Tagged articles

runtime state management

4 articles · Page 1 of 1

Oct 26, 2026 · Artificial Intelligence

Codex Retrospective: From 30-Second Feedback to Hour-Long Autonomous Runs

The Codex team's retrospective reveals how AI coding agents evolved from requiring human feedback every 30 seconds to running autonomously for hours, shifting feedback from granular actions to high-level events like permission boundaries and acceptance criteria, enabled by a persistent runtime that preserves goals and state across sessions.

AI coding agentsCodexOpenAI

0 likes · 17 min read

Codex Retrospective: From 30-Second Feedback to Hour-Long Autonomous Runs

DataFunSummit

Sep 11, 2026 · Artificial Intelligence

Graph Engineering Restructures Agent Systems: From Harness to Ontology

This article reviews a 2026 paper on Graph Engineering for LLM agents, detailing the shift from individual agent intelligence to system intelligence via explicit task DAGs, runtime state management with checkpoints and replay, multi-agent coordination through capability modeling, and ontology engineering for shared semantics.

Agent CoordinationDAG SchedulingGraph Engineering

0 likes · 20 min read

Graph Engineering Restructures Agent Systems: From Harness to Ontology

DataFunTalk

Sep 9, 2026 · Artificial Intelligence

Graph Engineering Restructures Agent Systems: From Harness to Ontology

A 2026 survey paper introduces Graph Engineering as the next phase for LLM agents, shifting focus from individual model capabilities to system-level organization via explicit task DAGs, runtime state management with provenance and recovery, capability-based agent coordination, and a graph-native control plane that treats tasks, agents, and state as first-class system objects.

Agent CoordinationDAG SchedulingGraph Engineering

0 likes · 22 min read

DataFunTalk

Sep 7, 2026 · Artificial Intelligence

Graph Engineering Rebuilds Agent Systems: From Harness to System Intelligence

A 2026 survey paper introduces Graph Engineering as the system layer that organizes LLM agents into reliable multi-agent workflows through explicit DAGs, runtime state management, fault tolerance, and a control plane, shifting focus from individual agent capabilities to system-level engineering.

Agent CoordinationDAG SchedulingGraph Engineering

0 likes · 21 min read

Graph Engineering Rebuilds Agent Systems: From Harness to System Intelligence