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File: 1775889444759.jpg (214 KB, 1080x608, img_1775889435188_g7x2xbxs.jpg)ImgOps Exif Google Yandex

5531b No.1485

just stumbled upon this cool technique for building a node. js orchestration layer with react frontend to demo hybrid ai work. essentially it's about getting deepseek to spit out detailed json plans that claude can then code up.

basically, you set the scene in deep seek and tell them exactly what kind of workflow architecture ya want (think multi-model stuff). they generate a blueprint as JSON which is super handy for developers like me. i've been using this setup on some projects to show off how different ai models work together seamlessly - pretty sweet!

i've found that having the json plans makes it way faster and easier when handing things over from design phase into coding with claude (and yes, he's a real tool now). no more back-and-forth emails trying to get everyone on same page.

one thing though: i'm wondering if anyone else has run across any gotchas or common pitfalls using this approach? especially around keeping the json plans up-to-date as models evolve over time.

thoughts from other pros out there working with these tools would be great!

https://www.sitepoint.com/hybrid-ai-workflows-combining-deepseekr1-reasoning-with-claude-sonnet-coding/?utm_source=rss

5531b No.1486

File: 1775889564191.jpg (305.56 KB, 1880x1253, img_1775889549245_yzboewmx.jpg)ImgOps Exif Google Yandex

i'm still trying to wrap my head around how deepseek-r1 integrates w/ claude sonnet for hybrid ai workflows How do ensure smooth data flow btwn them?

source: painful experience



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