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Prime Agent 0.9.2 Persists Trace Upload Progress with an On-Disk Cursor and Resumes Unfinished Work After Restart

The new release turns agent trace uploads into a persistent outbox. Processes no longer wait for network transfers when exiting, and can resume uploads from a byte cursor after restarting. It also begins recording semantic edges across sub-agents, but there is currently no corresponding delivery endpoint, so this should not be considered a complete distributed tracing capability.

U.S. Navy photo by Lt. j.g. Andrew Leatherwood · Public domain · Image source
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Prime Intellect released Prime Agent 0.9.2 on September 5, addressing two of the areas most prone to failure in long-running, multi-agent workloads: trace data persistence, and agent-tree state and cost accounting. Previously, a process could wait for trace uploads when exiting. The new release uses an on-disk cursor outbox that stores each session’s upload intent and the position of content already sent. Scheduled uploads process only newly appended data. When rate-limited, they are rescheduled according to `Retry-After` instead of putting the process to sleep in place; after an unexpected termination, catch-up runs on the next startup.

This design decouples “agent task completion” from “successful telemetry delivery,” reducing the likelihood that network or tracing-service failures will hold up the daemon. The tradeoff is that the local outbox becomes a new form of persistent state: operators must monitor backlog size and disk usage, and clean up cursors after deleting sessions. Otherwise, asynchronous delivery merely postpones failures.

Version 0.9.2 also extracts a shared append-only event-log foundation that supports the RLM spawn ledger through single-call `O_APPEND` writes, optional fsync, bounded fail-closed replay, and a recovery mechanism that tolerates a truncated final line. The new `semantic-edges.jsonl` assigns stable request IDs to model requests and records parent-child sessions, sub-agent calls and returns, continuations, and compaction events, allowing tools to reconstruct multi-agent execution graphs. However, the release notes explicitly state that only derivation and outbox registration are currently implemented; there is not yet an endpoint that actually delivers this type of ledger.

Other updates make MCP server tools supplied by ACP clients natively callable, recursively aggregate sub-agent token usage and costs, and fix potentially exponential revisiting during cancellation of deeply nested agent trees. This is an execution-reliability update, with no new standalone capability benchmark; Prime Agent’s core still allows models to execute code through a persistent IPython kernel. Adopters should verify MCP permissions within an external sandbox, check whether trace content contains sensitive data, and test whether crash recovery can produce duplicate side effects.

Sources

  1. Release v0.9.2 · PrimeIntellect-ai/prime-agent
  2. Prime Agent: A self-improving RLM agent
  3. Prime Agent: A Self-Improving RLM Harness