The most common question about our AI technology coverage is whether we're writing for engineers or for business readers, since technical AI topics can be covered at very different levels of depth depending on the intended audience, and readers want to know which one they're getting.
Why this question matters for how coverage actually reads
Technology coverage written for engineers assumes background knowledge and gets into implementation detail; coverage written for business readers has to build that context in and generally trades some technical precision for accessibility. Readers reasonably want to know which they're getting before investing time in a piece.
Our actual answer
We write primarily for business readers who need to understand technical AI developments well enough to make informed decisions, not for engineers who'd implement the technology directly - meaning we prioritize accurate, accessible explanation over technical exhaustiveness, without oversimplifying to the point of being misleading about what a technology actually does.
Why this balance is hard to hit consistently
Simplifying technical material for a business audience risks losing genuine, load-bearing nuance, while preserving too much technical precision risks losing the audience entirely. We don't think we get this balance exactly right in every piece, but it's the explicit target we're aiming at.
Why we think this framing matters to state clearly
Knowing which audience a piece of technical coverage is written for helps readers calibrate how much to rely on it for different purposes, and we'd rather state our target audience explicitly than leave readers guessing.