Honored to have witnessed this union.
Excited to hear more of @MilksandMatcha @vivianmshen on @SOTAwives!
“Do you think that getting married young has made you less ambitious?”
Welcome to the first episode of SOTA Wives with Sarah Chieng (Head of DevX at Cerebras, @MilksandMatcha) x Vivian Midha Shen (General Partner at Y Combinator, @vivianmshen).
In episode 1: finding your person before getting rich, turning down startup funding to finish MIT, what a YC partner sees in founders, and how a birthday post became “psychological violence.”
4:08 Finding your husband before the exit
8:48 Did we marry away our ambition?
18:04 The internet called Sarah's birthday “psychological violence”
20:47 Does your YC partner secretly think you’re doomed?
23:47 Building a startup with your ex-boyfriend
28:54 SF cat parties
Jeffrey Chen retweeted
I made Claude for Chrome up to 100% faster in a day with a simple concept.
Browser agents like Claude for Chrome are making way too many inference calls.
Most people use the same ~20 websites. The interaction patterns on those sites are learnable and reusable. So why hit the LLM every step?
I built a PoC where the LLM gets the task, picks the site, and pulls from a library of learned patterns for that site, like a cache. It plans what to do, then executes. No back-and-forth probing, no redundant inference calls to locate elements it found last week.
Results: up to 100% faster, ~25 fewer inference calls per task, half the cost, and sometimes more successful in actually getting the task done.
Jeffrey Chen retweeted
1/ The future of general-purpose robotics will be decided by one major question: which flavor of data scales reasoning? Every major lab represents a different bet.
Over the past 3 months, @adam_patni, @vriishin, and I read the core research papers, spoke with staff at the major labs, and mapped the talent pool. This has completely changed how we think about general-purpose robotics.
Our paper builds intuition, step-by step, across the 2025 frontier: from architectures → evals → data → industry dynamics. Each layer reveals a different bottleneck, but they all converge on one truth—data decides everything.
Our takeaways + process below👇
If you want access to our graph (sound on), comment or DM me
Jeffrey Chen retweeted
1/ I wrote this thesis a bit over a month ago and sent it to several TradFi money managers managing a total of hundreds of millions - it net 30% in one month.
The market is continuing to show that ETH is fundamentally mispriced in the crypto ecosystem (this is from someone who used to basically only own ETH).
Here's why the BTC/ETH spread trade is about to get much bigger (as much of CT knows) 🧵. Full 13 page pitch linked below.
Jeffrey Chen retweeted
Databricks' higher gross margin is primarily because compute/storage is billed through the cloud service provider instead of being passed through like with Snowflake. This is slightly different than on-prem/VPC type workloads.
Congrats to the homie @anishtxt and his cofounder for launching their LLM testing product!
Chatter (YC S23) makes LLM testing and iteration dead simple. Anyone from engineering to customer success can collaborate on LLM chains, test suites, versioning, and more. Think Postman, for LLMs.
ycombinator.com/launches/JDp…
Congrats on the launch, @anishtxt and @kasyapchakra!
