Productivity

AI-generated JIRA tickets and PRs have become word walls. Here's why your automation needs both a human summary and a machine-readable payload.

Compare GLM, Qwen, and Gemma local LLMs - benchmarks, context sizing, and when home GPU inference beats cloud token costs.

How engineering leaders adopt AI coding tools—from completion to agents—without trading speed for quality.

Essential resources for mastering agentic AI development — core concepts and guides for GitHub Copilot, Claude Code, Cursor, and OpenAI Codex.

A blog post exploring my two-week experiment using GitHub Copilot CLI for all coding tasks as a generative AI skeptic.

Discover 16 practical tips for writing AI-ready C# code, making your .NET codebase easier for AI agents and tools to understand, maintain, and extend.

Discover how GitHub Copilot Agents can function as AI developers on your team, automating development while complementing human developers' strategic skills.

Web chat portals can profoundly empower your team to build amazing things. Let's see how these systems can work securely and offer unique value to your team.

Model Context Protocol (MCP) and Agent2Agent (A2A) are rising stars in the world of AI. Let's see what they are and how they can work together.

This article defines an architecture for helping developers with software engineering tasks in a secure manner that utilizes organizational knowledge and data.