Agility Robotics CTO Melonee Wise talks with Audrow Nash about Digit’s warehouse work, humanoid robot design, labor and AI, and the path to broader uses.
Wise describes Agility as a mobile manipulation company focused on moving warehouse totes. She says Digit’s compact, balancing design helps it reach and handle loads in narrow aisles, where wheeled platforms can lose payload capacity to attachments or become less stable with high loads.
Wise says customers care about throughput over a full shift, and that Digit is at or slightly above human parity in the use cases where it is deployed, though Agility lacks enough data for broad comparisons. She connects warehouse automation to labor shortages and argues that workers need support to move into new roles. She describes current LLMs as useful for consolidating information, while noting that they can invent details and struggle with context.
Wise says Agility has demonstrated an LLM translating a complex instruction about a box’s color and a numbered podium into a behavior tree that uses Digit’s existing skills. She sees near-term value in letting customers describe workflows in ordinary language, then turning those instructions into repeatable robot behavior. For logistics, she says reliability and consistency matter more than having an LLM make fresh decisions each run.
Wise says Agility’s planned factory was under construction and designed for eventual production of up to 10,000 robots. She describes North American suppliers and says domestic manufacturing faces shortages of workers and dense supplier networks. Wise expects humanoids to spend roughly the next decade in industrial settings, with broader household use perhaps 20 to 30 years away; LLMs do not resolve the hardware and control challenges.
Wise says Digit uses simple, task-focused grippers and that high-dexterity hands are not yet needed for Agility’s target work. The company plans to expand from tote handling into stacking, boxes, and pallet tasks by combining reusable skills into customer workflows. Wise also stresses making robots easier to use and calls for more ways to share research on usability.
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