Multi-Agent Orchestration: Shipped. Ephemeral Agent Creation: Next

A product manager friend recently approached me with a screenshot of Genspark’s all-agents interface. “Kay,” he asked, “you have shipped so many agent features. How do you decide what to add next? How do you ensure users can keep up with all these new capabilities?

Multi-Agent Orchestration: Shipped. Ephemeral Agent Creation: Next

My answer was simple: We don’t ensure it, and we don’t intend to.

Since launching our Super Agent in April, we’ve taken a fundamentally different approach: treat features as tools, not destinations. Instead of forcing users to learn every new agent, the Super Agent learns them. Every feature we implement becomes a tool that our Super Agent can intelligently leverage. It selects the right capabilities, combines them through agentic reasoning, and helps users complete tasks end-to-end. The various agents you see in that screenshot aren’t standalone products—they’re building blocks. Our Super Agent orchestrates them seamlessly to create a unified experience.

Multi-Agent Orchestration: Shipped. Ephemeral Agent Creation: Next

Today marks a major leap toward this vision. We’re launching the Genspark Multi-Agent Platform, where you can assign tasks to a lead agent that simultaneously coordinates multiple specialized sub-agents to accomplish complex objectives.

A Symphony of Specialized Agents

Each Genspark agent operates in its own specialized canvas or environment:

  • AI Sheet Agent manages data tables and spreadsheets

  • AI Slides Agent crafts and refines presentations

  • AI Document Agent edits and formats documents

  • Call for Me maintains active phone conversations

  • Code Agent operates within its isolated coding sandbox

The magic of our Multi-Agent Platform lies in how it manages context across these diverse environments, enabling true collaboration between agents.

Here’s a key technical insight: While agents can execute in parallel, we maintain a fundamentally linear context. When parallel execution occurs, each sub-agent receives the same contextual snapshot. After gathering results, the lead agent updates the context holistically.

This design choice emerged from hard experience—non-linear context creates coordination nightmares, much like large companies constantly holding meetings to ensure everyone is “on the same page.” Our linear context approach keeps all agents inherently aligned while maximizing parallel execution benefits. The result? Superior user experience without sacrificing performance.

Create individual slide presentations for the top 10 largest US companies by market cap. Complete all tasks in parallel.

Preview: On-Demand Ephemeral Agents

In the spirit of building in public, let me preview what’s coming next to the Genspark Multi-Agent Platform: on-demand ephemeral agents.

Soon, lead agents will be able to instantiate specialized agents on the fly by writing a YAML configuration file. These ephemeral agents receive:

  • A specific toolset tailored to their task

  • Custom system prompts

  • Even specialized models when needed

DEMO: Investment Memo Assistant YAML Configuration File

name: Investment Memo Assistant&

description: Specialized assistant agent for investment analysis

version: 1.0

model: claude-4-sonnet

system_prompt: | You are a professional investment memo assistant…

https://mainfunc.ai/blog/genspark_multiagent_orchestration

Imagine an agent specifically instantiated to write investment memos using your firm’s exact format, or one that generates unit tests following your team’s development standards. These aren’t pre-built features—they’re agents created in real-time for your specific needs.

Our platform will include a library of pre-configured YAML definitions for common use cases, triggered automatically when appropriate. But the real power comes from the lead agent’s ability to create entirely new agent configurations based on the task at hand.

The Path to AGI

When tools can be generated on-the-fly through Python containers, and agents themselves (defined by toolsets, system prompts, and models) can be dynamically created by our Multi-Agent Platform, we approach something truly transformative.

This is when users experience that genuine “wow” moment—not from any single feature, but from a system that adapts, evolves, and creates new capabilities as needed. It’s intelligence that doesn’t just use tools but creates them. It doesn’t just follow workflows but invents them.

Stay tuned for Genspark’s evolution. When it comes to what we’re building, even the sky won’t be our limit.

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