Generative AI
Generative AI refers to AI systems that create new content—text, images, code, audio, video—rather than classifying or analyzing existing data. ChatGPT, DALL-E, Midjourney, and Stable Diffusion are all generative AI. The underlying models learn statistical patterns from training data and produce new outputs that follow those patterns. This is a meaningful shift from the previous decade of AI, which was dominated by discriminative models (spam filters, recommendation engines, fraud detectors) that sorted things into categories. Generative AI crossed into mainstream adoption faster than any technology since the smartphone, reaching 100 million users in two months. But the speed of adoption has outrun the infrastructure for using it well. Most organizations are still in the experimentation phase—running pilots, debating policies, and trying to figure out where generative AI creates value that justifies the cost, the risk, and the organizational change required to use it at scale.
Related terms:
Structured Output
Structured output occurs when a language model returns data in predictable, machine-readable formats—such as JSON, XML, or typed objects—rather than free-form prose, enabling software systems to reliably parse fields like names, dates, and dollar amounts. By using constrained generation to enforce a JSON schema, structured output transforms AI from a conversational interface into a dependable system component.
Foundation Model
A foundation model is a large AI model trained on broad data at massive scale, designed to be adapted to a wide range of downstream tasks rather than built for any single one. Coined in 2021 by Stanford’s Center for Research on Foundation Models, this approach boosts efficiency but concentrates power among providers like OpenAI, Google, Meta, and Anthropic.
WWGPTD
WWGPTD began as internal Slack shorthand to remind teams that using AI isn’t cheating but the essential first step. The accompanying bracelets serve to normalize AI as a fundamental tool for creating better work.