Hermes Subagents: Parallel Workflows and Multi-Agent Patterns

Hermes Agent supports four parallel subagent patterns: Parallel Independent (same task to N agents), Pipeline with Dependencies (chain tasks sequentially), Fan-Out/Fan-In (split work then merge), and Competitive (N agents same task, pick best). Configure with delegate_task and the kanban board for crash recovery.

A single agent session processes tasks sequentially. While it researches an API, it is not writing code. While it writes code, it is not running tests. Parallel subagents break through that ceiling by running multiple workstreams simultaneously.

[TOOL: Hermes delegate_task] The core primitive for spawning child agents with isolated context windows. Each subagent gets its own conversation, tool access, and terminal session. They cannot see each other's work or the parent's conversation history. This isolation prevents context poisoning and keeps the parent's context window clean.

Pattern 1: Parallel Independent. Deploy the same task to N agents with different parameters. Useful for research: one agent researches Stripe API, another researches PayPal API, a third researches Braintree. All run simultaneously and return structured summaries. The parent merges results into a comparison table.

Pattern 2: Pipeline with Dependencies. Chain tasks where downstream steps need upstream results. Step 1 researches the topic. Step 2 drafts the outline (depends on step 1). Step 3 writes the full article (depends on step 2). Each step gets the previous step's output injected into context. No parent relay needed.

[STAT: Pipeline patterns reduce multi-step task completion time by 60-70% compared to sequential single-agent execution (Source: Hermes Community Benchmarks, 2026)]

Pattern 3: Fan-Out/Fan-In. Split a large task into smaller independent pieces, run them in parallel, then merge. Perfect for multi-chapter content creation, codebase-wide refactoring, or batch research. The orchestrator splits the work, monitors completion, and synthesizes results through a barrier sync.

Pattern 4: Competitive. Spawn N agents to attempt the same task using different approaches or prompts. A judging agent evaluates all outputs against a rubric and selects the best. Useful when quality matters more than speed — generating multiple design proposals, architecture options, or copy variants.

[TOOL: Hermes Kanban Board] For production multi-agent pipelines, the kanban board provides crash recovery. Each task is a card on the board. Completed tasks commit results. Failed tasks are reclaimed by the orchestrator. The board survives agent crashes, process restarts, and full server reboots.

The file coordination layer prevents parallel agents from clobbering each other's edits. When concurrent subagents write to the filesystem, the coordination layer uses advisory file locks and conflict detection. If two agents modify the same file, the second write is blocked and the orchestrator is notified.

Real example from the community: 12 Hermes instances running in parallel daily to build Hermes Agent itself (Source: @Teknium, 2026). Each instance handles a different aspect of development. The kanban board coordinates work across all instances.

Start with Pattern 1 (Parallel Independent) for your first multi-agent workflow. Add pipeline dependencies as you discover sequential steps. Graduate to competitive patterns when output quality is critical and you can afford the extra token cost.

Related Architecture & Implementation Resources

• Explore more production agent architectures in the Daily AI World AI Workflows Directory.
• Discover compatible tool interfaces in the Model Context Protocol (MCP) Directory.
• Track breaking model benchmarks and unit economics on Latest AI News.