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Back to 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, with Harrison Chase.

Why Do Domain Experts Win With Vertical Agents?

Harrison Chase says a founder should start a vertical agent at the harness layer, doing context engineering before any post-training of the model, because domain experts who can verify the work capture the value.

People say agent value sits in verification, whether the agent did the job well, because verification unlocks the next step, automation. The winners are the domain experts who can quantify what the value means, which is very hard. Building evals is a very hard job, so a lot of the value will accrue to whoever can write the verifiers and capture the domain knowledge. Vertical agents for different domains follow from that, because the domain experts best suited to write the verifiers or build the evals will be able to build harnesses and models. It will not be the harness alone or the model alone. It will be some combination of them.

The practical path is to start at the harness layer, do context engineering, tweak the harness, and once users are on board, start tweaking the model in post-training. Starting at the context or harness layer first brings a much higher return. The verticals will quantify what good looks like in a domain-specific way, and that lets them build vertical agents and vertical agent experiences. Different agents might have different experiences.

Grokipedia·Harrison Chase

Transcript

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 ·

The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch

More from this episode

  1. Should I Take a Sequoia and Benchmark Discount?Harrison Chase says it is absolutely worth taking a discount for Sequoia and Benchmark.
  2. What Is the Hardest Part of Building AI Agents?Harrison Chase says the hardest part of building agents is getting the system to behave reliably. Models are non-deterministic black boxes.
  3. Will Model Labs Eat the Agent Harness?Harrison Chase says the agent harness should stay neutral, so the memory and context an agent builds are not locked to one model lab.
  4. Why Hasn't Anyone Solved AI Memory?Harrison Chase says the hardest part of AI memory is the intelligence that decides what to keep, not the database.
  5. What Kind of Agent Do Most Apps Need?Harrison Chase says most apps probably need a vertical agent of their own.
  6. Why Are AI Bills Rising Even as Models Get Cheaper?Harrison Chase says AI bills rise because agents burn far more tokens, even while frontier models get cheaper on price for performance.
  7. What Share of Engineering Salary Goes to Coding Tools?Harrison Chase says they spend roughly 30% of engineering salary on coding tools.
  8. Should Companies Fear Open Source Chinese Models?Harrison Chase does not think fear of open source Chinese models is justified. Some enterprises are fearful of working with open source Chinese models.
  9. Should Founders Discount for Sequoia and Benchmark?Harrison Chase says taking money from Benchmark changes a company's trajectory completely, and a discount is absolutely worth it for Sequoia and for Benchmark.

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