Lesson 4.3 – User Interface Selection for AI Agents

🎯 Learning Objectives

By the end of this lesson, you will be able to:

• Understand the different ways users can interact with AI Agents

• Choose the right Human User Interface (HUI) for your use case

• Determine when to use chat, SMS, email, apps, or APIs

• Align interface design with your workflows, personas, and expectations

• Plan your UI/UX architecture before training or workflow buildout begins

🧠 Why Interface Design is Strategic (Not Cosmetic)

Too often, interface decisions are made after an AI Agent is built. This is backward.

Your interface is the Agent’s body—it shapes how people will:

• Trust it

• Use it

• Rely on it

• Evaluate its usefulness

In a human workforce, we expect people to speak, write, listen, and present in different ways depending on the context. AI Agents are no different—they can operate through multiple channels, and each has pros, limitations, and design considerations.

🧑‍💼 Welcome to the HUI Era: Human User Interfaces

We call this new category HUI (Human User Interface)—the surface where humans and agents meet.

Your AI may live in:

Each one serves a different mode of interaction, and in many cases, your agent will need to use multiple HUIs to be effective—just like a human uses chat, email, or voice depending on context.

🔍 Deep Dive: Available Interfaces

💬 Live Chat

“Let’s embed an AI Agent on the site.”

• Quick to set up and deploy

• Best for top-of-funnel sales, FAQs, basic support

• Works great with raia’s out-of-the-box widget

• Limitations in formatting or complex conversations

Design Tip: Ensure fallback options exist (e.g., escalate to human)

🧠 raia Copilot

“Let’s give employees a super-assistant.”

• Internal Copilot that provides deep knowledge, actions, or analysis

• Use for troubleshooting, searching vector knowledge, triggering workflows

• Supports structured prompts and reasoning chains

• Best for internal use or agent monitoring/testing

Design Tip: Use this to test your Agent’s reasoning before launch

📱 SMS

“Let’s notify or gather quick responses via text.”

• 2-way asynchronous communication

• Great for appointment reminders, check-ins, or gathering data

• Low-friction, high-response for B2C workflows

• Limited formatting and session persistence

Design Tip: Keep messages short and provide an exit path (e.g., “reply STOP”)

📧 Email

“Let’s automate structured or formal messages.”

• Can be both inbound and outbound

• Ideal for order updates, NPS surveys, onboarding journeys

• Can include attachments, threads, formatted content

• Slower turnaround, but higher trust

Design Tip: Use email for high-confidence outputs (e.g., summaries, decisions)

🔌 API

“Let’s have other systems talk to the Agent.”

• Programmatic interface for automation

• Connects with CRMs, ERPs, apps, or workflows

• Enables building logic-heavy, data-rich applications

• Requires authentication, versioning, and monitoring

Design Tip: Use API if Agent is a service in a broader automation flow

🧱 Custom UX / AI-Powered Applications

“Let’s build a full app where AI powers the experience.”

Sometimes, a conversational interface isn't enough. You need:

• Form inputs

• Interactive dashboards

• Embedded workflows

• Role-based access

This is where custom apps, built using AI Coding Agents (like Lovable or Cursor), come in.

You can:

• Build the UI with AI-powered coding agents

• Connect to raia platform via API or function call

• Use n8n workflows to power business logic

Design Tip: Use this when conversation isn’t enough—or when structured data is needed alongside smart reasoning.

📘 Supported by guidance in [Module 4 – Interface Configuration] and the [Training Manual].

🗺 Interface Planning Worksheet

Before you train your Agent, fill this out:

👁 UX Design Tips for AI-Powered Interfaces

• Start simple: Begin with chat/Copilot, evolve toward apps if needed

• Maintain consistency: Users shouldn’t feel like they’re switching agents across interfaces

• Enable context switching: From chat → email → SMS → app, the Agent should remember the user’s journey

• Design for trust: Always allow human escalation, explanations, and transparency

• Keep users informed: When an agent is acting on their behalf, notify and confirm

✅ Key Takeaways

• Interface design is not about technology—it’s about user expectations

• Choose your Human User Interface (HUI) based on use case, user, and context

• You can (and should) combine interfaces when needed

• Design for clarity, escalation, and feedback

• Start with interface planning before you finalize training data or workflow logic