20VC: Five Predictions for a World of Agents | The Ads Business Model Will Die | Biggest Lessons from Working with Elon Musk at Twitter with Parag Agrawal, Parallel

Parag Agrawal (0:00)

We're gonna see the biggest or the frontier models be bigger and bigger over time. It appears there is no end to the scaling law that we can perceive so far. I think today we don't know how to pay for unique valuable insight or data. Ads don't work with agents in their current form. You need to find a replacement to the ads business model. I do think there should be some disparity in wealth, but I don't know what's too much.

Harry Stebbings (0:24)

This is 20VC with me, Harry Stebbings. Now, what do Andrew Reid, Vinod Khosla, and Josh Cooperman all have in common? Well, they all believe in Parag Agrawal to change the future of agentic search. Parag is the founder of Parallel, as I said, changing the future of how agents do web search efficiently. This is an incredible discussion on the future of agentic search, the future of income and wealth inequality, and so much more. Parag rarely does shows, and so it was very special to sit down in person with him in London. But before we dive into the show today, MongoDB has always been the database developers' love. Well, now is the data platform AI agents need. Agents need accurate context, fast. MongoDB stores, searches and reasons over your data in real time. JSON-native database, vector search, and Voyage AI embeddings all in one place. One system instead of 10, no data pipelines to maintain. Oh, this sounds too good to be true. Build and scale from your first user to billions of vectors. Run on any cloud, on-prem or your laptop even. That's why 75% of the Fortune 100 run their most critical apps on MongoDB, moving trillions of dollars every single day. And it's why AI-native companies like 11 Labs run 40 million agents on MongoDB. So if you're building in AI, MongoDB for startups helps you move faster with Atlas and Voyage AI credits and dedicated support. Don't build agents that answer once and forget. Build agents that remember and learn from your real-time data. Go to mongodb.com/agents.

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Parag Agrawal (3:08)

You have now arrived at your destination.

Harry Stebbings (3:11)

Parag, I'm so excited for this dude. I spoke to Vinod, I spoke to Andrew Reid, I spoke to Todd Jackson. Dude, I stalked the shit out of you, so thank you for joining me.

Parag Agrawal (3:21)

Thanks for having me and thanks for making all the calls.

Harry Stebbings (3:23)

Not at all. I would love to start with, for anyone that doesn't know, how would you describe Parallel in 60 seconds?

Parag Agrawal (3:32)

Parallel is the Google for agents. So agents need to search the web to do anything they do for you, whether it's a personal agent or an agent built for work. Just like humans need to go on a browser, search Google, oftentimes during work or for whatever you're doing in life, your agent needs to do the same. It turns out agents are different from humans and the way you build web search for agents is different. Parallel is about building the technology for agents to search the web and then the business models to make that sustainable.

Harry Stebbings (4:01)

Was that the original insight that you had?

Parag Agrawal (4:03)

Yeah, literally the first genesis of the company was the statement that agents will use the web 1000x more than humans. I wrote that down at some point. Hence, new tech is needed and new business models are needed. 1000x gives you a sense of scale. It changes how you think about building the tech underneath because no tech built for a certain scale survives three orders of magnitude. And then when you need new business models alongside new technology, a problem becomes really interesting.