Category
AI & LLM
13 posts filed under AI & LLM.
Agree Before You Build: Five Gates for Enterprise AI Use Cases
A five-gate method for picking enterprise AI use cases and measuring AI ROI in a way finance will accept and delivery can instrument, with a claims example.
Magentic-UI + Fara-7B: A Local-First Computer-Use Agent You Can Actually Run
Microsoft's Magentic-UI pairs a small-model orchestrator with Fara-7B, a computer-use agent, in a local sandbox — an MIT-licensed stack worth cloning.
AI Security: Prompt Injection, Jailbreaks, and Guardrails
Prompt injection, indirect injection, jailbreaks, and data exfiltration via tools — the real threats and defense layers that work in production AI systems.
MCP: What It Is and Why It Changes How You Build AI Tools
MCP solves the N×M integration problem between AI models and tools. What it is, how it works, and why it matters before your next AI feature.
What Is an AI Agent? (And When Should You Build One)
What AI agents actually are, how they differ from a plain LLM call, the patterns in production, and when an agent is the right call — and when it isn't.
Microsoft Ignite 2025: Microsoft Foundry - The Unified Enterprise AI Platform
Microsoft Ignite 2025 unveiled Microsoft Foundry — a unified enterprise platform for agents, models, tools, and governance. What to adopt now and watch.
Build Custom MCP Catalogs with Docker: Enterprise Control for AI Tooling
Docker's MCP Catalog, Gateway, and Toolkit let a platform team curate which MCP servers developers can run and route every tool call through one gateway.
Streamlining AI Development with LiteLLM Proxy: A Comprehensive Guide
Running LiteLLM proxy with Open WebUI, Postgres, and Redis in Docker Compose — one OpenAI-compatible endpoint in front of OpenAI, Anthropic, and Ollama.
Elevating Code Quality with Custom GitHub Copilot Instructions
How to customize GitHub Copilot with instruction files for Angular 19 and .NET 8+, so suggestions follow your team's standards, not generic patterns.
Building a Comprehensive RAG System: A Deep Dive Into Knowledge Architecture
A guide to building a Retrieval-Augmented Generation (RAG) system — vector databases, document processing, and LLMs for knowledge retrieval.
Deploying Ollama with Open WebUI Locally: A Step-by-Step Guide
Deploy Ollama with Open WebUI locally via Docker Compose — run open-source language models on your own hardware for privacy and cost savings.
Simplifying Database Queries with AI & SQL Automation
A REST API that converts natural language into SQL queries using OpenAI, letting non-technical users query a database without SQL knowledge.
