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.

Practical techniques for giving AI agents the context they need: AGENTS.md files, documentation strategies, and plan mode workflows.

Gitflow is now a legacy workflow that bakes unplanned merge work into your sprints. Here's why to drop it for trunk-based development.

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

How Claude Code hooks create mechanical enforcement at commit time — blocking violations, injecting warnings, and coaching better habits before code ever reaches review.

Back-testing across three projects shows forecasting accuracy rises with team autonomy, controlled WIP, and data-driven flow management.

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

How treating AI tooling like a distracted junior developer resulted in production-quality software

What if your AI agents could learn from their mistakes and get better over time? Check out a sample architecture that does just that.

A conversation with an LLM AI on how to gradually improve a very procedural method through the use of functional programming techniques. I learned about contexts, how to pay careful attention to method signatures, and the strengths and weaknesses of different languages in the use of functional programming.