One Prompt, 100 Parallel Agents: How Google's Agent Graphs Coordinates Multi-Agent Work
goyalshaliniuk · x · 2026-09-17
A breakdown of Google's Agent Graphs pattern: instead of a single chatbot, one prompt gets decomposed into subtasks run by 100 AI agents in parallel, with outputs stitched into a larger result.
- The evolution path: Prompts → Agents → Loops → Graphs, with the graph orchestrating everything
- Each agent can run a different model (GPT, Claude, DeepSeek, or local open-source), making the model a swappable component
- The developer's core question shifts from "which model" to "how to design the system" — workflow design matters as much as the model
- Key concepts: agent orchestration, graph-based workflows, parallel execution, tool calling, feedback loops, multi-agent systems
Related event: Google's Agent Graphs: One Prompt, 100 Parallel Agents(4 posts)→
More from coding & agent
- Tencent unveils Hyra 2.0, a research agent that builds reusable scientific tools — TencentHunyuan · 2026-11-02
- General Reasoning explains how to train agent swarms with RL and latency pressure — rosstaylor90 · 2026-11-02
- "Coding isn't the bottleneck anymore — usage windows are," says founder Kyle Gawley — kylegawley · 2026-11-02
- Demo passed ≠ production-ready: 5 questions to answer before letting agents run your business — _kellhus · 2026-11-02
- An AI agent passed 100 test chats—still not ready to run the business — djgoel123 · 2026-11-02
- Agent given total creative freedom produces a 1:44 code-drawn animated short film — ivegotnoidea1 · 2026-11-02