Vers Swarm Orchestration

Spawn and coordinate multiple agents across branched Vers VMs. Each agent runs in an isolated environment branched from a common state.

Prerequisites

•VERS_API_KEY environment variable
•A committed VM state (commit_id) to branch from
•For Clawdbot swarms: use sessions_spawn for each VM

Concept

code

        [Golden Commit]
              │
    ┌─────────┼─────────┐
    ▼         ▼         ▼
 [VM-A]    [VM-B]    [VM-C]
 Agent1    Agent2    Agent3
   │         │         │
   ▼         ▼         ▼
 Result1   Result2   Result3

All agents start from identical state, explore independently, report back.

Workflow

1. Prepare Golden State

Create and configure a VM with all needed tools:

bash

# Create VM
VM_ID=$(curl -s -X POST -H "Authorization: Bearer $VERS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"vm_config": {"vcpu_count": 2, "mem_size_mib": 2048, "fs_size_mib": 2048}}' \
  "https://api.vers.sh/api/v1/vm/new_root?wait_boot=true" | jq -r .vm_id)

# SSH in and install tools (Node, Python, git, etc.)
# ... setup commands ...

# Commit as golden image
COMMIT_ID=$(curl -s -X POST -H "Authorization: Bearer $VERS_API_KEY" \
  https://api.vers.sh/api/v1/vm/$VM_ID/commit | jq -r .commit_id)

echo "Golden commit: $COMMIT_ID"

2. Spawn Swarm

Branch N VMs from the golden commit:

bash

# Branch from commit (repeat for each agent)
NEW_VM=$(curl -s -X POST -H "Authorization: Bearer $VERS_API_KEY" \
  https://api.vers.sh/api/v1/vm/branch/by_commit/$COMMIT_ID | jq -r .vm_id)

3. Dispatch Tasks

For Clawdbot, use sessions_spawn to create sub-agents that SSH into each VM:

code

For each VM:
  1. Get SSH credentials
  2. Spawn sub-agent with task
  3. Sub-agent SSHs to VM, executes task
  4. Report results back

4. Collect Results

Wait for all agents to complete, gather outputs.

5. Teardown

Delete all swarm VMs when done:

bash

curl -s -X DELETE -H "Authorization: Bearer $VERS_API_KEY" \
  https://api.vers.sh/api/v1/vm/$VM_ID

Use Cases

Parallel Code Exploration

•Branch 3 VMs
•Agent A: Try approach with library X
•Agent B: Try approach with library Y
•Agent C: Try from-scratch implementation
•Compare results, pick winner

Distributed Testing

•Branch per test suite
•Run tests in parallel
•Aggregate results

Safe Experimentation

•Branch before risky changes
•If it breaks, the original is untouched
•If it works, commit the new state

Coordination Patterns

Fan-Out / Fan-In

•Coordinator commits baseline
•Fan-out: spawn N workers from commit
•Workers execute independently
•Fan-in: collect results, synthesize

Checkpoint & Retry

•Commit before each major step
•If step fails, restore and retry with different approach
•Build up chain of successful commits

Tips

•Keep golden images minimal but complete
•Commit often — checkpoints are cheap
•Label your commits (store commit_id → description mapping)
•Clean up VMs when done to avoid costs
•VMs branch instantly — the copy-on-write is fast