Coding for agents

"Agents change that equation. They don't reward the cleverest workflow. They reward the most legible one and, increasingly, the one that is optimized for them. This may seem scary but it's actually healthy. Just ask Hamel Husain."

"I was swimming upstream, because nbdev's idiosyncratic approach was like fighting the AI instead of working with it. Instead, he says, he wants to work in an environment where AI has the highest chance of success. He's building according to what the machines like, and not necessarily what he prefers."

"Large language models and AI agents aren't important to software engineering because they can write code at superhuman speeds. Without the right guardrails, that speed simply translates into mass-produced technical debt. No, agentic coding matters because it fundamentally changes what counts as good software engineering."

AI agents and large language models are transforming software engineering not through speed, but by redefining what constitutes good code. Traditional development allowed optimization for personal taste and individual workflow preferences, but agents prioritize legibility and machine-friendliness. Developers like Hamel Husain are abandoning tools and approaches that don't align with AI capabilities, choosing instead to work with agent preferences rather than against them. This shift moves development tools from personal expression toward infrastructure optimization, requiring developers to write explicit, consistent, and well-documented code that machines can easily understand and work with effectively.

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