Engineering insights, tool updates, and developer ecosystem news.
The difference between good and bad AI-generated code is usually the prompt, not the model. Here are practical techniques for getting better results from Claude, GPT, and Copilot.
We analyzed survey data from 10,000 developers to measure the real productivity impact of AI pair programming tools.
How to fine-tune open-source models on your codebase for better completions. Practical guide with dataset preparation and evaluation.
We tested every major AI coding tool on real-world tasks. Here is what delivered results and what fell short of the hype.
How to set up and use local language models for coding, testing, and development without sending code to the cloud.
We tested all three AI coding tools on real projects. Here's which one wins for different workflows.
A guide to the top MCP servers that connect your AI assistant to PostgreSQL, MySQL, MongoDB, and other databases.
We tested seven AI code review tools on the same codebase. Here is how they stack up on accuracy, speed, and developer experience.
A hands-on comparison of the leading AI code review tools, tested on real pull requests across multiple languages.
Power-user techniques for Claude Code: custom commands, project context, and workflows that save hours per week.
I evaluate tools for AIDToolStack daily. Here is the systematic framework I use to assess whether a tool is worth adopting — in 30 minutes, not a weekend.
How to be an effective partner to your AI coding assistant: communication patterns, review habits, and productivity maximizers.
