UX-NATIVE AI: Design the AI products people actually trust, and become the one who knows how while everyone else is bolting a chat box onto the side
UX-NATIVE AI: Design the AI products people actually trust, and become the one who knows how while everyone else is bolting a chat box onto the side - Image 2

UX-NATIVE AI: Design the AI products people actually trust, and become the one who knows how while everyone else is bolting a chat box onto the side

$ 150.838,00

This guide shows you why gluing a chat window on top of an existing app fails by construction, and how to redesign software from first principles around the user’s intent instead of navigation. You’ll see how to collapse a 700-parameter admin panel into natural-language control without losing precision, how to move from drawing screens to designing the decision checkpoints where the user reviews and corrects the plan before it executes, and how to decide when the AI should merely suggest, when it should ask permission, and when it should run on its own. The strategy isn’t a list of trends; it’s the order in which you make each design decision once software stops being navigable: how intent is expressed and resolved, how to show what the AI is doing without overwhelming anyone, how to design trust when the system acts on the user’s behalf, and what remains when the menus, the forms and the dashboards disappear. Every chapter attacks the exact point where a product with AI bolted on feels broken, and leaves you with the design decision already made instead of the problem left open. For people who build product and need to break out of the chatbox prison.

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Description

Look at the last AI feature your team shipped: a chat window bolted onto the side of the app, floating next to the same menus and forms as before. It feels wrong, and it is wrong. You have jammed a probabilistic, autonomous engine into a rigid, deterministic box, so the user ping-pongs between clicking strict menus and typing free-form prompts, and nobody can see what the AI is doing or decide whether to trust it. The chat panel is not an interaction model, it is a patch admitting you do not have one. What is missing is a way to design software that is AI-native from the interface down, not the old app with a text box stapled to the edge.

This guide shows you why gluing a chat window on top of an existing app fails by construction, and how to redesign software from first principles around the user’s intent instead of navigation. You’ll see how to collapse a 700-parameter admin panel into natural-language control without losing precision, how to move from drawing screens to designing the decision checkpoints where the user reviews and corrects the plan before it executes, and how to decide when the AI should merely suggest, when it should ask permission, and when it should run on its own. The strategy isn’t a list of trends; it’s the order in which you make each design decision once software stops being navigable: how intent is expressed and resolved, how to show what the AI is doing without overwhelming anyone, how to design trust when the system acts on the user’s behalf, and what remains when the menus, the forms and the dashboards disappear. Every chapter attacks the exact point where a product with AI bolted on feels broken, and leaves you with the design decision already made instead of the problem left open. For people who build product and need to break out of the chatbox prison.

Is this book for you?

This guide is for: engineers and product designers who already shipped software with menus, forms and dashboards, and are now bolting AI on top of it (a chat panel off to the side) and can feel that it came out clumsy and disconnected, without knowing why or what to design instead.

What you’ll get inside

  • Chapter 1: Introduction: the chat box bolted onto the wall, and the feeling nobody can name
  • Chapter 2: The forty clicks that were never the point
  • Chapter 3: Why “powerful” software needs a $2,000 training course
  • Chapter 4: What the user typed is only 5% of what they meant
  • Chapter 5: A single Execute button is a coin toss
  • Chapter 6: Three tasks before lunch, none want the same interface
  • Chapter 7: Between the silent black box and the firehose
  • Chapter 8: The morning the AI skipped “are you sure?”
  • Chapter 9: Take EU down to 80% without learning where the knob lives
  • Chapter 10: The AI did the thinking and handed you the typing
  • Chapter 11: The one-word reply that makes users verify everything
  • Chapter 12: It failed four steps in. What state is everything in now?
  • Chapter 13: The assistant with the memory of a goldfish
  • Chapter 14: The model is the least important part of your AI product
  • Chapter 15: From drawing screens to designing the rules that draw them

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