Shivansh Inamdar, who develops AI and manipulation software for autonomous warehouse robots at Nimble Robotics, shares insights on building more robust software systems. He emphasizes designing for failure, as even rare bugs become common at the scale of hundreds of robots handling thousands of items daily. Inamdar also highlights the critical need for built-in observability, as debugging real-world robotic failures is impossible without detailed logs of sensor data, decisions, and reasoning pathways. AI
IMPACT Lessons from robotics software development can improve the robustness of any software system, including AI applications.
RANK_REASON Author shares personal insights and lessons learned from their work, rather than announcing a new product, research, or significant industry event.
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