Post #1996020

Reminder that I'm ready to spend 4h (!) of my time working on whatever thing you throw at me, with my current heavily #llm supported workflow. I'm doing this in the hope of showing that they are very capable development tools, and worth being considered seriously, hopefully for building more local / self-hosted / community-oriented software, or at least to show that they have a serious impact on what the definition of a software engineer is, in our current work practices, and that the labor implications go beyond "CEO read fancy AI article in HBR and thinks they can lay off half of their engineering dept". Also, that openweights model are very capable, and anthropic and openai going down in flames doesn't mean that the engineering landscape will revert back to pre-llm practices (that could have happened if we had stopped 2-3 years ago, but that window has passed). I've been writing software for 30 years now, 25 professionally, I averaged 4-5k commits a year before #LLMs on github, I'm not entirely new to software engineering. Anyway, only constraint is that I get to use go + javascript (i.e., my standard stack) or potentially embedded c++ (but i'm rusty), except if you want to throw "learn a programming language / technology stack" problem at me. Feel free to try to conjure a gotcha if that amuses you, but I will give it a good faith attempt. FWIW, I wrote this over 3 years ago. They held up reasonably well... - https://the.scapegoat.dev/llms-will-fundamentally-change-software-engineering/ - https://the.scapegoat.dev/llms-a-paradigm-shift-for-the-pragmatic-programmer/ If you want some insight into why I think putting human communication at the center of any LLM workflow: https://www.youtube.com/watch?v=zwItokY087U And some AST/DSL programming language nerdery: https://www.youtube.com/watch?v=4GSShoBLZF0 #genai #chatgpt #claude #llms #llm