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news.ycombinator.com• Jul 25, 2026• 1 min read

Tell HN: It's a LotI'm not sure if anyone needs to read this. I know I would, just to have some pause. A contemplative moment, if you will. Hence the post.--I need to know full-stack software engineering, preferably in full. That means going from hardware all the way up to whatever compiled language you choose. Web, app, desktop, all of it. Full-stack isn't just backend/front-end on web. I see a stack running way deeper and higher than that (this XKCD comes to mind [1]).But when I know all that, I also need to know how to do it securely right? So I need to know about that too.Then, I need to know about best practices such as CI/CD, hexagonal architecture, testing, whatever the developer culture came up with (e.g. the Smalltalk community and JS community do not agree on extending base classes). And many more things.I need to know math, not necessarily in full, but definitely at the level of that I can read ML papers and at least try to come up with potential novel thoughts.But there's also the topic of AI

news.ycombinator.com• Jul 25, 2026• 1 min read

Ask HN: Is neuromorphic computing going to replace traditional AI?I’ve recently learned about neuromorphic computing while thinking about the core inefficiencies of current deep learning.Today AI relies heavily on super-dense layers, continuous computation of all layers and neurons at all times, and global backpropagation to find optimal weight updates. But when you look at the human brain, none of that happens.The brain operates on principles that stand in contrast to modern LLMs:- Local Evolution: Neurons are largely independent, evolving based on their local neighborhood and simple feedback loops like neurotransmitters (e.g., dopamine) rather than a global error signal. - Extreme Sparsity: The system is massively sparse (neurons only evolve and get updated when they have been involved in a firing-chain). - Event-Driven Processing: Neurons are only firing when they get evaluated and are actually triggered by other spiking neurons.In contrast, current LLM‘s seem to me like they brute-force their way through problems by training all layers and neuron

github.com• Jul 25, 2026• 1 min read

Show HN: The TERSE state language and protocol# Hello World(valid terse; for Show HN)I'm terse(greetings)## Container"A container may have one text block, single or multi-line"Object(Semi-colon separated attributes; variables_like: 123; "Traditional unicode strings allowed here too.")Another object with a name(multiple objects under a container)## Further description of TERSE"""TERSE is a unified way to store state, with a defined way to query and mutate it that has been relentlessly refined for overall simplicity and token efficiency not just at rest, but in operation.We realized state access was a low-level, common pattern that keeps getting reinvented. It goes deeper than just AI memory. Consider that Anthropic memory and others are a bunch of markdown files and in some respects, they got it right... simpler is better.So REALLY the problem is settling on a format that is flexible to cover 95% of a domain. We can do so MUCH better than Markdown; TERSE is opinionated on that but it has very good reasons.By being a line-ordered an