AI For Developers
AI from a developer's perspective — practical, not theoretical. Learn to integrate AI into your workflow, understand AI architecture, and build AI-powered apps.
A series on AI for developers — not "what is AI" but "how to use AI". Each post is a practical guide with code examples and decision frameworks you can apply to your project immediately.
Posts in this series
DORA 2025: 90% of Developers Now Use AI in Daily Work
Google's DORA 2025 report shows AI is no longer a trend — it has become an indispensable tool for nearly all developers.
Simple Programming Languages and AI Coding Agents
AI coding agents perform better with less fragmented ecosystems. Go, Rails, and Rust produce more stable output than JavaScript or Python — reshaping how developers choose their stack.
Claude Code Mastery: From Casual User to Daily Driver
A deep dive into advanced Claude Code patterns — plan mode, CLAUDE.md, skills, subagents — that help developers achieve 2-3x quality improvements.
AI Coding Agents Hit Product-Market Fit — What It Means For Developers
Anthropic nears first profitable quarter; OpenAI puts 32% workforce into enterprise sales. Coding agents are no longer an experiment — developers must adapt.
Google I/O 2026: The Agentic AI Era and What Developers Need to Know
Google I/O 2026 was a manifesto for an era where AI doesn't just answer questions — it acts. Here's what Gemini 3.5 Flash, Antigravity 2.0, and Managed Agents mean for developers.
Zerostack: The Rust-Powered AI Coding Agent That Uses 16MB RAM
While most AI coding agents consume 300-700MB RAM, Zerostack uses just 16MB. Written in Rust with a 12.9MB binary — it challenges the assumption that AI tools must be bloated.
Microsoft Builds Its Own Coding Model, Drops Claude Code: The Distribution War in AI Coding
Microsoft is cancelling all Claude Code licenses and moving engineers to Copilot CLI running on a homegrown coding model. This isn't just about cost — it's a bet that distribution beats the best model.
LLMs Are Eroding Three Pillars of Developer Expertise
Domain knowledge, distributed debugging, architecture — three things that once made senior devs special are being commoditized by LLMs.