Prukalpa Sankar
Co-founder and Co-CEO, Atlan. On 1 show, 1 appearance. The Shows tab opens the full record on each.
founderexecutive@prukalpa ↗LinkedIn ↗prukalpa.com ↗
Prukalpa Sankar is the co-founder and co-CEO of Atlan, an enterprise data control and context platform backed by investors including Insight Partners, Sequoia Capital, and Salesforce Ventures. She previously co-founded SocialCops, a data intelligence platform that powered India's National Data Platform and the United Nations' Sustainable Development Goals tracker.
1shows
1appearances
31statements
1resolved
0supported
1contradicted
0%fully supported
Everything Prukalpa Sankar said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Sankar: Selling to personal networks creates fake traction because people want to help
“I believe, most people love founding stories. Most people want to help. And most people will find a way if you speak with them and tell them this is the problem you're trying to solve, they'll find a way to help you. And that doesn't mean that they are going t…”
Sankar: AI-native companies must foundationally redesign hierarchies and processes
“You have to like leveling structures, like you have to foundationally reimagine how you operate as a company to be truly AI native or on the frontier versus I think The other option of it is you could say, hey, this is how I do things today. I'm gonna go slap …”
Sankar: Humans will always remain at the center of AI development
“One of our biggest realizations has been that humans will always be the center of AI. And how humans expand their creativity and their thinking through this is what is going to actually drive the next wave of this.”
Sankar: Settling for average PMF stalls startups at $5M to $7M
“You either never find product market fit or you find product market fit, but it's an average product market fit. And so you peter out at five million or seven million because you can't scale beyond that.”
Sankar: Frontier tech salespeople must be builders to hold customer credibility
“Well, I actually think they do. I think if you're trying to sell to the frontier what, how are you going to have a conversation with a customer who's talking to you about, you know, the difference between model gateways and three harnesses and memory systems, …”
Sankar: Software is fungible, but building products people use is hard
“Rebuilding technology is actually the easiest part of this problem, right? Like software itself is fungible. It has always been fungible. Like, I don't know why people now in AI suddenly are like, oh my God, it was always fungible. It was never that hard to Bu…”
Sankar: 50% of Atlan's platform users are AI agents
“Actually I, I'd say 50% of our end users are now agents and the rest 50% are humans.”
Sankar: Legacy data platforms and knowledge graphs are rebranding as context platforms
“So you'll see, you know, semantically or platforms are rebranding as context platforms and ontologies and knowledge graphs are rebranding as context platforms and data platforms are rebranding as context platforms. The model layers and the agent platforms are …”
Sankar: Enterprise context will be the defining moat and proprietary IP in AI
“It is going to be company IP. It is going to be the true differentiator or the moat in this new world.”
Sankar: Less than 10% of human job performance stems from cognitive intelligence
“And in fact, less than 10% of human job performance is explained through cognitive intelligence. Everything else is Context and how you learn on the job and how you act in real life.”
Sankar: Building AI agents is easy, but managing context is hard
“Investing in the
Orchestration layer or the model layer, like that's the easier problem to solve. Building an agent is easy. How do you actually make it accurate? How do you actually manage your context? That's going to be the hard problem.”
Sankar: Corporate AI discussions are theater because companies hide failed experiments
“And in fact, the core purpose is there's right now a lot of AI theater going on. So people only share the good things about AI. Nobody shares the experiments that went wrong.”
Sankar: Every institutional VC that backed Atlan helped close customer deals first
“Every round that we closed when we raised from an institution, the institution had helped us close some customers.”
Sankar: Modern leaders have no excuse not to build directly
“In today's world, you can't be a leader And not be pushing your team. I truly believe like you have to be in the details and the bar is so low. There's no excuse. It's so easy. Like there's no excuse to not set up and build yourself today.”
Sankar: India lacks the Bay Area's generational legacy of enterprise learning
“I think the challenge that India has is that India doesn't have the ecosystem that the Bay Area has, right? In the Bay Area, you had Adobe that passed to Google, who passed to Facebook, who passed to, you know, like, there's just this, like, legacy of learning…”
Sankar: Agentic AI use cases took off after reasoning models dropped
“All kinds of agentic use cases, which really started becoming a thing after the reasoning model dropped.”
Sankar: AI needs context to achieve agentic outcomes
“Every AI use case, if you want to go towards agentic outcomes is going to need context.”
Sankar: Product-market fit is about repeatability, not novelty
“Product market fit is about repeatability, not novelty.”
Sankar: Product-market fit is a search for truth, not traction
“Product market fit is a search for truths, not traction. And that's a really strange thing to internalize as an entrepreneur.”
Sankar: Horizontal platforms are loved by VCs but pose horrible GTM challenges
“We were a horizontal platform, which was great. You know, VCs love it. It's actually a horrible go-to-market problem because you know, where do you start? It's about repeatability, right?”
Sankar: Data engineers spend roughly 80% of time debugging
“In fact, like, 80% of time of data engineers were spent on debugging things.”
Sankar: Agents require three context layers: knowledge, expertise, and norms
“This is the context that any agent, actually human or AI agent needs to be able to solve this problem for the customer. Knowledge, expertise, and norms. So if you had to build this in a business, you need to be able to bring together first the map of the busin…”
One line per show, most statements first. The link opens Prukalpa's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 NEON SHOWLEDGER | Co-founder and Co-CEO, Atlan | 1 | 31 | 0% 0/1 | full record on the Neon Show → |