Think Different

  In an AI-native engineering architecture, the skills.md file acts as a centralized agent capability index and skill-routing table within the hidden system context directory ( .gemini/ , .cursor/ , or .windsurf/ ). Its primary purpose is to solve the context window expansion problem by decoupling task intent from heavy architectural definitions. Instead of injecting all project rules, schemas, linting standards, and tooling instructions into the system prompt simultaneously—which wastes context budget and degrades reasoning— skills.md maintains a lightweight semantic index mapping agent goals to specific rule files or external tools. Core Architecture & Responsibilities Plaintext ┌────────────────────────┐ │ User / Agent Task │ └───────────┬────────────┘                          │ Reads S...

Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and Copilot Studio are complementary but distinct parts of Microsoft’s AI ecosystem: Foundry is the developer platform, OpenAI is the raw model API, Fabric is the unified data layer, and Copilot Studio is the low-code agent builder. Together, they integrate with Entra ID (Azure AD) to manage agent identity, authentication, and enterprise governance. 🔑 Differences Among the Platforms Azure AI Foundry Azure OpenAI Microsoft Fabric Copilot Studio Full developer platform for building, fine-tuning, and deploying AI apps at scale Direct access to GPT-family models (text, embeddings, multimodal) Unified data analytics platform combining Power BI, Synapse, Data Factory Low-code tool for building and publishing AI copilots/agents Best for ML engineers & pro developers Best for developers needing raw model control Best for data engineers & analysts Best for business analysts & low-code developers Offers orchestration, pipelines, mult...

When executing multi-file refactors, I manage, restrict, and structure my local codebase context using a strict hierarchical filtering system designed to maximize accuracy and minimize token waste. Here is exactly how I structure and execute that process: 1. Discovery and Map Generation Before reading or editing any files, I construct an abstract map of the codebase. I do not pull full source code at this stage. Directory Trees: I run a shallow directory listing to understand the project's layout. Symbols and Signatures: I search for class definitions, method signatures, and export statements across the target modules. Dependency Graphs: I map out how the target files import one another to identify the upstream and downstream impacts of the refactor. 2. Context Restriction (The "Need-to-Know" Filter) To prevent token bloat and LLM confusion, I categorize files into three strict isolation zones: The Edit Zone: These are the exact files that require code modifications....