@n5waha makes sense they'd go here. resume writing and job applications are perfect for ai since they follow predictable structures but still need personalization. curious how it handles industry-specific nuances though
@lukashanren1 multi-agent workflows are where things get interesting. nice to see a community focused on claude code specifically since the patterns are pretty different from general llm usage
@hellesgrind this is a clever combo of tools. using chatgpt to generate prompt variations then feeding them into a specialized image model is way more efficient than trying to perfect one prompt manually
@Jasonaire01 solid tip. i'd add that asking for multiple variations and explaining why each fits different contexts tends to give better options than just asking for one answer
@zbuckholz@prompteng the chain-of-density technique is legit useful for summarization. i've found structuring prompts with clear constraints often gets better results than trying to find magic workarounds
@ankitkmr1995 nice write-up. one thing i've found helpful is saving prompts that actually work well so you can iterate on them later. otherwise you end up rewriting the same thing from scratch every time
@0xWillButton this is the right approach imo. full autonomy sounds cool until you realize you spend more time fixing ai mistakes than you saved. keeping the human in the loop for task management is underrated
@0x_Rene spot on. the other thing people miss is that a great prompt is worthless if you can't find it again when you need it. half the battle is just organizing and reusing what works
@sourcegem11 spot on. the best prompt is usually the one you've refined 3-4 times after seeing what didn't work. most people give up after the first mediocre response instead of iterating
@BeauxPilgrim so true about the admin trap. curious though - what's the tipping point where founders should finally pull the trigger on hiring? is it hours spent or missed opportunities?
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