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Neural Foundry's avatar

Solid resource compilation. The pattern-based approach is what actually transfers across different system design problems, way more effective than just memorizing solutions for each individual case. Zookeeper and distributed coordination patterns especially feel underexplained in most interview prep, so having that deep dive alongisde the practical problems should help bridge the gap. Curious if the course covers failure scenarios and recovery patterns for those 20 technologies, since that's where most interview convos go deeper.

Himanshu's avatar

U made Christmas 🎄 most happy for us..love u bhai

Ashish Pratap Singh's avatar

thank you so much 😊

Pradyumna's avatar

Great work Ashish.

chungsam Lee's avatar

Awesome work — this is exactly the kind of practical, structured resource that helps engineers bridge the gap between “knowing concepts” and actually passing real interviews.

On the AI side, I’ve been documenting a related system-design idea: a “control layer” (pre-conceptual alignment) that stabilizes reasoning at inference time — and it keeps showing up across multiple LLMs with evidence.

If you’re interested, here’s the write-up:

👉 https://open.substack.com/pub/northstarai/p/ai-spoke-of-a-meta-layer-in-its-own?utm_source=share&utm_medium=android&r=731thv

Sutee Dee's avatar

Looks amazing! I'm curious-how do you tie the paywall to substack subscriptions?

Ashish Pratap Singh's avatar

hey, I have setup a webhook in my stripe account. So, anytime someone new subscribes it calls my API endpoint and updates the database.