Ryan Wexler
301 posts

Ryan Wexler
@RyanMWexler
Enterprise VC @Signalfire




Anyone who tries to build an AI agent for an enterprise quickly realizes that context is king, but is still extremely hard to get right. Internally at OpenAI, we've been trying to solve the context problem for one vertical: data warehouses. And it's starting to work quite well!





AI companies are spending billions hiring humans to produce training data. @haydenfield and I wrote about the explosion in new vendors and what it means for the future of AI development: theverge.com/cs/features/83…




Introducing Early Decision. For students who want to do a startup but also want to finish school first. Apply now, get funded the moment you're accepted, and do YC after you graduate. ycombinator.com/early-decision



@htaneja This is correct. Starting from $1M in revenue, 3/3/2/2/2 gets you to $72M in 5 years. Top quartile AI growers are going $1M to $100M in 3.5 years according to our data at @metrics_co. And that’s the top quartile, not the top decile.

Build two practical AI agents with Gemini, @CopilotKit, and @langchain: a Post Generator for social content and a Stack Analyzer for GitHub repos. Watch the tutorial to get started.

The enterprise AI switch has flipped! I loved jamming w/ @benscharfstein who is as sharp as they come on building complex AI for the enterprise. He runs product for one of the best kept secrets in SV - the @scale_AI Enterprise Applications Business - which has been a remarkable success over the past ~12 months. He shared some of his key learnings from the Scale Enterprise journey - notably how to sell+implement massive deals, what it’s like building forward deployed teams from scratch, and how delivering complex products & services is changing at the enterprise. I had a ton of fun and hope you enjoy this ep as much as I did.

I would pay $1,000 per month for voice AI that could let me get actual work done when I drive. Answer emails, schedule meetings and do other tasks









