CEOInterviews.AI
Start App
Try: AI strategy tariffs earnings guidance layoffs interest rates growth

Harrison Chase

Co-founder & CEO, LangChain

Search every verified Harrison Chase interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. Harrison Chase, co-founder and CEO of LangChain, discussed the company's focus on agent development and infrastructure in recent appearances. At the Interrupt NYC conference in October 2026, he announced updates to LangSmith's Managed Deep Agents, including auth primitives, user-level memory, and built-in web search via Parallel. He also outlined a philosophy of "owning your intelligence," which he described as building domain-specific components around models, supported by an open, model-neutral harness, a learning loop from agent usage, and governance for internal agents. In interviews, Chase said LangChain has rebuilt its product stack multiple times since 2022 due to changing models, and acknowledged underestimating demand for raw inference and general-purpose coding agents. He stated that the company spends roughly 30% of its engineering salary on coding tools, a figure that declined over two months while token usage increased. Chase also said he believes models are becoming commoditized, with differentiation shifting to surrounding data and domain-specific harnesses. He noted that LangChain built a gateway "way too late" and expressed a preference for rapid iteration over dogmatic adherence to specific approaches.

Recent appearances

  • Horizontal vs Vertical Agents: Who Wins? | Model Routing: Commodity or Increasing in Value?

    October 17, 2026 · 📺 20VC with Harry Stebbings

    Harrison Chase is the co-founder and CEO of LangChain, which helps developers build, test and deploy AI agents. Backed by Sequoia Capital, Benchmark and IVP, LangChain has announced approximately $160 million in funding with the last round at a $1.25BN valuation. The company works with 35% of the Fortune 500, has surpassed one billion open-source downloads and processes over one billion events daily through LangSmith. ----------------------------------------------- Timestamps: 00:00 Intro 01:05 What Is LangChain and Why Are Agents Still So Hard to Build? 03:17 Why Better Models Force LangCha…

    Read the verified transcript → Watch on YouTube ↗

  • Interrupt NYC: Opening Keynote

    October 05, 2026 · 📺 LangChain

    Harrison Chase, Co-Founder and CEO of LangChain, uses examples from Rogo, Harvey, and JPMorgan Chase to explain owning your intelligence, which means building domain-specific pieces in and around the model, and the three pillars it takes: an open, model-neutral harness such as LangGraph or Deep Agents, a loop that compounds what you learn from how people use your agents, and governance for internal agents. He then walks through the LangSmith platform layer by layer: a new Managed Deep Agents release with auth primitives, user-level memory, and built-in web search via Parallel, decision model…

    Read the verified transcript → Watch on YouTube ↗

  • LangChain CEO Harrison Chase on the infrastructure bet he got wrong

    September 15, 2026 · 📺 Browserbase

    Chase (Co-Founder & CEO of LangChain) has rebuilt his product stack four times since 2022, chasing models that kept changing underneath him. In this episode of Navigators, Paul sits down with him to talk about what LangChain got right, and the one piece of infrastructure it built years too late. Harrison admits the team underestimated how massive the demand for raw inference would become, and how big general-purpose coding agents would get. He walks through the shift from LangChain to LangGraph to DeepAgents, why sub-agents rarely work the way people expect, and why LangChain now runs its own…

    Read the verified transcript → Watch on YouTube ↗

  • When to Build Your Own Agent Harness | Harrison Chase, LangChain

    August 13, 2026 · 📺 Sequoia Capital

    An agent is a harness orchestrating a model and context. If you want to own your intelligence, you probably want to own all three. LangChain co-founder and CEO Harrison Chase focuses on the harness: the loop that brings the right context to the model at the right time, and how to customize it with middleware, hooks, and sub-agents. At Sequoia Capital's Own Your IntelligenceI event, Harrison explains when an off-the-shelf harness is enough and when to build your own (the more out-of-distribution your task, the more customization you'll want) and why even custom harnesses should keep in-distrib…

