context Files, when to use each, and how proper context management dramatically improves AI-generated code quality.
Your Retrieval-Augmented Generation (RAG) application performs well during testing but suddenly experiences latency spikes in production. The problem isn't always the LLM. Learn how to identify whether your bottleneck is the embedding service, vector database, document retrieval, network, reranking,
Your recommendation model performed exceptionally during offline testing, but click-through rates dropped after deployment. The culprit may not be the ranking model—it could be embedding drift. Learn what embedding drift is, why it happens, how it affects recommendation systems, and practical
Modern AI coding assistants can do more than generate code—they can help debug it. Cursor AI's Agent Mode enables iterative debugging by inspecting code, proposing fixes, updating multiple files, and responding to compiler or test feedback. Learn how to use Agent Mode effectively while keeping human
Bigger context windows don't automatically produce better AI responses. In many cases, stuffing an LLM with excessive conversation history, documents, or retrieved passages reduces answer quality, increases latency, and introduces distractions. Learn why context window bloat occurs and how to keep
Your machine learning model produced well-calibrated probability estimates yesterday, but after retraining, its confidence scores no longer match reality. Learn why model calibration often degrades after retraining and how to build ML pipelines that maintain trustworthy probability predictions.
AI coding assistants have become an essential part of modern software development. Two of the most popular options—Codeium and GitHub Copilot—offer intelligent code completion, chat assistance, and multi-language support, but they differ in pricing, ecosystem integration, customization
Large Language Models don't hallucinate randomly. Certain categories of questions consistently produce higher rates of fabricated facts, nonexistent citations, invented APIs, and incorrect reasoning. Understanding these hallucination hotspots helps developers design safer AI applications