Justin

if your product isn’t 90% inspired by online references you’re ngmi

taught our gtm intern how to vibe code

because guys like you respond to it 😘

@jessilychen ooh Milo’s X algorithm exposing him?!

@VivianCaiIAm @elsaprofitable @mc_chng

we’re finally hosting a founder dating show > studio grade production > starring a16z & yc founders if this sounds like something you’d want to be part of or help make happen, send me a message🫶 details in the comments soon

@VivianCaiIAm @elsaprofitable @SimonLivva

@SkarmyAI @jessilychen @UNC 🔥yo wth skarmy responded

@jessilychen @UNC Excited to see what you do! 🚀 🌖

@jessilychen @UNC Jessily what is your Beli recs looking like in Sf

@PavanKumarNY jokes

@PavanKumarNY also damn bro no tag ngmi

pov: your cofounders made it on Times of India on July 4th.

@PavanKumarNY dude we got on MSN

just came to BestBuy for some iPhone SEs. The worker was like, “are you with that ai startup dude that comes in every week for SEs” LOLL🔥🔥IYKYK

my startup fired half our devs today.. because of Fable 5.. Our codebase is designed FOR agents working in parallel. 8-repo codebase..

@iamlulu_zh @UseCorgi haiku ahh post

out: ABG in: ACG - asian cool girl @UseCorgi bathroom

@CeciliaCici13 what happened to all of those larp photos u took with me and @SimonLivva lol

Girls only be seen at gtm events

@AadiGujral @rohansuri_06 @TPapavramidis can i angel?

We discovered that 50% of AI inference costs are going down the drain. It might sound crazy, but it's true. Six months ago we set out on a mission to solve a single problem: “Why are LLMs so damn expensive?” We expected the answer to be obvious - bigger models, more users, more tokens. Instead, what we found was surprisingly mundane. Companies waste enormous amounts of money simply because every request is treated the same. So we built Phantm. Phantm is an API gateway that sits in front of your existing AI stack and dynamically optimizes every request. In our testing on real workloads, it consistently reduced inference costs by over 50% without sacrificing output quality. Every company with ambition will eventually build on AI. As that happens, AI won't just need models - it will need infrastructure: routing, observability, budgeting, analytics, governance, security, evaluation. It will need Phantm. The same way cloud computing evolved from "just servers" into an entire ecosystem, AI infrastructure will evolve into an entire operating layer. That's what we're building. Today, that starts with optimization. Tomorrow, it becomes the platform that helps enterprises use AI efficiently, safely, and intelligently at scale. We're incredibly grateful to @edwardlando, @JBoustou and @CKraycik from the @ParetoHoldings team, and everyone else who believed in us early. If your company is building with LLMs and your AI bill keeps growing, we'd love to talk.

Cybertruck FSD is like claude with dangerously skip permissions. revolutionary car

@saraknggg in my startup we scaled to 8 people in 2 weeks and if anyone gets behind, any of the other 7 people can update them updates and information spread like a virus in our company #antivaxx

@saraknggg gonna be contrarian here, i think the company should be the biggest possible team where everyone still sees the vision

when building a company from scratch, do you prefer keeping a lean team or divide and conquer - outsourcing for skills you don’t have? i feel like the larger the team is during early stage, context lag and stickiness between humans will fragment the speed at which one can build, scale, or master distribution.