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We hit an annualized run rate of $120M in October.
This year alone, we’re projected to add around $150M in net new revenue. This is an amazing milestone and a testament to the work of the @e2b team.
I’m particularly excited about two things:
1/ This showcases how strong the tailwinds of AGL (Agent-Led Growth) can be.
If you build a tool for agents and optimize your whole growth engine to serve them, you can see tremendous growth. This isn’t something you can just throw money at and buy. Agents don’t decide based on ads. You need a sophisticated growth engine that fine-tunes things like your AEO. I think this is what all future B2B devtool sales will look like. Increasingly, decisions about tool adoption will be made by agents, not humans.
2/ The use cases we’re serving. The majority of our revenue and usage comes from agents running in production. Not RL.
When we started, we had two theses: (i) code is all you need—all agents will use code to complete tasks (which has turned out to be true); and (ii) sandboxes for agentic workloads will be a bigger market than sandboxes for RL workloads, but takeoff will be slower (still playing out).
In the past 30 years, every company has become a software company. In the next 10 years, every company will have become an agent company. We’re building an infrastructure layer to power all these agents.
This year alone, we’re projected to add around $150M in net new revenue. This is an amazing milestone and a testament to the work of the @e2b team.
I’m particularly excited about two things:
1/ This showcases how strong the tailwinds of AGL (Agent-Led Growth) can be.
If you build a tool for agents and optimize your whole growth engine to serve them, you can see tremendous growth. This isn’t something you can just throw money at and buy. Agents don’t decide based on ads. You need a sophisticated growth engine that fine-tunes things like your AEO. I think this is what all future B2B devtool sales will look like. Increasingly, decisions about tool adoption will be made by agents, not humans.
2/ The use cases we’re serving. The majority of our revenue and usage comes from agents running in production. Not RL.
When we started, we had two theses: (i) code is all you need—all agents will use code to complete tasks (which has turned out to be true); and (ii) sandboxes for agentic workloads will be a bigger market than sandboxes for RL workloads, but takeoff will be slower (still playing out).
In the past 30 years, every company has become a software company. In the next 10 years, every company will have become an agent company. We’re building an infrastructure layer to power all these agents.
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