Ashwin Sreenivas

speaker

310 appearances 1 recordings 1 series first heard Jul 2026 last heard 31 Jul

Ashwin Sreenivas’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

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The a16z Show · How Enterprise AI Really Gets Deployed · 31 Jul 2026 podcast

And we're like, wow, this is quite a lot of time.

How do we productize this?

And we built that into Duet.

And then the second part, which we called Duet Autopilot, was once we built Duet, people were using Duet to write things up.

And then we're like, oh, wow, there's still a lot of time that goes into iterating upon the agent.

Once it goes live, like reviewing conversations, figuring out how to improve it.

And we're like, great, let's productize that as Duet Autopilot.

In fact, AOPs themselves were a result of this exact scenario because before AOPs, you would have to write all these procedures in code.

And then we found that, oh, it's taking a lot of forward-deployed engineering work to write all these things in code.

Wow, wouldn't it be so much easier and efficient if we could productize it by writing it in plain text?

So the way we think about product improvements, forward-deployed engineering investment, everything is built around

What can we productize from forward-deployed work so that engineers and any kind of customer-facing resources on our team don't need to be kind of as heavily involved?

I think in the short term, actually, it is the ability to work with enterprise resources.

And what I mean by this is that the capability of models today is far greater than they are being used for within the enterprise.

by which you can't just take a model and say, I'm just going to give this model access to everything within the enterprise, and it'll just figure everything out.

That's practically not how these things work.

So to make models like this deployable within the enterprise, let's assume that every model is just perfect and makes no mistakes.

But to make something like this deployable within the enterprise, you need to say, okay, I need a way to be able to tell the model what it can and cannot do and make sure that it cannot do anything like catastrophically wrong.

Then I need a way to make sure that hundreds of people within the enterprise can collaborate to make sure that the agent is behaving as expected in the use cases in which they're experts.

Then I need a way to be able to test this model and make sure that it doesn't cross any regulatory lines that I have and test it, make sure it works well.

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