Your interface isn’t just a delivery mechanism. It’s how your product expresses intelligence. And how users experience it. Every AI product begins with a fundamental decision: how do you want humans to interact with the machine?
The moment a team decides to “add AI” to a product, the next question is almost always: what should the UI look like? Too often, the answer is: let’s add a chatbot.
But AI is not a feature — it’s a new paradigm for interaction. Chat is only one form of that paradigm, and while popular, it’s not always effective. If your user is trying to get something done, explore ideas, or delegate tasks, the interaction model should match the nature of the intelligence — and the intent behind the task.
This section gives you a shared language to define the primary interaction models of AI-native products — chat, tool, and agent — and shows how to use them intentionally, or in combination, to create clarity and flow.
Why this section matters
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Model
Description
Best For
Caution
Chat
Natural language exchange with generative or responsive capabilities
Exploration, idea generation, Q&A, customer support
Risk of verbosity, ambiguous boundaries, unclear capabilities
Tool
Structured input/output mechanisms like sliders, dropdowns, buttons, modals
Editing, filtering, transforming, navigating
Too rigid for exploratory tasks
Agent
Task-executing entities that act on user behalf, often semi-autonomous
Automating tasks, managing workflows, continuous monitoring
Overstepping, lack of user awareness, low trust without transparency







