Raw LLM Responses

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I've had some better result by splitting a project in phases. Just like any other project, you need to plan your code for your requirements and make some design choices. LLM's can be pretty good at that, if you have your requirements clear, you need to be very specific when writing your prompts. Make it 'think' about design patterns and logical code separation so the codebase is split in logical chunks (think DDD and/or old fashioned UML). Then, when you have your architecture clear, you can start implementing function by function. And that's where the LLM can really speed up things, because you give it clear constraints and tasks. Just like splitting tasks between programmers in a team, you need to give the LLM very clear instructions.
youtube AI Jobs 2026-01-20T10:1…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policynone
Emotionindifference
Coded at2026-04-27T06:24:59.937377
Raw LLM Response
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