LangChain publishes guide on building custom agent harnesses for domain-specific tasks

LangChain · x · 2026-09-16

LangChain's Sydney Runkle argues building an agent (model + harness) comes down to two things: picking the right model on the cost/intelligence curve, and building a harness that gets the right context to the model at every step.
The post defines the harness as scaffolding connecting the model to the real world, and introduces createagent — pass a model, tools, and a system prompt to get a working agent (example: anthropic:claude-sonnet-4-6).
Pre-assembled harnesses like Deep Agents and Claude Agent SDK ship opinionated middleware (memory, context management, sandboxing) for fast productionization, but many agents need finer customization — custom prompting, business logic, guardrails — which the guide shows how to build on createagent.

More from coding & agent