# A Training Paradigm Tries to Make LLM Agents Plan Ahead Instead of React

The proposed method internalizes a world model so agents can evaluate hypothetical futures during long-horizon tasks.

- Published: 2026-06-29T10:45:14.906Z
- Canonical: https://polylog.news/ai/2026-06-29/a-training-paradigm-tries-to-make-llm-agents-plan-ahead-inst
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [arXiv (cs.AI)](https://arxiv.org/abs/2606.27483)

A paper called Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning addresses a known weakness of language-model agents. They are strong at sequential decision-making but remain fundamentally reactive over…

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