AI agent design built so people trust it
The experience layer of an AI agent: how it presents itself, how it communicates uncertainty, how it escalates to a human and how it makes clear what it is doing at all times.
The problem we solve.
An agent that technically works but scares or confuses users fails just like one that doesn't work. The difference between a useful agent and one that gets switched off usually lies in the experience design, not the underlying model.
We design how the agent presents itself, how it manages uncertainty, how it asks for confirmation, how it escalates to a human when needed and how it communicates progress so the user feels in control instead of navigating blind.
What is included
- Agent-user interaction patterns adapted to your case (chat, embedded, autonomous)
- Design of uncertainty and error communication
- Human escalation flows that preserve context
- Progress indicators, intermediate states and "what the agent is doing" signals
- Microcopy and agent voice aligned with the brand
Our process for AI agent design.
Audit
We review the current agent flows or the sketches of the one you want to build and detect the critical UX points.
Design
Interaction patterns, microcopy, error handling and documented fallback flows.
Validation
Tests with real users on prototype or pre-release product before full deployment.
Difference from the "AI Agents" service in the consulting pillar
The "AI Agents" service in the main pillar covers the complete technical architecture: agent design, system integration, evals, deployment. This service focuses specifically on the agent's experience layer. It makes sense when the agent already exists (or another team is building it) and the friction is in how it presents itself to users, not in how it reasons internally.
Other services within AI-native experiences
AI product strategy
How to integrate AI into your existing product or build a new one with AI at the centre.
View service →Functional AI prototyping
Functional prototypes connected to real LLMs to validate use cases in days, not months.
View service →Context engineering
Designing the context that feeds the models: prompts, tools, memory, RAG and usage policies.
View service →Generative UI
Interfaces built on the fly based on user intent and the available context.
View service →Multimodal UX
Experiences that combine text, voice, image and video naturally within the same flow.
View service →