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Sequential Pipeline Agents(SPA)
Specialized agents process tasks in a linear pipeline where each agent's output becomes the next agent's input
In 30 seconds
- What
- Breaks work into ordered stages where each specialized agent processes output from the previous stage before passing results forward.
- When to use
- Multi-stage workflows where each phase needs different expertise and intermediate results benefit from validation before proceeding.
- Watch out
- Errors or poor quality at early stages compound downstream, wasting effort in later agents on flawed inputs.
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Sequential Pipeline Agents: Overview
Specialized agents process tasks in a linear pipeline where each agent's output becomes the next agent's input
- Linear workflow processing
- Specialized agent roles
- Output-input chaining
- Quality checkpoints
- Stage-specific optimization
- Error isolation
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Also known as: AI agent pipeline, Agentic pipeline, Agent execution pipeline
References
The papers, specifications, and repositories this pattern is based on.
- Multiagent Systems: A Survey from a Machine Learning Perspective (Stone & Veloso, 2000)
- Multiagent Cooperation and Competition with Deep Reinforcement Learning (Tampuu et al., 2017)arXiv:1511.08779
- The Complexity of Decentralized Control of Markov Decision Processes (Bernstein et al., 2002)
- A Review of Cooperative Multi-Agent Deep Reinforcement Learning (OroojlooyJadid & Hajinezhad, 2019)arXiv:1908.03963
- AutoGen - Multi-Agent Conversation Framework
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