Genetic Programming is a well-studied approach for solving optimisation problems. Previously, a programmer wanting to make use of these techniques would have to either study and reimplement the state of the art, or use an off-the-shelf solution, like PonyGE. However, these tools still require the programmer to write a grammar. While most programmers may have heard of grammars, they are not commonly used by the average programmer. In addition, most python IDEs and linters do not understand these grammars, and thus misbehave in some way on another on these projects (such as by reporting some missing function which isn’t actually missing or not checking the grammar code at all). In this demo, we will present Genetic Engine (GEng), a GP framework. Instead of requiring a separate grammar, GEng infers the intended structure from class hierarchies and constructors. These are features that are familiar to the everyday programmer, making it a much more approachable framework. This demo will be structured as a live coding session, where several optimisation problems, increasing in complexity, will be modelled and solved with GEng. As the problems increase in complexity, so will the solutions, showcasing more and more GEng features. This demo is targeted at the common developer who has an interested in optimisation problems or search based problem solving. However, for this demo, no prior genetic programming experience is required.