Field notes from the frontier of agent systems.

Agents are becoming real operators in real environments. They write code, inspect files, call tools, monitor systems, coordinate with other agents, and increasingly act inside machines that have memory, constraints, failure modes, and operational texture.

That changes the work. The interesting questions are no longer only about model capability. They are about perception, coordination, grounding, judgment, self-regulation, instrumentation, and trust.

Can an agent understand the machine it inhabits? Can it adapt under pressure? Can multiple agents share reality instead of hallucinating past one another? Can a workflow remain legible as it becomes more autonomous? Can we build systems that feel durable in practice, not just impressive in demos?

Local Frontier exists to document that territory. It is a workshop, publication, and running notebook for builders working on local-first agents, MCPs, orchestration, observability, memory, evaluation, and the practical weirdness of living with increasingly autonomous tools on real machines.

This is not meant to be generic AI discourse. It is meant to hold the texture of the work: the build logs, the patterns, the failures, the changes in taste and judgment that happen when agents stop being a topic and start becoming an environment.