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scrubbles ,
@scrubbles@poptalk.scrubbles.tech avatar

Perfect! We’ll just write out the definition of the product completely in Jira, in a specific way, so the application can understand it - tweak until it’s perfect, write unit tests around our Jira to make sure those all work - maybe we write a structured way to describe each item aaand we’ve reinvented programming.

I see where you’re going, but I’ve worked with AI models for the last year in depth, and there’s some really cool stuff they can do. However, truly learning about them means learning their hard pitfalls, and LLMs as written would not be able to build an entire application. They can help speed up parts of it, but the more context means more VRAM exponentially, and eventually larger models, and that’s just to get code spit out. Not to mention there is nuance in English that’s hard to express, that requirements are never perfect, that LLMs can iterate for very long before they run out of VRAM, that they can’t do devops or hook into running apps - the list goes on.

AI has been overhyped by business because they’re frothing at the mouth to automate everyone away - which is too bad because what it does do well it does great at - with limitations. This is my… 3rd or 4th cycle where business has assumed they can automate away engineers, and each time it just ends up generating new problems that need to be solved. Our jobs will evolve, sure, but we’re not going away.

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