Entrepreneurs
1 Curated Dialogues
Harrison Chase
Key Views & Dialogues
20VC: Horizontal vs Vertical Agents: Who Wins | Model Routing: Commodity or Increasing in Value | The Future of the Inference Market | Why Founders Should Take Discounts for Tier 1 Firms with Harrison Chase, LangChain
Chase says vertical-agent routing belongs in a state-aware harness, where domain-specific context and verifiers differentiate products. He estimates most OpenRouter usage is gateway access; smart routing is less common than assumed, and better frontier models can erode its value. His inference-market reversal—passing on a gateway was “100% the wrong decision”—signals room for Fireworks, AWS, and Crusoe.
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- Harrison Chase’s clearest call: routing for vertical agents belongs in the harness, not the gateway, and routing is not a commodity. The harness knows state — prompt cache, prompt strategies, task context — and is his preference for domain-specific routing. Gateways have a portability case and may fit general coding or chat. He estimates most OpenRouter usage comes from being a gateway, not a router; smart routing happens less than people think, and a frontier model that gets better at everything can erode routing’s value.
- If agent value is derived through verification, domain experts win — and Chase is “massively bullish on vertical agents.” Whoever can write verifiers and build evals captures value; practically, founders should start at the context/harness layer and only post-train models once they have users. On Harvey and Ramp “building their own models”: much of it is post-training open-weight models, sometimes Chinese models, which he defends as valuable — “if you’re training a model from scratch, you’re probably at NeoLab.”
- Memory is the biggest unsolved layer in agents, and LangChain has the scar tissue to prove it. The hard part isn’t the database (some companies store memory in “a single file”) but distilling observations into context — a meta-reflection task LLMs still struggle with. LangChain launched and killed a commercial memory product because it “tried to be too general”; memory must be domain-specific, yet he expects “all products in a few years to have some aspect of memory.”
- LangChain spends roughly 30% of engineering salary on coding tools — and spend has gone down while token usage rose, via visibility, budgets, and owning the harness. One misconfigured plugin capturing the DOM every agent turn burned $40K in a week. Harry Stebbings frames this number as the fundamental determinant of Anthropic’s $2T value; Chase agrees it underpins it, but says software engineering is the only domain agents have really affected so far and expects agent impact in other domains to grow substantially.
- His biggest change of mind: “the market for inference is massive” — passing on building a gateway a year and a half ago was “100% the wrong decision.” He invokes Eric Vishria’s broader observation that “everything just works” and the market is big, and recalls Thomas Tunks’s point about inference demand. Chase says Fireworks, AWS, and Crusoe can all work because demand is so large. Enterprise fear of open-source Chinese models is “largely unfounded,” and he expects comparable U.S. open-source models within 12 months.
- The agent-era internet could be agent-to-agent: providers expose their own vertical agents, and horizontal agents interact with them. Chase’s proposed responses to infrastructure strain and lost ad/upsell opportunities are that vertical agents can interact with underlying systems more efficiently, and ads or recommendations could appear in the agent’s natural-language response.
- On venture: “absolutely it’s worth taking a discount for Sequoia, and Benchmark, and probably other tier-one VC firms.” Benchmark was a “third co-founder” from 2 to 400 people; Sequoia is “a machine” whose talent network sourced hires. His investing filter: talent, execution speed, and brand from being first — for a breakout team that’s proven its speed, “you just don’t look at the price and you just invest” — though AutoGPT, the fastest-growing GitHub project of all time, shows being first guarantees nothing. At the IPO prices Harry posed, Chase picks OpenAI at $1.5T over Anthropic at $2T.