Agent Lab is where the work gets built in the open. Small agents, unusual workflows, and tools that extend how EchoNerve operates — documented from concept to deployment.
The premise: the best way to understand agent systems is to build them. Not toy demos — real tools with real constraints, real failure modes, and real operational requirements. Agent Lab documents that process: what got built, what decisions were made and why, what broke, what the working version looks like, and what a team without a dedicated AI engineer would need to replicate it.
Past builds include: a source-monitoring agent that tracks specific researchers and topics across papers and preprints, a brief-drafting workflow that assembles the week’s signal from structured inputs, and an editorial quality check that runs before publication. Each is documented as a case study — specific enough to be useful, honest about the parts that didn’t work.
Agent Lab drops when something is built and worth documenting. Roughly monthly. The builds are practical and the documentation is direct.
Status: Active. Members only.