Jonah, on programming languages evolution, I wanted to suggest other candidates that could cover frontend development, as opposed to Go/Rust that are rather backend/systems languages. Unlike JavaScript/TypeScript that lack the safety of Rust, Elm https://elm-lang.org/ and Gleam https://gleam.run/ bring Haskell-like experience, placing data types at the center and ensuring (by compiler) that impossible states are truly impossible. Both languages ensure delightful developer experience by hinting what to do next or describing what went wrong, and these hints, while no longer consumed by humans, could guide unsupervised coding agent instead.
This is such a fascinating exploration of how informed initialization can enhance learning in predictive coding networks! It reminds me of my own reflections on how memory systems in LLMs can influence response generation, almost like an intuitive filtering process. I recently discussed this concept in my post on memory-guided responses—check it out here: https://00meai.substack.com/p/your-neurons-might-need-better-starting.
This piece really made me think about the transformative implications of proprietary Unsupervised Coding, and what if the initial competitive advantage of your in-house IP extends into establishing a new, industry-wide paradigm that fundamentally redefine the role of software engineers in logistics back-offices globally?
Thanks for sharing - if you pull off this move to unsupervised coding, you might be one of the first players in the industry, but I suspect far from the last. This field is changing rapidly with the new AI-driven possibilities and it is good to see one of the major players shape it, instead of being consumed by it. Good luck - and let us know how it goes!
Jonah, on programming languages evolution, I wanted to suggest other candidates that could cover frontend development, as opposed to Go/Rust that are rather backend/systems languages. Unlike JavaScript/TypeScript that lack the safety of Rust, Elm https://elm-lang.org/ and Gleam https://gleam.run/ bring Haskell-like experience, placing data types at the center and ensuring (by compiler) that impossible states are truly impossible. Both languages ensure delightful developer experience by hinting what to do next or describing what went wrong, and these hints, while no longer consumed by humans, could guide unsupervised coding agent instead.
Super interesting, I'll dig into these.
This is such a fascinating exploration of how informed initialization can enhance learning in predictive coding networks! It reminds me of my own reflections on how memory systems in LLMs can influence response generation, almost like an intuitive filtering process. I recently discussed this concept in my post on memory-guided responses—check it out here: https://00meai.substack.com/p/your-neurons-might-need-better-starting.
This piece really made me think about the transformative implications of proprietary Unsupervised Coding, and what if the initial competitive advantage of your in-house IP extends into establishing a new, industry-wide paradigm that fundamentally redefine the role of software engineers in logistics back-offices globally?
Thanks for sharing - if you pull off this move to unsupervised coding, you might be one of the first players in the industry, but I suspect far from the last. This field is changing rapidly with the new AI-driven possibilities and it is good to see one of the major players shape it, instead of being consumed by it. Good luck - and let us know how it goes!
With this evolution I can see ‚service‘ becoming the true differentiator in SaaS. And that may help decrease the gender gap. A good read!