Topology optimization is a field that combines physics simulation and (mathematical) optimization to optimize the shapes and designs of physical systems. It is an extremely rich and fast growing field with its roots in structural and solid mechanics design but is quickly growing into other areas of physics and engineering. Being a fast growing research field, there is still no consensus on what functionality must be available in a decent topology optimization software. The ability to easily experiment with existing algorithms and easily define new problems to apply algorithms on is something that TopOpt.jl takes to a whole new level. Manually deriving gradients of long chained functions is still embarrassingly half of almost every important topology optimization paper in the field to this day! TopOpt.jl hopes to eliminate the need for this using automatic differentiation (Zygote.jl). Some custom adjoint rules are necessary to define for efficiency but automatic differentiation makes the software design and the API for defining custom adjoints much more pleasant than the status quo of re-inventing automatic differentiation for every new objective, constraint, sub-function, physical system, etc. The modular design of TopOpt.jl also allows a near complete segregation of the objective and constraint definitions from the mathematical optimization algorithm implementations which enables both to grow asynchronously appeasing to different audiences with different sets of expertise.