Arvind Jain

speaker

456 appearances 1 recordings 1 series first heard Jul 2026 last heard 11 Jul

Arvind Jain’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

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

Appearances

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch · 20VC: Why OpenAI and Anthropic Won't Win the App Layer | Why Teams Will Get Bigger Not Smaller in a World of AI | Why AI Removes Incumbents Advantage of Bundling | China vs America: Who Wins the AI War with Arvind Jain, Co-Founder @ Glean · 11 Jul 2026 podcast

We're probably more conservative than most other companies.

There was in fact a discussion inside the company that, well, now AI can write so much code and the real bottleneck has shifted from the person who writes the code to person who has to review.

And so there was a proposal to actually eliminate code reviews.

And then many companies are doing that.

It's like let AI write the code and directly get submitted into the repos.

Yeah, it's true.

But I think what it is doing right now is, we're still in the learning phase of using AI effectively, thinking about long-term ramifications of it.

Because when you write code, for example, with AI, you can write a million lines of code, but it becomes incredibly hard to actually maintain it and understand it and manage it over time.

Yeah, the only thing is that it's not that perfect right now.

I think right now we're willing to pay the cost of reviewing the code.

So we're still faster than before because the writing part is actually much faster now.

And the person who writes is the one who actually does the first review.

The first thing that we have to do is make sure that you are able to bring the right context to these AI agents.

If you think about most enterprises today, the way they're rolling out AI is that they actually just put it into the system and connect AI with all of enterprise systems in a rudimentary manner using MCP servers.

And now you're letting any piece of work that you are trying to do with AI

You're letting the models sort of brute force their way into trying to figure out and assemble the right raw materials that they need to complete the task and then do it.

And in this mode, AI is super slow.

It takes a lot of time to actually just assemble the basic information it needs to do the work.

It also becomes very, very costly because most of the tokens are being burned just trying to assemble the right context for that given task.

And you're trying to sort of use AI for things where it's not even good at or needed.

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