I needed to understand how and why use background agents. This video helped me understand it better
_(Photo by Haberdoedas II on Unsplash)_
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Related:
State machines to visualize the work of agents — using state machines to make LLM agent behavior more deterministic and visible, directly relevant to making background agents predictable
Agents and State Machines — formal state machine model for Pi-sdk-based agents (Lamport + Kay style), giving background agents a rigorous theoretical foundation
State Machines — Knowledge Map — hub page collecting all state-machine/agent documents across the repository
Vibe code like a PRO — proposes extending background agents into a Linear-to-PR pipeline: fetch issues, expand with codebase context, spawn agents, create PRs
Agents — Seed Hypermedia's agent architecture: agent specifications, sessions, completions, and triggers — the formal framework for building the background agents Cursor popularized
Product Backlog — Opportunity 26: Linear-to-Agent Pipeline CLI — the formal roadmap for packaging background agents into a CLI: fetch Linear issues, expand with codebase context, spawn agents, create PRs
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