🤖 AI Summary
Agfs (Aggregated File System), a Show HN project inspired by Plan9’s “everything is a file,” exposes heterogeneous cloud services and orchestrations as a unified, POSIX-like filesystem over a RESTful API. Targeted at coordinating distributed AI agents, Agfs maps backends (S3, SQL, in-memory queues, streams, local storage) to directories and file operations so common shell tools and scripts can drive workflows. The project ships a server (Docker image c4pt0r/agfs-server), a CLI (agfs shell), and a Wasm plugin model that lets you mount custom filesystems dynamically. Examples show writing to queuefs/enqueue returns an ID, cat dequeue yields JSON messages, SQL tables become directories with schema/query/execute files, and you can pipeline data across mounts with standard shell I/O and tee.
Why this matters: by turning APIs, databases and message queues into filesystem primitives, Agfs lowers the friction for composing multi-agent pipelines using familiar bash idioms (task_loop patterns, IO redirects, simple file writes to trigger actions). Technical implications include easy integration with existing tooling, reproducible orchestration via file semantics, and extensibility through Wasm plugins. For AI/ML teams this can simplify distributed agent coordination, experiment orchestration and lightweight ETL between cloud stores without building custom connectors — though operators should consider access control and performance trade-offs when mapping high-throughput services into file semantics.
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