Create a LangChain Deep Agents Harness Profile for NVIDIA Nemotron 3 Ultra to Improve Performance
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Sean Lopp
Author
Sean Lopp
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Terms in this piece · Glossary
agent harness — The scaffolding around a model that turns it into a working agent — the loop, the tools it can call, and the rules for when to stop.
Why it matters
Matching the agent harnessThe scaffolding around a model that turns it into a working agent — the loop, the tools it can call, and the rules for when to stop.Full definition → to a cheaper model can close more of the gap than switching models.
Key quotes
“The goal of harness engineering is to make the calls from the agent to the model more closely resemble what the model saw in the training data.”
Sean Lopp
“Geoffrey Huntley calls this the “ralph loop”: a model repeatedly reads the current state, makes one change, and uses the filesystem—not the conversation—as memory.”
Sean Lopp
“A fix is accepted only after it passes the same test several times in a row, which filters out changes that passed once by luck.”
Sean Lopp
“And it is told to prefer the general fix over the specific hack—to infer the broader behavior a failure exposes rather than special-casing the exact inputs of one test. This distinction is the difference between teaching the model a durable skill and memorizing a single answer.”
Sean Lopp
“The evaluation benchmark is what makes this safe to automate—it gives the loop a ground-truth verifier, so a proposed change is only kept if it measurably helps.”
