Nicolay Gerold

"I would go as far as to say that 90% of writing clean code is “just” naming things correctly." Good name doesn’t misdirect, doesn’t omit, and doesn’t assume. A good name should give you a good idea about what the variable contains or function does. A good name will tell you all there is to know or will tell you enough to know where to look next. It will not let you guess, or wonder. It will not misguide you. A good name is obvious, and expected. It is consistent. Not overly creative. It will not assume context or knowledge that the reader is not likely to have. Write a comment above the function/variable where you describe what it is, in human language, as if you were describing it to your colleague. It might be one sentence or multiple sentences. This is the essence of what your function/variable does, what it is. Now, you take the role of the sculptor, and you chisel at and shape that description of your function/variable until you get a name, by taking pieces of it away. You stop when you feel that one more hit of your imagined chisel at it would take too much away. Is your name still too complex/confusing? If that is so, that means that the code behind is too complex, and should be reorganized! Go refactor it. Ok, all done → you have a nice name! That comment above the function/variable? Remove everything from it that is now captured in the code (name + arguments + type signature). If you can remove the whole comment, great. Sometimes you can’t, because some stuff can’t be captured in the code (e.g. certain assumptions, explanations, examples, …), and that is also okay. But don’t repeat in the comment what you can say in the code instead. Comments are a necessary evil and are here to capture knowledge that you can’t capture in your names and/or types.

We call it WINS Work: the places where tasks, functions, possibly your entire company or industry are dependent on the manipulation and interpretation of Words, Images, Numbers, and Sounds (WINS). Heart surgeons and chefs are knowledge workers but not WINS workers. Software programmers, accountants, and marketing professionals are WINS workers. GenAI has the potential to be power tools for WINS work. Every WINS task, subprocess, and end-to-end process within your enterprise (and in many cases the entire enterprise) should be evaluated for potential leverage with GenAI. Plotting your company on a 2×2 matrix, ask yourself where it falls. The top-level categorization can be accomplished by looking at the cost base of the firm overall and then by function, and estimating the percentage of work that is WINS work. For example, software development, customer service, marketing, and R&D are just four areas with high levels of WINS work.

Producing: One part of your system (a producer) wants to send a message, which could be anything like an order from a customer, a sensor reading, a log message, etc. Consuming: Another part of your system (a consumer) wants to receive and process that message. FastStream acts as a postman, ensuring the message is delivered accurately and efficiently from producer to consumer. Applications: E-commerce Platform: When a customer places an order, a message regarding that order needs to be communicated to various services like Order Management, Inventory Management, Payment Gateway, and more. FastStream will handle these messages, validate the order data, and ensure that all relevant microservices are informed in real-time, ensuring a smooth ordering process. IoT Sensor Network: Consider a network of IoT devices sending sensor readings (temperature, humidity, etc.) to a central server. FastStream ensures that all these readings are valid, documented, and are efficiently communicated to the central server for further analysis or action. Financial Transactions: In a financial application, transactions and trading data can be passed through FastStream to validate transactions, communicate them to various analytic and logging microservices, and even trigger alerts or actions based on the data.