Emergent: How Six Months of Tinkering Led To A $100M ARR Company
Mukund Jha joins Y Combinator to explain how he built Emergent, an AI no-code software platform, to $100M ARR in 9 months after 6 months of tinkering post-Dunzo.
The gist
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Emergent outpaced rivals by building real backend infrastructure and end-to-end automation while competitors were focused on front-end demos.
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Jha's team used SWE-bench as a forcing function during YC, which led to key discoveries like parallel agents and memory systems.
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Jha says to build for where AI models will be in 6 months, not where they are today, even if investors reject the vision.
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Building for a global audience from day one takes the same effort as building locally but opens far larger markets, Emergent now has 8.5M users across 190 countries.
Mukund Jha uses it
"I picked this benchmark SWE-bench which was the hardest benchmark at that time and told them while I figure out what we're going to build let's just attack this benchmark. It took us 3 months to crack that benchmark became world number one on that benchmark."
▶ Play at 21:55What they recommend · 1 pick
SWE-bench
AI tools
"I picked this benchmark SWE-bench which was the hardest benchmark at that time and told them while I figure out what we're going to build let's just attack this benchmark. It to..."
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