Google Proposes Procedural Graphs to Steer Long-Horizon AI Agents

Google's new Procedural Graphs framework organizes agent actions into structured, self-evolving execution topologies, addressing long-horizon failures like goal drift and out-of-order tool calls. Community authors also outlined a six-step roadmap for building self-improving agents on this idea.

2026-09-09 ~ 2026-09-10 · 3 related posts

• Google proposes Procedural Graphs, self-evolving execution structures for LLM agents — google · 2026-09-09
• Google paper proposes Procedural Graphs to make long-horizon agents' procedural knowledge explicit — omarsar0 · 2026-09-10
• A 6-step roadmap: self-evolving AI agents with procedural graphs — MaryamMiradi · 2026-09-10