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Comments (41)

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  armchairhacker
  The gist ("product becomes a black box") applies to any abstraction. It could apply to high-level languages (including so-called "low-level" languages like C), and few people criticize those.But LLMs are particularly insidious because they're a particularly leaky abstraction. If you ask an LLM to implement something:- First, there's only a chance it will output something that works at all- Then, it may fail on edge-cases- Then, unless it's very trivial, the code will be spaghetti, so neither you nor the LLM can extend itVs a language like C, where the original source is indecipherable from the assembly but the assembly is almost certainly correct. When GCC or clang does fail, only an expert can figure out why, but it happens rarely enough that there's always an expert available to look at it.Even if LLMs get better, English itself is a bad programming language, because it's imprecise and not modular. Tasks like "style a website exactly how I want" or "implement this complex algorithm" you can't describe without being extremely verbose and inventing jargon (or being extremely more verbose), at which point you'd spend less effort and write less using a real programming language.If people end up producing all code (or art) with AI, it won't be through prompts, but fancy (perhaps project-specific) GUIs if not brain interfaces.
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  furyofantares
  For those unaware, the title is a reference to a Little Britain skithttps://www.youtube.com/watch?v=sX6hMhL1YsQ&themeRefresh=1
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  bushido
  I love the framing here.However, I think what a lot of people don't realize is the reason a lot of executives and business users are excited about AI and don't mind developers getting replaced is because product is already a black box.
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  thesimon
  > This is a great insight. For software engineers coding is the way to fully grasp the business context.> By programming, they learn how the system fits together, where the limits are, and what is possible. From there they can discover new possibilities, but also assess whether new ideas are feasible.Maybe I have a different understanding of "business context", but I would argue the opposite. AI tools allow me to spend much more time on the business impact of features, think of edge cases, talk with stakeholders, talk with the project/product owners. Often there are features that stakeholders dismiss that seemed complex and difficult in the past, but are much easier now with faster coding.Code was almost never the limiting factor before. It's the business that is the limit.
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  SamLeBarbare
  I really like the framing here (via Richard Sennett / Roland van der Vorst): craft is a relationship with the material. In software, that “material consciousness” is built by touching the system—writing code, feeling the resistance of constraints, refactoring, modeling the domain until it clicks.If we outsource the whole “hands that think” loop to agents, we may ship faster… but we also risk losing the embodied understanding that lets us explain why something is hard, where the edges are, and how to invent a better architecture instead of accepting “computer says no.”I hope we keep making room for “luxury software”: not in price, but in care—the Swiss-watch mentality. Clean mechanisms, legible invariants, debuggable behavior, and the joy of building something you can trust and maintain for years. Hacker News needs more of that energy.
• doug_durham
  The quote at the center of this posting uses poetic language like "dialogue" to make a certain class of work seem virtuous. I find it very difficult to take this kind of framing seriously. What are the data to back this up? We are at the phase of LLM use where the data on productivity gains and their impact hasn't arrived yet. Postings like this fill the vacuum with fuzzy language.
• stewrat
  After watching speedrun videos on youtube, my hunch is that there will always be a countervailing forces to the degradation of our ability to write code. There are some unborn wizards who can't help but bring it all the way back to writing assembly, just because it's hard. And they will be rewarded for it
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  amelius
  If your computer says No just ditch it and buy a non-Apple computer.
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  ktpsns
  To be honest, the same applies when a developer gets promoted to team lead. I made this experience on my own that I no longer got in touch with the code written. Reasons are slightly different (for me it was a lack of time and documentation)
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  googamooga
  If you are a painter, you don't need to know chemical formulas for the pigments you're using to have a direct touch to your creation.For me, that material conciousness in computers was always in grasping the way system works holistically. To feel the system. To treat it as almost a living organism.
• kitd
  > feeling resistanceIn a software context, I wonder what the impact of the language used is on the sense of "resistance"?
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  iSnow
  To an extend, AI can help with explaining what the code does. So, computer says why it says "no".
• anon
  undefined
• luxuryballs
  this isn’t the right way to use ai to write code at work, it shouldn’t become a black box, you should make it iterative and be precise about architecture, guide the ai carefully to maintain the code in a state that a human can instantly drop in on if needed, use ai as a keyboard extension not a blindfold