    Read the verified transcript → Watch on YouTube ↗

  • Agents in the Enterprise: Deep Agents, Evals, and Ambient UX | Austin Vance and Harrison Chase

    July 27, 2026 · 📺 @austinbv codes

    Austin Vance sits down with LangChain CEO Harrison Chase to discuss how LangChain is using AI internally and what enterprise teams need to rethink as they build non-deterministic, LLM-driven software. Harrison shares how LangChain gives developers the freedom to choose their own coding agents, uses AGENTS.md files and skills to guide those systems, and runs an internal Slack-based agent responsible for a growing number of documentation pull requests. They also explore why enterprise AI requires stronger processes, evals-first development, human-in-the-loop experiences, and new roles focused…

    Read the verified transcript → Watch on YouTube ↗

  • The Agent Development Lifecycle 101 by Harrison Chase

    July 22, 2026 · 📺 LangChain

    How teams build, test, deploy, and improve production agents Everyone wants to ship agents, but the best teams are no longer treating agents as one-off demos or isolated projects. They are building a repeatable Agent Development Lifecycle: a system for building, testing, deploying, monitoring, and continuously improving agents over time. Join Harrison Chase, CEO and co-founder for LangChain for a walkthrough of the Agent Development Lifecycle and why it matters for teams moving agents into production. We’ll cover how leading teams are shifting from “build an agent” to an ongoing improvement l…

    Read the verified transcript → Watch on YouTube ↗

  • Jensen Huang: Why companies need open agent systems

    July 08, 2026 · 📺 LangChain and 2 more

    NVIDIA founder and CEO Jensen Huang sits down with Harrison Chase to discuss why the last six months finally made AI useful, and what it takes to turn a large language model into a real, deployable product. The path there, Jensen says, is building your own "super agents": domain-specific systems wrapped in an open harness, grounded in your data, and improved over time. NVIDIA and LangChain also announce a new blueprint for running Deep Agents with Nemotron 3 Ultra inside OpenShell, a secure, open runtime, giving every enterprise the building blocks to create and deploy super agents anywhere.…

    Read the verified transcript → Watch on YouTube ↗

  • Why Enterprise AI Adoption Is Slower Than You Think — Aaron Levie (Box) + Harrison Chase

    June 29, 2026 · 📺 LangChain

    Aaron Levie, CEO of Box, sits down with Harrison Chase, co-founder and CEO of LangChain, to dig into why AI agents are thriving in software development but still struggling to break through in the rest of the enterprise. Aaron breaks down the structural reasons the knowledge work gap exists, how Box is building its agent harness, and why being headless might actually drive more usage than it kills. Chapters: 0:00 Why Aaron tweets so much (and never uses AI to do it) 1:58 Box's core mission: bridging tech breakthroughs to the enterprise 3:28 Coding agents vs. knowledge work agents — why the ga…

    Read the verified transcript → Watch on YouTube ↗

  • The Future of AI Agents with Andrew Ng | Interrupt 26

    June 17, 2026 · 📺 LangChain

    Andrew Ng sat down with Harrison Chase for a wide-ranging fireside chat at Interrupt, the agent conference by LangChain. Watch the full session and get insights on: How fast coding agents have evolved and how the way small teams ship is being reshaped The "product management bottleneck" and why accelerating software development just moves the constraint somewhere else How enterprises are getting incremental AI wins but missing the bigger transformation The data architecture rework most companies haven't started yet ...and so much more The Future of AI Agents with Andrew NG | Interrupt 26 0…

    Read the verified transcript → Watch on YouTube ↗

  • The Future of AI Agents: What Will Interrupt 2027 Look Like? | Interrupt 26

    May 21, 2026 · 📺 LangChain

    Harrison Chase, Brace Sproul, and Caroline di Vittorio kicked off Day 2 of Interrupt 26 with an inside look at where AI agents are headed, the unveiling of LangChain Labs, as well as the latest features in LangSmith Fleet. 0:00 Welcome & Shoutouts 0:29 Setting the Stage: Imagining Interrupt 2027 1:22 Two Types of Agents: Long-Horizon vs. Customer Experience 2:42 The Future of Voice Agents 3:58 Why Every Agent Needs a Sandbox 4:47 The Rise of Open-Source Models 6:01 Agent Identity & Auth Patterns 7:26 Continual Learning: Model, Harness & Context Layers 10:42 Announcing LangChain Labs 11:00 Up…

