Jeremy Huang

Coordinating agents in a repository

Jcode manages sessions through a shared server. When one agent changes a file another has read, the server notifies the second agent so it can inspect the change and respond. Agents can message one another or coordinate a group of workers. The software supplies communication and awareness of changes; agents still need to reason about conflicts and the correctness of their combined work.[2]

Customizing the harness itself

The project’s self-development mode lets an agent modify, build and test Jcode’s own source, then reload its binary while continuing a session. This makes the harness another editable part of the workflow. Its demonstrations and reproducible benchmarks expose concrete behavior such as startup latency and incremental session memory.[2]

Huang frames the number of agents a developer can run as a systems problem: each additional process consumes memory, so a heavy harness can constrain concurrency before the model service becomes the limit. Jcode’s design targets that overhead. His company’s launch demonstrates a workflow with many parallel agents; its comparative measurements are project-specific benchmarks rather than a general promise for every machine or task.[1]