Ai

There is a conversation happening right now in engineering circles about code reviews. The argument goes roughly like this: AI is generating code faster than humans can review it, PR volume is exploding, and we need smarter tooling to keep up. That argument is correct. And it is solving the wrong problem. The deeper issue is not that reviews don’t scale. It is that we are still treating the review as the primary quality gate — a last line of defence before code enters the codebase. In the age of AI-assisted development, that assumption needs to be challenged at its root. ...

In the current era of AI-driven development, the pressure to deliver “faster” has never been higher. With the advent of sophisticated coding agents, the first instinct for many project leads is to parallelize: split the work, run frontend and backend tracks simultaneously, and maximize output. However, this rush to parallelize often comes with a hidden cost that many organizations fail to account for. By optimizing for simultaneous output, we are inadvertently sacrificing the very Agility we claim to pursue. ...

A question recently surfaced in my LinkedIn feed that I haven’t been able to shake: How will the next generation of software developers gain experience when AI takes over the writing? The analogy offered was that of a conductor — someone who doesn’t need to play the violin to judge whether the orchestra is in harmony. It’s a compelling metaphor. But I think it lets us off the hook too easily. ...