Experience Design for MULTI-AGENT AI Systems
Multi-Agent Orchestration & Accessibility Frameworks
Go from designing screens to architecting systems, learn the skills that will define the next decade of design
For UX / Product Designers, Service Designers, AI Product Managers, and Accessibility Specialists
This framework teaches experience design for multi-agent systems, not platform engineering. Engineers build the systems. You architect the human-AI experience.
Technical frameworks (LangGraph, AutoGen) handle implementation. This framework handles orchestration design, accessibility, and human-AI experience.
The Industry Is Shifting. Most Designers Will Miss It.
WHAT MOST DESIGNERS ARE DOING:
This approach will become obsolete.
WHERE THE INDUSTRY IS GOING:
This is what you need to learn NOW.
If you've heard terms like "agentic commerce," "machine customers," or "multi-agent orchestration"
You already know where the industry is headed. This framework gets you there before your competition.
The Challenges of Agentic Systems
Multi-agent systems introduce challenges that traditional websites, app, and single chatbots never had.
How do multiple agents coordinate?
As a UX Designer: You can't design the frontstage experience (what the users see) without understanding backstage orchestration. Visual design alone isn't enough anymore.
As an AI Product Manager: You can't spec the project without knowing which orchestration pattern to use and where human control is needed.
How do I make multi-agent systems accessible?
As an Accessibility Specialist: Screen readers break between agents. Keyboard navigation fails at handoffs. You can't audit a system you don't understand, and WCAG doesn't cover agent coordination.
How do I handle high-risk actions (commit phase)?
When agents book appointments, process payments, or perform irreversible actions - risk explodes. You need commit-phase safety patterns: approval gates, audit trails, and rollback strategies.
What about agentic commerce and machine customers?
AI agents buying or negotiating with other AI agents on behalf of humans is coming fast. You need trust frameworks, verification patterns, and coordination design that doesn't exist in traditional UX.
What you’ll Learn
8 comprehensive modules teaching multi-agent orchestration, the agentic lifecycle model, accessibility frameworks, and system architecture, from first principles to advanced implementation. Figma diagrams and design solution examples included.
MODULE 1
The Mental Model
The Agentic Lifecycle: Intent → Discovery → Evaluation → Commit → Fulfilment → Support
MODULE 2
Core Foundations
Stable vocabulary for understanding multi-agent coordination
MODULE 3
20 Orchestration Patterns
Each pattern includes lifecycle considerations, accessibility requirements, failure modes, and real-world examples
MODULE 4
Failure Modes & Recovery
What goes wrong and how to fix it
MODULE 5
Accessibility for Multi-Agent Systems
Where your competitors fail, making orchestration accessible
MODULE 6
Templates & Frameworks
Practical tools for implementation
MODULE 7
Real-World Examples
Complete lifecycle slices with full documentation
MODULE 8
Testing & Auditing
Verify systems work safely and accountably
This Isn't Just UX. It's Systems Architecture.
Multi-agent orchestration requires synthesizing multiple disciplines - UX design, service design, systems thinking, distributed systems architecture, accessibility frameworks, and product strategy. This framework teaches you to think like an architect, not just a screen designer.
The Shift: Screen-First → System-First
Traditional UX focuses on what users see. Multi-agent orchestration focuses on what happens behind the scenes - how agents coordinate, where human control is needed, and how systems fail gracefully. This framework teaches both.
Tools like vibe coding accelerate execution, but they don’t solve orchestration, accessibility, or commit-phase risk. This framework defines the system-level decisions that must come first.
What You'll Be Able to Do
You'll go from "I design chatbot UIs" to "I architect multi-agent systems."
That's the difference between staying relevant and getting left behind.
WITH This Framework:
WITHOUT This Framework:
What you’ll Get
Complete Framework
8 modules (150-200 pages)
20 orchestration patterns
Agentic lifecycle model
Accessibility frameworks
Commit-phase safety
Real-world examples
Design Resources
140 Figma templates
Pattern flowcharts
Decision trees
Service blueprints
Orchestration diagrams
Component library
Working Tools
Notion workspace template
Airtable orchestration planner
Test scenario library (50+)
Accessibility checklist
Audit framework
Pattern selector
Everything you need to architect accessible multi-agent systems professionally.
Lifetime access • All updates for 12 months • Email support
What Suits You Best
Who Should Learn This
Perfect Fit if You're:
Not for You if:
Meet Your Tutor
Gabriela-Aurora Statie
15+ years designing UX in regulated industries (healthcare, cybersecurity, gaming) where accessibility and accountability are mandatory.
When I started researching multi-agent AI systems, no frameworks existed for orchestration patterns, commit-phase safety, or accessibility across agent handoffs. Everyone teaching "AI UX" focused on chatbot flows, useless for architecting systems with multiple coordinating agents.
I synthesized Microsoft's HAX Guidelines, Nielsen's Heuristics for AI, WCAG standards, Google's Conversational Design Framework, and service design principles into practical orchestration patterns. This framework is the result, applied patterns for practitioners architecting accessible AI systems where mistakes have real consequences.
Background: Computer Science degree
Certifications: Service Design (UAL), IAAP CPACC (March 2026), IAAP WAS (December 2026)
Expertise: Multi-agent orchestration, accessibility frameworks for AI, commit-phase safety, service design for distributed systems.
