corvuszero รีทวีตแล้ว
corvuszero
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corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว

I'd like to welcome
"we fired half the company because we are just so gosh darn productive"
to the list of Weasel Statement All-Stars! 🏆
"my biggest weakness is that i work too hard"
"you deserve someone better"
"we're right sizing to invest in our people"
"i'm resigning to spend more time with my family"
"i just don't want to hold you back"
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@bradgessler Same code, different infra (app_a, app_b, etc as Rails env). You can deploy them and scale them separately. Config YMLs became huge but this should be more manageable nowadays using Docker + separate env files
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corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว
corvuszero รีทวีตแล้ว

Cindy is on the money, as always
The difference between those who do this and those who don't will be massive
What makes all of this tricky is that heavy + cutting-edge AI usage is easiest done on prototypes + unimportant stuff where it's ok to let it rip
Cindy Sridharan@copyconstruct
Unpopular opinion: Unless you’re just prototyping, you should aim to understand as close to 100% of production code generated by LLMs. Yes, all of it. Effective mental models are still important for humans to sustainably maintain and evolve a codebase via prompting alone.
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