underscored

@underscored

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Tag:human-computer-interactionClear

Latency is a product problem, not merely a model problem. Opus 5.5 produced solid work, but parallel tasks routinely took more than 10 minutes with little visible feedback. Claire's experience suggests that a faster agent with slightly weaker output may feel more useful than a smarter one that disappears while working.

— Claire Vo
1w ago

The key thing to understand about agents is that they are not just AI: they are an AI that has access to a computer. It was clear very early on in the ChatGPT era that AI would not replace computers, but rather operate them.

1mo ago

Rather than simply dictate instructions, or follow a turn-based conversation with a voice agent, Wispr envisions a more collaborative workflow, in which the interface is continuously learning from your recent actions, following what you're doing on the screen using computer vision, and learning about you enough to understand nuanced instructions, while suggesting and running others behind the scenes.

3mo ago

traditional AI models function sequentially—listening and then responding—whereas its new model aims for simultaneous input processing and response generation, akin to a phone call.

5mo ago

The chatbot interface appeared to be the obstacle, not the work. And once a conversation got messy, it stayed messy. The AI, optimized to be helpful, just mirrored back whatever disorganized structure the user provided while the user, overwhelmed, didn't reorganize.

6mo ago

Until now, working with AI has been copy-paste. You take information from one app, paste it into ChatGPT or Claude, get a result, then manually move that result into another app. You're the middleman between AI and the tools you use in your work. Plugins remove you from that role.

7mo ago

Underscored — save the words that stop you in your tracks.

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