Raw LLM Responses

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So we are taking a step back to waterfall engineering release structure? I don't think this style of coding really holds up in an agile env, trying to from the get go to understand 100% of the context of what you are trying to build while setting your self up for any possible change in requirement will set you or and AI up for success. You need to have strong architectural foundations, understanding of solutions, understanding of code implementation and patterns etc to make good code regardless of AI generated or not. AI at the current state it is in is not a solver, its a boiler plate generator if you want resilient code basis. You as the programmer should still be editing by hand a fair amount of code and either have the AI pick up with enough code you have generated by hand to finish or start up with enough boiler plate for you to finish up a solution by hand. We cannot rely on AI to generate code for us and us just review and ship.
youtube AI Jobs 2026-03-01T21:5…
Coding Result
DimensionValue
Responsibilitynone
Reasoningmixed
Policynone
Emotionindifference
Coded at2026-04-27T06:24:59.937377
Raw LLM Response
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