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As agents stack dialogue turns, observations, and tool outputs into a finite context window, they can hit a 'dumb zone' where model quality drops because the growing context overwhelms capacity and leads to hallucinations or degraded reasoning before the window fully fills.
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See all →Context engineering keeps agents on-rail by selectively feeding, sequencing, and pruning the most relevant information so the model gets the right facts at the right time and avoids overload or confusion.
Designing robots for home use demands choices beyond dexterous hands—lighter mass, back-drivable joints, and washable materials—because lighter bodies reduce injury risk, force transparency enables safe interactions, and waterproof surfaces prevent cross-task contamination.