First, we need the problem, not the solution.
Problems must be understood before solutions to avoid unnecessary complexity and find the optimal solution.
Evals: Unit tests for AI applications
Since modern AI is generally non-deterministic, we need an alternative to unit tests. Eval is an excellent complement to these.
What is semantic versioning and does it also work for systems?
Semantic versioning has made component-based software development possible. Perhaps in systems engineering too?
Develop products faster with Behavior Driven Development (BDD)
Behavior Driven Development (BDD) comes from software development, but can also be used in systems engineering.
Agile Product Operating Model: The path to agile product development
Agile Product Operating Model is an agile framework for product development. It extends agile principles for complex products.
SysML: Avoid spaghetti models with the right package structure
It is amazing how quickly the number of elements in a system model grows. It is therefore essential to structure them correctly from the outset. Otherwise we quickly end up with "spaghetti models". This refers to models that look like a ball of spaghetti and are therefore difficult to understand. But almost all modeling languages, including SysML, give us...
System context: meaning, modeling and practical applications
Every development project has a system context. We should record this explicitly, with or without modeling.
The 2 biggest pitfalls when assigning IDs
IDs, or identifiers, are everywhere. In systems engineering, we work with IDs that uniquely identify requirements. In PLM, we have part numbers. But we also deal with IDs outside our area of expertise: Websites have URLs, or now URIs (the I stands for "identifier"). Books have an ISDN. And places have addresses. Identifiers...
Are there alternatives to the "Scientific Method"?
The "scientific method" has been established in research and development for hundreds of years. This refers to a systematic procedure consisting of a few steps that leads to reproducible results. The scientific method is so simple that even children can apply it. It is regularly used not only in research, but also in industrial development.
Collect AI data correctly in 6 steps
By now, word has gotten around that training data plays a central role for AI models. But how do we get good AI data? And since everyone is currently talking about "Artificial General Intelligence", the question arises as to whether we still need training data at all. The short answer is: Of course! Read on for the long answer...
The reward function: the linchpin of AI systems
When we develop systems for people, we have to make important decisions: Who are the users? What is important to the users? What is valuable to them? What problem will the system solve for these users, and how do we solve it? How do we know if we are ready? We need to answer all these questions, whether...
Tradespace exploration: making well-founded decisions
The term Tradespace Exploration (TSE) originates from the defense sector. TSE provides decision makers with an understanding of capabilities, gaps and potential trade-offs in order to find a good compromise for the competing objectives. Tradespace exploration is also an interesting approach for systems engineering to make informed decisions regarding solution approach, architecture and design.
