Great Read!! As the cost of compute continues to drop and new technologies make it easy for competitors to copy software, traditional advantages like having a unique product or strong technical barriers are less effective. While having strong distribution and getting your product into the hands of customers through effective channels is more important than ever!
You're right that distribution has become king as compute drops and features get commoditized fast.
I've spent years in AI infra/sales ops at a Bay Area firm scaling data flywheels - I've seen "viral" startups hit $10M then flatline because product couldn't retain. The winners? They deliver consistent value beyond the hype.
Most AI-native plays won't rewrite SaaS overnight. Distribution matters hugely, but without durable product stickiness and economics, it's just noise. Props to the ones quietly compounding like Surge and Gamma. The rest? Often more story than substance.
Exceptional. We need more writing like this: clear case studies, well-structured, and, most importantly, sophisticated attention to trade-offs and contextual limitations.
In many cases you note that these decisions shape the org structure. Would love to see a deep-dive on on this: when are what roles being added so as to successfully maximize revenue per employee?
Great Read!! As the cost of compute continues to drop and new technologies make it easy for competitors to copy software, traditional advantages like having a unique product or strong technical barriers are less effective. While having strong distribution and getting your product into the hands of customers through effective channels is more important than ever!
You're right that distribution has become king as compute drops and features get commoditized fast.
I've spent years in AI infra/sales ops at a Bay Area firm scaling data flywheels - I've seen "viral" startups hit $10M then flatline because product couldn't retain. The winners? They deliver consistent value beyond the hype.
Most AI-native plays won't rewrite SaaS overnight. Distribution matters hugely, but without durable product stickiness and economics, it's just noise. Props to the ones quietly compounding like Surge and Gamma. The rest? Often more story than substance.
Exceptional. We need more writing like this: clear case studies, well-structured, and, most importantly, sophisticated attention to trade-offs and contextual limitations.
In many cases you note that these decisions shape the org structure. Would love to see a deep-dive on on this: when are what roles being added so as to successfully maximize revenue per employee?
Very insightful, @Bocar Dia!
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We just published our new walkthrough on RCA question.
https://www.crackpminterview.com/p/rca-questions-zepto-repeat-purchase-rate-dropped-by-15-percent
This is a gold mine of insight and experience. Thanks for sharing it.
Love this perspectifve!
Useful
I need read later feature in substack to remind to read shortlisted subs later.
I have been waiting for that feature also! Bookmark sort of works but not exactly a read-later
very interesting. I think only a few companies could have had this growth journey, but they are best practices to adopt!
Interesting read
Thanks. Incredible usefull
Great article - thank you
🙏
Super cool. Thanks for your work here. A great help :) Neil x
++ Good Post. Also, start here : 500+ LLM, AI Agents, RAG, ML System Design Case Studies, 300+ Implemented Projects, Research papers in detail
https://open.substack.com/pub/naina0405/p/most-important-llm-system-design-77e?r=14q3sp&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false
Lovable changed everything and gave hopes to so many startups in AI.
Thanks for sharing Bocar - great post - just subscribed and would mean the world if could read my work too ☺️🫶🙏
https://substack.com/@mikilundh/note/p-193152904?r=ad6no&utm_medium=ios&utm_source=notes-share-action