The hottest Systems Engineering Substack posts right now

And their main takeaways
Category
Top Technology Topics

Launching Live Courses on Systems Programming

Confessions of a Code Addict • 1058 implied HN points • 25 Jan 25
🕹 Technology Software Development Systems Engineering Education Programming Course design
  1. There is a growing gap between complex systems in software and the engineers who understand them. More engineers need to learn how these systems work in detail.
  2. The new live courses will help those interested in systems engineering to gain practical skills. They'll start with basics like programming in X86 assembly and progress to more complex topics.
  3. Hands-on practice is key to learning in these courses. Along with guidance, you'll need to put in effort and time to really understand the concepts.

Object-Oriented Brain Rot

Burning the Midnight Coffee • 96 implied HN points • 31 Jan 25
🕹 Technology Software Development Object Oriented Programming Systems Engineering Software Design Computer Science
  1. When modeling objects like rectangles and squares, thinking too rigidly can lead to problems. Sometimes, it's simpler to just write a function to handle what you need rather than forcing everything into class hierarchies.
  2. Object-oriented programming can sometimes make things overly complicated. It's better to focus on solving the actual problem instead of worrying about fitting everything into a strict structure.
  3. Learning to think in terms of complex class hierarchies can actually harm your ability to solve problems. Simple, direct solutions are often more effective than trying to model everything in a complicated way.

Building reliability from unreliable parts

Sunday Letters • 59 implied HN points • 12 May 24
🕹 Technology AI Cloud Software Data science Systems Engineering
  1. Modern AI systems have a random element, making them sometimes unpredictable or unreliable. This means they can give different answers even to the same question, which is a challenge for creating consistent outputs.
  2. Just like the early cloud systems, we need to use smart software solutions to make our current AI technologies more reliable. Instead of relying solely on the AI itself, we should layer software to handle and fix errors.
  3. To build better AI systems, it’s important to explore structured approaches, like guided conversations or iterative processes. This way, we can combine the strengths of AI with reliable system design.

How did places like Bell Labs know how to ask the right questions?

FreakTakes • 30 implied HN points • 20 Apr 23
🕹 Technology Engineering Research Innovation Systems Engineering Telecommunications
  1. New science orgs should aim to combine the positive aspects of both applied and basic research.
  2. Applied and basic research distinctions are sometimes arbitrary, with some projects blurring the lines between the two.
  3. Institutions like Bell Labs successfully managed research by selecting profitable courses that satisfied both basic and applied research needs.

Primer on Machine Learning Interviews for Software Engineers

ExpandAI Newsletter • 0 implied HN points • 30 Jun 23
🕹 Technology Machine Learning Software Engineering Mathematics Neural Networks Systems Engineering
  1. Software engineers in the future will likely require strong machine learning backgrounds.
  2. Machine learning interviews for software engineers cover software engineering, mathematics, and machine learning topics.
  3. Preparing for machine learning interviews should focus on optimizing for both software and machine learning skills.
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