“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

AI slop isn't just tacky and uninspired. It can get you sued. Generating fake AI faces that resemble real people, or using someone's likeness without permission, is creating new legal and reputational risks for brands. So we built @mirrormirror_ai as part of a16z @speedrun, a marketplace where brands can digitally book real models and creators to generate AI content using their likeness, with their permission. Brands browse and book identity-verified talent, agree on usage rights, and generate content within those terms. Every approved image comes with a signed license and embedded provenance. We're seeing brands produce lookbooks and campaign visuals up to 10x faster, with up to 90% cost savings. Meanwhile, models and creators can earn additional income from their digital likeness without having to show up for another shoot. Everyone is racing to make AI generation faster, cheaper, and more realistic. But there's still a huge missing piece: how do you license the rights to the people appearing in AI-generated content at scale? That's why I'm excited about what we're building. Not just another AI generator, but the licensing and rights infrastructure for AI-generated content.

I have a lot of thoughts on the whole “it’s impossible to find someone technical who’s also good at creating content, has taste, and deeply understands the ai ecosystem (twitter)” In no particular order 1. I have seen many companies hire for this role too early. When I interviewed for this vague new media/ devrel/ DevX world before joining Cerebras, many very cool companies reached out but they had no clear product to market and no clear audience. What ends up happening is that there is no clear need or scope and this person is dumped to do everything because they lowkey can do everything. (Be warned) 2. Many of the best folks at this role did not start as GTM folks. The most common profile are folks who are engineers first, generally have CS degrees (although many are now self taught) and naturally found themselves really excited to be educators as well. Key word = educators. I had a CS degree from MIT, decided very early I did not want to be a software engineer because it was too monkey mill, and carved out a hybrid role for myself. 3. When thinking about who is exceptional at this role, it’s important to distinguish the person from the company. For example, if someone is at a top lab, how much of the viewership, followers, etc are from them or just natural company groupies. (This is not to say folks at oai, ant, etc are not extremely talented). 4. So! Now everyone thinks they can now be a creator because how good AI is. One of the main differentiators for engaging content is having a literal human face in your content versus obscene amounts of screen recordings and graphic animations. Thus everyone is trying to hire a face of a company and needs to hire faces of a company. 5. This is just a thought but there are very clearly AI companies built around their founder where the founder is the face and everyone at the company feels like it’s their job to just make the founder more famous. I will not name names. I appreciate smaller companies like @browserbase who seem to amplify the many voices in the company. 6. There are still a ridiculous amount of companies who do not realize the value of investing heavily in these types of folks. Perhaps they are scarred by the lack of impact of enterprise/ old school marketing. But these AI companies, when not doing well, react by firing and downsizing these technical GTM teams (wrong move buddy), you never hear about them again, and they spiral into oblivion. Don’t do this. 7. There are two types of companies who “get it”. The companies who just do, and the companies who have been burned by 5+ years of failing to get the company message out and are finally like oh shit. We need to hire these types of folks and do this type of thing.

Exa just passed $100m in annualized revenue. We've grown almost exactly 10x per year for 3 years. We now handle 2 billion requests a month from 200k+ teams. And it’s still so early: We predict agents will search 1000x more than humans by 2030. Agents don't search like humans. They write long, complex queries and want all the world's data, not just the web. We've spent 5 years building a search engine designed for them. We now serve personal agents, AI labs, coding agents, GTM agents, really any agent. Exa gives these agents access to 100s of billions of web documents and tons of proprietary data. Our customers are increasingly noticing that information is the bottleneck to agent performance. While the world seems close to perfect intelligence with models like Fable and Astra, we are very far from perfect information. To our small but legendary team, thank you for getting us here, from engineering to research to GTM to ops. To our customers, it is an honor to serve you. We have some exciting releases coming soon and can't wait to share them 🫡

$52M seed round. 15M+ users. But this is what we're most proud of yet. Introducing Drama 3: the most emotive and controllable TTS model in the world And yes, it's open-weight. You can now control how even a single word should sound, change its tone, and shift your voice mid-sentence. Uncle Roger was impressed too. Try it here: Comment “DRAMA” within the next 48 hours for 1 month free. If you're an enterprise your first month is on us:

Introducing SubQ Snap, the first long-context decision model for real enterprise work. Snap is the only decision model or LLM where compute per token stays constant as context grows. • 384K tokens of multimodal context, 12x larger than Jev. • 61.7 on Decision Index v0.2.1 vs Jev’s 57.9, outperforming on 13 of 16 enterprise benchmarks. •Processes 100K tokens and returns a decision in under one second. •$0.05/MM input tokens. Output is free. Available today to anyone. The first 10,000 sign-ups get 100M free input tokens. We’ll likely hit capacity fast and will add users as we add compute. Compute offers welcome 🙂. Latency will be variable as we tune the platform to this new model and category of users. Model speeds are 80ms for minimal context, 250ms for 32k, 660ms for 100k, and 2.5 seconds for 384k. Visit:

“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

WTF is a SOTA Wife? SOTA Wives is a podcast exploring the unfiltered side of Silicon Valley. We built it as an antidote to the performative polish of tech Twitter. Brought to you by @MilksandMatcha x @vivianmshen. Episode 1 goes live on Monday, 12th October at 9 AM PT on everywhere you get your podcasts 💙

“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