The hottest Systems Engineering Substack posts right now

And their main takeaways
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Personalization at Bluesky

Recommender systems • 76 implied HN points • 23 Feb 26
đź•ą Technology Systems Engineering
  1. Bluesky builds Discover personalization from fixed post embeddings (BLIP2) plus broad topic labels and finer HDBSCAN clusters to track user interests, after an initial two‑tower retrieval approach didn’t work out.
  2. PinnerSage captures diverse short‑ and long‑term interests by clustering a user’s recent interactions into many medoids, scoring each cluster with a time‑decay importance, and using those medoids as weighted seeds for ANN candidate retrieval.
  3. Multiple per‑user medoids ease retrieval but complicate ranking, so the plan is to use PinnerSage for candidate generation and then adopt a transformer (PinnerFormer) to create a single user embedding for efficient, accurate ranking.

The Sequence AI of the Week #813: Deep Diving Into the Amazing GLM-5

TheSequence • 63 implied HN points • 25 Feb 26
đź•ą Technology Systems Engineering
  1. AI is shifting from manual 'vibe coding' to agentic engineering, where models autonomously plan, navigate large codebases, run tests, and iteratively fix bugs over long time horizons.
  2. GLM-5 is an impressive open-source model that scales a mixture-of-experts architecture to 744 billion parameters and showcases strong systems engineering to handle that scale.
  3. Enabling agentic behavior needs rethought reasoning, support for huge context windows, and robust reinforcement-learning alignment, and GLM-5 tackles these core bottlenecks.

Launching Live Courses on Systems Programming

Confessions of a Code Addict • 1058 implied HN points • 25 Jan 25
đź•ą Technology Systems Engineering
  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.

Building reliability from unreliable parts

Sunday Letters • 59 implied HN points • 12 May 24
đź•ą Technology 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.

Object-Oriented Brain Rot

Burning the Midnight Coffee • 96 implied HN points • 31 Jan 25
đź•ą Technology Systems Engineering
  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.
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How did places like Bell Labs know how to ask the right questions?

FreakTakes • 30 implied HN points • 20 Apr 23
đź•ą Technology Systems Engineering
  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.

16th Minute Newsletter 1.0.0

realkinetic • 0 implied HN points • 24 Jun 24
đź•ą Technology Systems Engineering
  1. 16th Minute newsletter covers a range of tech topics from compound AI systems to data structures.
  2. AI development is shifting towards compound AI systems where operations and systems thinkers play vital roles.
  3. Multi-tenancy in Kubernetes is an important area to explore for those working on enterprise software.