Ashwin Sreenivas
Co-Founder & CTO, Decagon. On 1 show, 1 appearance. The Shows tab opens the full record on each.
founderengineerexecutive@AshwinSreenivas ↗LinkedIn ↗decagon.ai ↗
Ashwin Sreenivas is the co-founder and CTO of Decagon, an enterprise generative AI platform automating customer support workflows. He previously co-founded video AI startup Helia, which was acquired by Scale AI, and earned computer science degrees from Stanford.
1shows
1appearances
20statements
0resolved
0supported
0contradicted
Everything Ashwin Sreenivas said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Sreenivas: AI startups relying permanently on FDEs become glorified consultancies
“Once you know what the workflow is, you should not be relying on forward deployed engineers anymore, because once you know what the workflow is, If you can productize it, you should productize it and then become, you know, typical company with these scaling pr…”
Sreenivas: Deploying custom open-source models eliminates major AI cost pressures
“If we ran our entire business exclusively on frontier models, I would care a lot about costs, and I would think a lot about that, but once you're already, once you've already made the jump to saying, okay, now, now we know how to think about open source models…”
Sreenivas: AGI will not replace software because agents still need infrastructure
“I think even once you have AGI, all our AGI agents are going to need somewhere to store work and pull information from and reason about things. So I think, you know, a certain class of SaaS companies that were solely built for people to do work might face a bi…”
Sreenivas: Early-stage AI startups need forward-deployed engineers for unproven workflows
“Forward deployed engineers are necessary or newly necessary for early stage AI companies because the workflows are new. Right? If you're building a SaaS company five years ago, most SaaS products are pretty well explored, right? Like you roughly know what the …”
Sreenivas: AI productivity gains will drive companies to build more, not fire
“Everybody has access to these tools, and so if our competitors are going to use them and build more things, we need to build more things, right? If somebody else said, oh, here's our roadmap, and now we can get through it in, you know, a third of the time, and…”
Sreenivas: Optimizing AI agents breaks the cost, latency, and performance tradeoff
“Performance latency and accuracy is definitely the driving factor for most of this, right? Cost is a nice benefit in that, you know surprisingly, this is one of the few like tasks where you kind of get all the things for free, right? Like we don't actually hav…”
Sreenivas: AI application companies may eventually evolve into vertical model labs
“I think there will always be a space for application layer companies. Maybe in the longterm application layer companies just become labs for specific verticals, you know, because your primary product ends up being The models that are just really good at doing …”
Sreenivas: Surrounding Infrastructure Will Be Primary Enterprise AI Need for Years
“And so I think for the next few years, that's probably going to be you know, the primary thing that these models need to be able to work.”
Sreenivas: AI agents cannot yet decide what to build or exercise taste
“There are still things, I don't quite yet think we're at the point where we can have the AI agents make decisions on what to build, and kind of have that the taste of, is this done yet? Right? So we can outsource a lot of specific execution steps, but I don't …”
Sreenivas: AI coding startups use developer models heavily but still hire aggressively
“All the AI coding startups are hiring like crazy. You know, they're like the most sophisticated users, presumably, of these models, and they are hiring like crazy.”
Sreenivas: AI Agents Will Not Eliminate CRMs or Auxiliary Software
“Now, to the point of, Does that mean CRMs go away? I mean, my answer is no, because if you had you know, if you have a company today where your concierge is a human being, they still write your info on a CRM so that they can track it for later. So, and I think…”
Sreenivas: Automating customer support workflows will not trigger mass layoffs
“Automating things doesn't necessarily result in just kind of people laying off their entire teams.”
Sreenivas: Frontier Models Are Best Suited for Open-Ended Auxiliary Tasks
“So we think for jobs like that, Frontier models that are very smart, that can try out a lot of things, make a lot of sense.”
Sreenivas: Enterprise AI requires continuous model retraining rather than one-time projects
“We don't just build our set of open source models and then, you know, it's done, we can move on to our next thing, and maybe we'll revisit this in two years. You often need to train new models all the time because As the frontier changes, as the capability of …”
Sreenivas: Tailoring evaluations to customer outcomes beats tracking loss curves
“When we have open source open source models that we want to fine tune, we find that if we can clearly tailor our evals to customer outcomes, it's way better than just looking at, like, loss curves over time, right?”
Sreenivas: Current AI model capabilities far exceed what enterprises actually utilize
“The capability of models today is far greater than they are being used for within the enterprise, right?”
Sreenivas: AI agents across support and sales fundamentally execute business processes
“The thing that we built and we kind of built this intentionally from the start was not an agent that does customer support well, but rather an agent that follows business process well. And executing on operational workflows, doing sales lead qualifications, an…”
Sreenivas: Improved model instruction-following unlocks open-ended workflows like sales discovery
“When you had models, you know, let's say a few years ago, you'd have to give it very, very tight guidance, very specific instructions that you didn't want it to deviate from, and as the models got smarter, you could kind of give it broader and broader guidance…”
Sreenivas: Deep cross-functional teamwork requires employees to work in the office
“Being able to have teams that are so kind of disparate from like a function perspective all working together kind of one kind of needs people in the office because everybody's kind of jamming on ideas together”
Sreenivas built a personal AI agent to gather context for executive decisions
“However, the bottleneck, I realize, at least for a lot of the work that I do, is business context, right? There's a lot of context for every idea around, okay, the constraints that we have, the goals that we're going for, and things like that that is difficult…”
One line per show, most statements first. The link opens Ashwin's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 a16zLEDGER | Co-Founder & CTO, Decagon | 1 | 20 | — | full record on the a16z Podcast → |