Introducing tapes: Transparent Telemetry for AI Agents
Blog post from Paper Compute Company
AI agents are increasingly prevalent but lack transparency and auditability, leading to challenges in debugging and improving their performance due to missing records of their sessions. In response, Paper Compute has introduced "tapes," an open-source telemetry layer that creates durable, auditable records of AI agent sessions to address this observability gap. This system functions as an intermediary between AI agents and their inference providers, capturing essential telemetry data without altering workflows, and offers features like a proxy service, an API server for querying sessions, a CLI client for session analysis, and a terminal UI for detailed investigations. Tapes enhances search capabilities by allowing users to employ semantic search across recorded sessions, using content-addressable hashes for each message to enable conversation checkpointing, branching, and point-in-time retries. This tool aims to improve the management of AI agents by focusing on better tooling rather than smarter models, and it is the first component of the larger Paper Compute observability stack, with plans to expand support and integration with other platforms and storage solutions.
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