Ethan LockshinSales at NVIDIA focused on AI adoption

The Co-Founder of booming AI startup Continue reveals what’s next in coding.

Name: The Co-Founder of booming AI startup Continue reveals what’s next in coding.
Uploaded: 2025-10-29T15:36:56+00:00
Duration: 1 min 22 s
Channel: Ethan Lockshin
Description: In this monologue, the co‑founder of the AI startup Continue outlines how AI will transform the software development lifecycle over the next three years…

29 Oct 2025 · 1 min

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1:22

In this monologue, the co‑founder of the AI startup Continue outlines how AI will transform the software development lifecycle over the next three years. He argues that the current model of a single AI assistant under direct human supervision will give way to multi‑threaded, event‑driven workflows where many AI coding agents operate concurrently. These agents will be triggered by regular cadences (daily, weekly, monthly) or by events such as pull‑request openings or JIRA ticket creation. Humans will shift from constantly monitoring a single agent to indirectly overseeing and managing a fleet of assistants, providing feedback, permissions, and occasional interventions. This evolution creates an asynchronous, multiplayer environment he calls “continuous AI,” where AI inference happens both inside the human loop and increasingly outside of it, enabling constant, automated code assistance throughout the development process.

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How do you see the role of AI evolving in the software development life cycle over the next three years? I don't know if I can predict the next six months, but if you're pressing me, then the thing I would say is we're going to move from kind of human in the loop, direct monitoring, watching over everything that's happening step by step in real time, to actually multi threaded workflows where you have multiple agents going on where events happen. So either like on a daily, weekly, monthly cadence, you often have tasks that need to be done, or there's event driven tasks where maybe pull request opens or a JIRA tickets created that kicks off workflows. We're moving kind of from directly monitoring all day, every day at one agent to kind of be able to have to directly monitor, indirectly monitor and manage many AI code assistants at once. So you and the agents can kind of work together. And there's the places where the human touch and the human feedback and the human permissions gathering are set up in a way that works for you in the long run. I think that ends up increasingly causing things to look asynchronous, to look multiplayer. The term we like to use is continuous AI where you're just constantly having events happen. And so I think that the next three years are definitely about kind of increasingly moving towards a lot more inference, empowering many more kind of AI coding agents that are running in the loop with the human, but also increasingly outside the loop of the human and outer loop.