What "Multiple Agents" Hides
The phrase "multi-agent" gets used a lot. Claude Code says it. LangGraph says it. CrewAI says it. Marblo says it.
The problem: the word hides too much. Same word, very different architectures. This article compares the two most-confused setups — Claude Code's subagent pattern and genuine heterogeneous multi-agent orchestration.
1. What Is a Subagent?
Claude Code's subagent is "the main agent delegates a specific task to a child agent".
Main Claude
├── Sub Claude A (code review)
├── Sub Claude B (test authoring)
└── Sub Claude C (documentation)
Properties:
- All instances of the same model (Claude)
- The main agent controls start/stop
- Results aggregate back to the main agent
Pros: context separation saves tokens, all inside one tool, simple setup. Limitations: single vendor, every task tied to Claude's strengths/weaknesses, hard for PMs to observe externally.
2. What Is Real Heterogeneous Multi-Agent?
Genuine heterogeneous multi-agent means:
- Agents from different model vendors running concurrently (Claude + GPT + Gemini)
- Each agent in its own process (separate memory and rate limits)
- A central orchestrator routing tasks by model strength
- A GUI for PMs to observe and intervene in real time
This is the structure Marblo standardizes.
3. Five Concrete Differences
| Claude Code Subagents | Marblo Heterogeneous Multi-Agent | |
|---|---|---|
| Model diversity | Claude only | Claude + GPT + Gemini simultaneously |
| Isolation | Shared main context | Physical process isolation |
| Visualization | CLI text | Kanban + code + multi-terminal |
| PM access | Effectively no | Real-time via board |
| Rate limits | Single vendor cap | Independent per vendor |
4. Which Fits Which Situation?
Subagents Fit When
- Solo developer work — one person, one big code task
- Simple delegation — code review, docs, tasks that one model can handle
- Claude-only license environments
Heterogeneous Multi-Agent Fits When
- Multiple PMs/operators participate — board-based status sharing is essential
- Model-strength differences materially affect output — balanced backend accuracy + frontend speed + test automation
- Reducing single-vendor lock-in is a priority
- Internal system integration (ERP, CRM) with permission and audit-log management
5. "PM Sees the Board" — Why It Matters
The most-underestimated difference is PM access. Claude Code subagents live in the CLI. If a PM or decision-maker wants to ask "Where are the agents now?", a developer has to screenshot the terminal.
Board-based environments like Marblo are different:
- The PM views the kanban board on their own machine
- Clicking a card reveals agent activity logs, code changes, MCP calls
- They can drag cards to reprioritize, leave feedback comments
This isn't just UI polish. Operating AI agents at organizational scale requires a board as the coordination medium.
6. Conclusion — Tool Choice Is Organizational Choice
Subagents are a powerful personal tool. Heterogeneous multi-agent is organizational infrastructure.
Neither is superior — they serve different goals.
If you're seriously adopting AI agents organizationally, start with a structure that includes PM access + model diversity + governance. That prevents the 1-year migration tax.
Marblo is standardizing that structure. In-house Adoption Consulting helps design the right structure for your environment.