Ask anyone who’s ever begun a term paper the night before it’s due: there are stark tradeoffs between research time and research quality. This is especially true of primary user research, one of the fundamental ways large enterprises can ensure their products resonate with customers. Historically, this has required a choice between user interviews, which are high-fidelity but slow, manual, and expensive, and surveys, which are scalable, cheaper, and faster, but often result in unrefined, low-signal data. Although there have been some strong companies on the survey side, e.g. Qualtrics and Medallia, this uneasy compromise has always persisted—until now.
We were thrilled to feature Charles Srisuwananukorn from Together AI at January’s Chat8VC. Charles is the Founding Vice President of Engineering at Together AI, where he leads the company’s work on AI infrastructure and clusters. Previously, he was Head of Applied Machine Learning at Snorkel AI and held engineering roles at Apple. He studied Computer Science at Stanford and has helped steer Together from an early contributor to open-source AI to a full-stack infra platform.
We were thrilled to feature Joe and Jonathan from Upwork at March's Chat8VC in San Francisco. We covered their journey from teams like Google Brain and Cruise, and their own startup, to leading AI efforts at Upwork—building Uma, a suite of specialized LLMs powering workflows for freelancers and clients across the platform.
Human-quality workflows need human-quality data, an axiom that has only grown truer in the AI-first enterprise. However, access to complete, high-signal data remains a limiting factor, given steep data provider fees, inflexible schemas, AI hallucinations, and scattered, inconsistent, and mutating sources. Customers don’t need to be data scientists to recognize shovel-ready datasets, but if they need to be data scientists to generate them reliably, data will always be rate-limiting.
It’s widely agreed that GenAI will transform software development, and GenAI dev tools have emerged as cornerstones of 8VC’s portfolio and broader AI productivity thesis. Up to now, however, hard data on the scale and specifics of this shift have been missing from the equation. In competitive industries, the speed and efficiency gains promised by GenAI coding tools could well mean the difference between market leadership and obsolescence. Companies can’t afford to select the wrong tools and end up on the wrong side of the AI adoption curve.
For many consumers, the grocery aisle is the avatar of post-COVID inflation. Even as headline inflation has cooled (from 9.1% in June of 2022 to 2.8% in February of 2025), food prices remain stubbornly high, driving popular perceptions of gouging. $10 egg cartons, once confined to artisanal producers in Portland who know every hen by name, have hit big box stores. But grocery is a famously low-margin industry, and for CPG brands, the cost of doing business can be prohibitive.
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