Google Scientist on Long-Horizon Agents: Balancing Context vs. Scaffolding
AnneliesGamble · x · 2026-08-26
Google DeepMind Distinguished Scientist Prateek Jain discusses two high-level strategies for enabling AI agents to tackle complex, long-horizon tasks: expanding the context window to hold more of the problem in mind, or building external scaffolding (retrieval, memory, planning, tools, sub-agents) to reduce the burden on the model. The interview explores finding the right balance between these approaches.
Related event: DeepMind Scientist on Long-Horizon Agents: Context vs Scaffolding(2 posts)→
More from coding & agent
- Fix Hermes Agent Install Error with PowerShell One-Liner to Skip CUA — Teknium · 2026-08-26
- Dev Trick: Using shadcn's `improve` Skill for Task Planning — shadcn · 2026-08-26
- Agents lower product building barrier, distribution is the moat — paw_lean · 2026-08-26
- Maya: Open Source Mac App Wraps Screen Recordings in Device Frames — tom_doerr · 2026-08-26
- Agentmuxer Launches: The OpenRouter for Agent Capabilities — garrytan · 2026-08-26
- Interactive Lyrics Visualizer Built with AI Assistance — stuffyokodraws · 2026-08-26