Ethan LockshinSales at NVIDIA focused on AI adoption

Co-Founder & Chief Product Officer of Continue: Ty Dunn. Explaining what is missing in coding agents

Name: Co-Founder & Chief Product Officer of Continue: Ty Dunn. Explaining what is missing in coding agents
Uploaded: 2025-10-29T16:36:59+00:00
Duration: 1 min 33 s
Channel: Ethan Lockshin
Description: In a brief interview, Ty Dunn, Co‑Founder and Chief Product Officer of Continue, discusses what he sees as the biggest gaps in current AI‑powered coding…

29 Oct 2025 · 2 min

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1:33

In a brief interview, Ty Dunn, Co‑Founder and Chief Product Officer of Continue, discusses what he sees as the biggest gaps in current AI‑powered coding assistants such as GitHub Copilot, Cursor, and Claude Code. He argues that the primary missing element is the ability to build developer trust and a supportive experience that clearly demonstrates where AI is reliable. Once that foundation is established, the next frontier is enabling asynchronous, continuous AI agents that can run background workflows and seamlessly hand control back to humans when needed. This requires substantial infrastructure to manage human‑in‑the‑loop pauses, handoffs, and resumptions. Finally, Dunn highlights the need to minimize developer intervention, likening the future of AI‑assisted development to the evolution of build‑time and continuous integration pipelines, where much of the work is automated and developers focus on higher‑level decisions.

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I was recently reading the Q2 State of AI report by Artificial Analysis and there is a section for demand for AI coding tools. And at the top you had GitHub, Copilot, Cursor, Claude code, a few others, but then your company was there. Continue. So you are at the forefront of dev copilots. What do you think is still missing in today's AI coding tools?
We have to do more to help people build trust and actually gain experiences. And so it's actually not the most obvious when it comes to using this technology to build software that's be much easier to get the encouragement, the clarity, the inspiration you need to build trust in what is AI capable of doing, where can it be reliable and how can you apply it? And once that kind of foundation is set up, what then comes is the ability to pool all those with your team and have everybody work together on them. So where the frontier is moving towards asynchronous code agents and in particular this idea of continuous AI and that's a huge infrastructure build out. In order to make that happen, you need the ability to go from these asynchronous workflows that are running in the background and bring those back into the loop. Because this technology in some cases really needs the human to be able to pause, take over and hand back control to them. The last missing piece that I can see at this point is minimizing developer intervention and setting people up with the tools to do that. That is the frontier of what it means to build software and in the future is similar to build time and continuous integration. And that's the future of the engineering.