glossary.

Low-value AI-generated content. Usually slop means work produced quickly and in large volumes with little critical human oversight, and it often pops up in the places where we'd expect human-grade material, so the contrast makes it visible. AI slop can be images, articles, reviews, music, video, even company reports. AI slop is content with a bad ratio of considered thought to content volume. But AI generated content isn't necessarily slop, and slop isn't negative only because AI was involved. It's actually the lack of good human judgement to filter, craft and edit the AI generated content that creates the slop part. Merriam-Webster made "slop" its word of the year in 2025, and LinkedIn now even has a "report AI slop" button to counter the flood of AI generated content that's boomed on the platform.

We all know an AI vampire, and it might even be you. The AI Vampire works late into the night emboldened and empowered by the dramatic uptick in productivity they can achieve when using AI. It's not all great news, as AI Vampiring can leave us fatigued after those midnight screen-time hours. AI Vampires might actually just be creating AI slop or volumes and volumes of AI reports ready to fire off to team members for action (or rather, for them to paste into their own AI for summarisation). Or even just resetting the baseline of what's expected at work, fuelled in part by unhealthy work-life balance. The phrase was possibly coined by veteran engineer Steve Yegge in 2026, named after the Energy Vampire in What We Do In The Shadows, who links it to burnout especially amongst software engineers.

Cognitive offloading is where we push our thinking onto someone or something else, and in the case of AI, onto AI. You don't remember phone numbers any longer? That's cognitive offloading to your phone. With AI the amount we can offload is huge, and it happens without us really noticing. Cognitive offloading is so tempting because our attention and working memory are limited and the hit of speedy and immediate performance from AI can be strong. The challenge is where our offloading is uncritical or excessive, when we're delegating much of our work, or the process of understanding and judgement as well as execution, into AI. It de-skills us. It reduces learning, as the learning is shallower. We get weaker at detecting errors. And over time we risk more homogeneous thinking, as teams using the same models may produce the same kinds of output. For problem solving or for parts of an organisation where creativity and divergent thinking are required this can be an issue. The long-term cognitive effects of generative AI are not well established, but early research suggests our brains do change with use.