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All digests tagged User Experience (UX)
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Building internal tools with AI agents requires more than just prompting. Achieving a polished, usable product demands implementing advanced patterns like optimistic updates, autosave, and rigorous end-to-end verification.
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Building a Voice OS requires moving beyond accurate ASR to mastering latency, personalization, and style inference. The talk details using LLMs and RL to structure raw speech into polished, usable communication.
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As AI agents level the implementation playing field, the differentiator becomes building the right thing. Learn to use Jobs to be Done and the Kano Model to guide product judgment and technical architecture.
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As AI agents commoditize implementation, the most valuable skill for engineers is Product Engineering: the ability to define the 'right thing' to build. This requires connecting customer needs to technical constraints, focusing on the smallest useful slice of the system.
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Improving voice AI requires optimizing system behavior under uncertainty, not just accuracy. By minimizing the Outcome User Cost Heuristic (OUCH), developers can significantly boost UX even if the core recognition accuracy remains constant.
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Voice AI failures are not random bugs, but structural issues. Kim introduces a linguistic framework mapping communication to two channels (listening/speaking) and four interdependent levels: sounds, words, interaction, and mental model.
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