From Medieval Latin imaginarius, “relating to images”, from Latin imago, “image, likeness”.

1. 1
   adj. Existing only in the mind; having no physical or objective reality. The imaginary city served as a testing ground for new ideas.
2. 2
   adj. In mathematics, denoting a number that is a multiple of the square root of −1. Complex numbers combine real and imaginary components.
3. 3
   n. The shared space of what is imagined, especially in creative or conceptual work. The project lives in the imaginary shared by designers and engineers.
4. 4
   extended, in this lexicon A playful, exploratory “hors-sol” zone designed to protect real customer activities while experimenting freely. We first move ideas into the imaginary so they don’t disturb real customer flows.

Name of a fictional robot from an animated film, derived from the acronym “Waste Allocation Load Lifter – Earth-class”.

1. 1
   A small, box-shaped, trash-compacting robot, emblematic of curiosity, environmental care, and quiet persistence. Like WALL-E, the prototype patiently collects and compacts data.
2. 2
   by extension Any device or persona that tidies up a chaotic ecosystem and prepares the ground for new growth. In this workflow, the “WALL-E” component cleans the legacy data before training.
3. 3
   personal usage An old contraption that has accumulated lots of stuff: scripts, prototypes, leftovers, and odd treasures piled up over the years. Our ancient test server — a true WALL-E — still carries prototypes from a decade ago.

From English to train, “to instruct, to develop by practice”, with the agentive suffix -er.

1. 1
   A person who guides and structures practice to build skills or understanding. The trainer helped the team internalize the new workflow.
2. 2
   A system or learning environment designed to shape the behavior of another system, especially a machine-learning model. The semantic bicycle acts as a trainer for the model’s conceptual balance.
3. 3
   extended, in this lexicon A coach for surviving and thriving in the future AI world — helping people understand models, keep control of tools, and remain actors rather than spectators. The program is designed as a trainer to prepare teams for the silent shock of generative AI.