It is how we think, how we transform reality into a communication pattern -a “handshake” in a protocol – a common language! It is how we make decisions– by “learning” using probabilities of guesses gives successes from a model. The future has already arrived. From deep learning models to autonomous systems. Despite advances and new findings, the reality in industries still seems to be stuck. It is about convincing people, a lot of people – to form strong communities. These communities can have the strength to adapt, improve, secure, speed up – and make our tools, languages, methods and systems work faster and better. There are still no standards for AI models – Data is everywhere – and can be corrupt, transformed and lost. IoT combines all aspects – and we must be much better in cooperation for common success. Most software systems created are filled with bugs and despite this, still fulfills a purpose. Going autonomous creates new hard requirements on all aspects of analysis and creation of software and systems development, testing, validation and modelling. It is easy to forget all the non-functional requirement, or simply define your constraints into your model. It is the analysis – still in our mind – and slowly transforming into the computers reinforcement that currently is the key to the “right” model. Change is the only one thing that is for certain. In this talk I will highlight some experiences gained, impacting the quality of the futures systems from a more industrial perspective. What we gain, what we miss and what my “model” of success can look like in information overflow society.