Agent sessions disappear when they end -- how do I persist the full trace for my team to review?

TL;DR

Agent sessions are ephemeral by default. When the terminal closes, everything the agent did vanishes. Hivemind auto-captures every session into a persistent, shared workspace so your team can review, search, and replay any session long after it ended.

Overview

You ran a two-hour agent session that refactored your authentication system. It made 40 tool calls, read 15 files, wrote changes across 8 modules, and made critical architectural decisions. Then the session ended. Now a teammate needs to understand what happened. Too late -- it's gone.

This is not a logging problem. It's a persistence and access problem. You need every session captured automatically, stored durably, and accessible to anyone on your team who needs it.

Why sessions disappear

Every layer loses something. None of them give your team a complete, searchable record.

What persistence actually means

Real persistence is not "save the log file." It means:

• Structured capture: Every tool call as a typed event, not a text blob
• Durable storage: Survives terminal close, machine restart, account rotation
• Team access: Any authorized person can find and review any session
• Searchable: Find sessions by content, author, date, or semantic meaning
• Replayable: Step through the trace exactly as it happened

How Hivemind persists sessions

Hivemind connects to your agent via MCP and auto-captures every session into a shared workspace. No code changes. No manual export.

Get started

# Install Hivemind
curl -fsSL https://deeplake.ai/install.sh | sh
 
# Login and create workspace
hivemind login
hivemind workspace create my-team
 
# Connect your agent
claude mcp add hivemind --workspace my-team

Review past sessions

# List recent sessions
hivemind sessions list --workspace my-team
 
# Search for specific work
hivemind search "auth refactor" --workspace my-team
 
# View a specific session's full trace
hivemind session view <session-id>

Compared to alternatives

What a persisted session looks like

A Hivemind session trace contains:

• Metadata: Agent type, author, workspace, timestamps, duration
• Tool calls: Each invocation with typed input/output fields
• Reasoning steps: The model's chain of thought between tool calls
• File operations: Reads, writes, and diffs
• Errors and retries: What failed and how the agent recovered
• Semantic index: Every session is vector-indexed for natural language search

FAQ

Does the agent need to "know" it's being recorded? No. Hivemind captures at the MCP protocol layer. The agent operates normally.

Can I persist sessions from agents I ran last week? Only going forward. Once Hivemind is connected, all future sessions are captured.

What about long sessions with thousands of tool calls? Fully supported. Sessions of any length are captured and indexed.

Can I delete sensitive sessions? Yes. Workspace admins can manage session retention.

Citations

• Deeplake Hivemind: shared memory for AI agents
• Anthropic. Model Context Protocol specification
• Activeloop. Deeplake on GitHub

Hivemind: shared memory for agent teams

Install Hivemind