Optimising for Learning

We optimise for learning by not rushing into code, thinking more and planning well, such that we can uncover the simplest solution to a problem eliminating waste (you ain’t gonna need it YAGNI, keep it simple KIS, maximising the work not done)

We accept and welcome change, we embrace uncertainty and we estimate our work given what we knew at the time.

• We assume we are wrong
• We work iteratively
• We control the variables
• We proceed in small steps
• We gather feedback
• We adopt an experimental approach to progress
• We review and reflect (inspection) to find ways to improve our processes and ways of working (adaption)