> ## Documentation Index
> Fetch the complete documentation index at: https://docs.driven.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Multi-Agent Strategies

> How to run multiple Driven Agents in parallel: separate value and momentum strategies, keep contexts clean, and compare how different approaches perform.

This guide covers running multiple Agents, each with its own strategy, context, and portfolio. Because each [Agent](/concepts/agents) is independent, you can run strategies that should not share assumptions side by side, and compare how they perform without one contaminating the other.

## Why use multiple Agents

A single Agent works best when it has one coherent strategy. The moment you try to run a long-term value approach and a short-term momentum approach out of the same workspace, their assumptions collide: the risk rules differ, the time horizons differ, the screening criteria differ. Splitting them into separate Agents keeps each one clean and its scheduled tasks unambiguous.

## Common multi-agent setups

* **Value Agent + momentum Agent** — two different philosophies, each with its own Playbook and rules
* **By market** — a US Agent, a Hong Kong Agent, an A-share Agent, each tuned to its market
* **By horizon** — a long-term portfolio Agent and a short-term trading-experiment Agent
* **Research + monitoring** — one Agent for deep research, another dedicated to portfolio monitoring and alerts

## Step 1: Define each Agent's mandate

Give each Agent a clear, distinct purpose and Playbook. For a value Agent:

```text theme={null}
This agent runs a long-term value strategy. Add to its Playbook: focus on profitable, durable businesses trading below intrinsic value, with strong balance sheets. Long holding periods. Avoid momentum-driven names.
```

For a separate momentum Agent:

```text theme={null}
This agent runs a momentum strategy. Add to its Playbook: focus on names with strong relative strength and improving fundamentals. Shorter horizons. Defined invalidation levels on every position.
```

## Step 2: Keep contexts separate

The point of multiple Agents is isolation. Do not blur it — run value research in the value Agent and momentum research in the momentum Agent. Each builds its own history, portfolio, and intuition for its strategy.

## Step 3: Compare performance

Because each Agent has its own paper portfolio, you can compare approaches directly:

```text theme={null}
[In each agent] Summarize this strategy's paper portfolio performance and what's driving it.
```

Running the same period through two different strategies is one of the most useful things paper trading enables.

## Step 4: Let each Agent specialize

Over time, each Agent's Playbook and history make it better at its job. A value Agent that has only ever done value research develops cleaner instincts for it than a generalist juggling everything.

## Common mistakes

* **Too many Agents.** Every Agent is context to maintain. Create one per genuinely distinct strategy, not one per idea.
* **Blurring the mandates.** If you run momentum trades in your value Agent, you have lost the benefit of separation.
* **Not comparing.** The big payoff of multiple Agents is head-to-head comparison. Use it.

## When one Agent is enough

If your strategies share a universe and rules, keep them together. Multiple Agents are for approaches that genuinely should not share assumptions, not for organizing a single coherent strategy.

## Related

* [Agents concept](/concepts/agents) — how Agents work
* [Build your Playbook](/guides/strategy/build-your-playbook) — give each Agent its strategy
* [Value investing setup](/guides/strategy/value-investing-setup) — configure a value Agent
* [Growth investing setup](/guides/strategy/growth-investing-setup) — configure a growth Agent