The next leap in agent performance may not come from bigger models—it...

The biggest shift in AI right now isn’t just scale. It’s where the memory lives. More teams are seeing better results when candidate options, evidence trails, verification notes, and compact context are handled by the surrounding system—not left to the model alone. That design choice can make long workflows more reliable, easier to audit, and far less likely to lose momentum as tasks get complex. For leaders, the upside is practical: stronger enterprise search, better research workflows, and automation that’s easier to trust and reuse across teams. If the right context could be preserved outside the model, what would your team build differently?

How would your team change its search, research, or automation strategy if context could persist outside the model?

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