    Read the verified transcript → Watch on YouTube ↗

  • The Agent Development Lifecycle: Build, Test, Deploy, Monitor | Interrupt 26

    May 19, 2026 · 📺 LangChain

    At the opening keynote from Interrupt 26, LangChain's annual agent conference. Harrison Chase (CEO & co-founder) and Ankush Gola (CTO & co-founder) walk through the Agent Development Lifecycle: the framework top teams use to build, test, deploy, and monitor AI agents in production, as well as a wave of new LangChain launches across every stage of that lifecycle. More resources The Agent Development Lifecycle Explained: https://www.langchain.com/blog/the-ag... SmithDB: https://www.langchain.com/blog/introd... LangSmith Engine: https://www.langchain.com/blog/introd... Try LangSmith: https://sm…

    Read the verified transcript → Watch on YouTube ↗

  • Harrison Chase of LangChain on Deep Agents, LangSmith, and Earning Trust | NVIDIA AI Podcast Ep. 297

    May 06, 2026 · 📺 NVIDIA

    LangChain has surpassed 1 billion downloads—and the framework that started as a weekend project is now the harness powering the next generation of production-grade AI agents. In this episode, Harrison Chase, co-founder & CEO of LangChain, breaks down the architecture behind deep agents, explains why systems like Claude Code, Manus, and Deep Research all share the same foundational pattern, and lays out what it actually takes to deploy autonomous agents responsibly in the enterprise. 🔬Topics covered: What is a ""deep agent,"" and why does architecture matter more than ever? How enterprises a…

    Read the verified transcript → Watch on YouTube ↗

Verified interview transcripts

Notable quotes

“I think we spend probably roughly 30% of our engineering salary on coding tools. It's actually gone down the last 2 months. While tokens, the number of tokens that we've used has actually gone up. And so this has we've done this by doing three steps. First is basically just visibility. We tracked all of our coding agent usage to LangSmith. So we could tell who was spending how much, what they were spending it on. We ”

“I think we built a gateway way too late. Um, I remember talking about this as a team a year year year and a half ago. Um, and and we just didn't really know like what we could provide that was different on top of like a light LLM or an open router. Although I think light LLM was really like the main thing at the time. Um, and uh, I think there I I think clearly there's one of one of the things that I've just consiste”

“The benefit of cost is it comes in a couple of different ways. I happen to think that when you have cost-effective intelligence, people just use more of it. When you have a cost-effective agent, then you can iterate across a larger search space. And as a result, the answer could actually be better. And in the case of Nemotron, it's cost-effective because it's so fast. It's so computationally efficient. When it's comp”

“Every company is built fundamentally on domain-specific or some specialized intellectual property. The reason why we call it intellectual property, intellectual, it's intelligence. Every single company is built on intelligence, some foundation of intelligence that's specialized. Our company is specialized in something. We're not good at everything, but we're very good at one thing, and every company is built that way”

“I think a very clear opportunity is kind of like in vertical AI applications where there is kind of like domain specific knowledge and domain specific tools that will not be built in to the base models uh or not be part of their their kind of like guiding like code coding is kind of like vertical in some way but it's so core and so generalizable that all of the models are kind of like rushing at it. Um, and so I thin”

“I think what creates more lock in is when there's state that starts to accumulate behind these APIs. And so that could take the form of kind of like short-term memory. So like what happens inside of a conversation. So conversational history which we see some of the model labs starting to do. Um and or it could take the form of long-term memory and learning kind of like preferences over time. I think that creates a lo”

The summary and quote tags on this profile are produced with AI assistance from verified, first-person interview transcripts, then checked by our team to confirm the speaker's identity and the accuracy of every quote. See how we verify →