Explore our latest articles about developer productivity
8 articles in this category
Claude Code silently changed the default reasoning effort to medium. Your output quality dropped and you might not even know why. Here's the fix and what to set based on your subscription tier.
Dmytro Chaban
GLM-5 launched with bold claims of beating Kimi K2.5 on intelligence, coding, and speed. After two weeks of real OpenClaw agentic workflow testing, here's the honest truth: benchmarks lie, z.ai is slow, and Kimi K2.5 still wins where it matters.
Dmytro Chaban
After a week of testing all three Codex interfaces, here's the setup that actually works: AGENTS.md for repo instructions, skills for repeatable workflows, and config.toml for MCP connections—without the trial-and-error.
Dmytro Chaban
Stop piecing together scattered docs. This is the complete, reproducible way to set up Gemini CLI: a minimal GEMINI.md, reusable skills, MCP tool connections, and quality-of-life hooks.
Dmytro Chaban
Stop trusting leaderboard scores. Here's a practical A/B testing method to find which AI model actually performs best on your specific tasks.
Dmytro Chaban
Stop duct-taping configs. This is the clean, reproducible way to set up Claude Code: a minimal CLAUDE.md, reusable skills, MCP tool connections, and quality-of-life hooks.
Dmytro Chaban
Kimi K2.5 is not the best model for everything, but it is often the best value for routine engineering work. This guide shows where Kimi wins, where Claude and Codex are stronger, and how to choose the right model by task type.
Dmytro Chaban
Two AI coding agents dropped on the same day. I tested both at enterprise scale. Here's why Claude Opus 4.6 wins despite what the benchmarks say.
Dmytro Chaban