Frequently Asked Questions
No. If you understand basic UX principles and are willing to think at a systems level, this framework will accelerate your career. The designers who learn orchestration now will be the senior architects in 2-3 years. The ones who wait will be playing catch-up.
Yes. This framework complements the technical infrastructure you're already using (LangGraph, AutoGen, CrewAI). While those frameworks show you HOW to wire agents together technically, this framework helps you understand WHICH orchestration patterns to use, WHEN to apply them, and HOW to design for accessibility and user experience.
Think of it as the design layer that sits above your technical stack. It helps you make better architectural decisions about agent coordination, human-in-the-loop placement, and commit-phase safety before you write code.
Many engineers find this framework valuable for understanding the "why" behind design/product decisions and for collaborating more effectively with UX teams.
No. This framework is intentionally not about vibe coding, prompt engineering, or AI implementation workflows.
Vibe coding helps teams generate code faster AFTER decisions have been made. It does not define:
- how multiple agents should coordinate
- where human approval is required
- how accessibility survives agent handoffs
- how to design safe commit-phase behavior
This framework teaches experience architecture for multi-agent systems — the mental models, orchestration patterns, accessibility requirements, and risk controls that must exist before any code (manual or AI-generated) is written.
Many designers use vibe coding tools after applying this framework to prototype and test orchestration decisions. Without this foundation, vibe coding simply accelerates poorly designed systems.
The best time to learn this was 6 months ago. The second best time is now. By the time your company assigns you a multi-agent project, your colleagues who learned early will be leading while you're catching up. Get ahead while the industry is still transitioning.
You're right. Most current job postings are for AI engineers, not designers. That's because companies are in the "build fast" phase, deploying multi-agent systems without proper design frameworks. Right now, those systems are messy: users get confused by agent handoffs, accessibility fails at coordination points, and commit-phase safety is an afterthought.
Within 12-18 months, companies will realize they need designers who understand orchestration, just like they needed mobile UX designers after the iPhone launched, or accessibility specialists after WCAG became mandatory. Microsoft, Google, Salesforce, and Amazon are already shipping multi-agent platforms (Copilot, Agentspace, Agentforce).
The design roles will follow once companies feel the pain of poorly-designed coordination. Learn this now, and you'll be the expert they're desperately searching for when job titles catch up to reality. Early adopters win.
Most chatbot courses focus on designing single-agent conversation flows. Many current AI UX courses go further in the wrong direction - optimizing for tools, auto-generated UIs, or speeding up visual design production.
This framework teaches multi-agent orchestration: how 3–10 agents coordinate, share and hand off context, recover from failure -and how you expose that complexity to users without overwhelming them. In multi-agent systems, you can’t jump straight into screens or flows - the architecture is the HAX (Human–AI Experience).
It’s the difference between designing a button, automating mockups, and architecting a distributed system where behavior, coordination, and trust must be mapped before pixels do.
Engineers can absolutely wire agents together technically (using LangGraph, AutoGen, etc.), but multi-agent orchestration requires design decisions that sit outside engineering expertise. Which orchestration pattern best serves user needs? Where should human approval be required? How do we design agent handoffs for screen reader users? What level of transparency do different user groups need?
These are judgment calls rooted in service design, user research, accessibility frameworks, and contextual understanding of human behavior, not technical implementation. Engineers have the skills to BUILD the coordination; designers now have the framework to DESIGN the coordination. Both are essential.
History shows this pattern: In the early 2000s, engineers built technically functional websites that were unusable until designers applied IA principles. In 2010, engineers built mobile apps that worked but had terrible UX until mobile design patterns emerged. In 2016, engineers deployed chatbots that frustrated users until conversational design frameworks matured. Every time, companies realized technical capability ≠ good user experience.
Engineers optimize for technical efficiency and system performance. Designers optimize for human experience and accessibility. This framework teaches the design layer that complements technical implementation, helping teams make better orchestration decisions before writing code.
Even if AI automates interface generation, someone still needs to make design decisions: where human approval is required, how much transparency users need, and how to design for accessibility across diverse abilities. These aren’t technical problems, they’re judgment calls rooted in empathy, ethics, and understanding human needs.
AI can generate interfaces, but it can’t determine what’s appropriate for a specific context, how much control users should have, or how to balance automation with human agency. That requires understanding people, not just optimizing pattern.
If you think AI should make all decisions with no human oversight, this framework isn’t for you. If you understand that humans experience AI systems, and someone must advocate for them with empathy and accountability, this framework is essential.
Advocacy doesn’t get automated away. Judgment, ethics, accountability, and meaning won’t disappear. They’ll become even more important in the agentic era.
Even in an AI-automated world, someone still needs to design the human experience. That’s what this framework teaches.
No, but systems thinking helps. If you can understand service design (frontstage/backstage), accessibility and UX principles, you can learn this. The framework translates technical concepts (distributed systems, coordination patterns) into design language with visual examples.
They will be. Agentic systems are emerging fast. Companies that aren't thinking about this now will be in 6-12 months. You'll be the expert they need when they realize they're behind.
You can apply patterns immediately (Module 2). Deep mastery takes 3-6 months of practice. Most practitioners spend 10-15 hours learning the framework, then reference it continuously while building real systems or concept-portfolio work.
Yes. 30-day money-back guarantee. If the framework doesn't give you the orchestration patterns and system architecture knowledge you need, email for a full refund. No questions asked.
The framework includes email support for questions. For ongoing community learning, monthly projects, and live feedback, join the Agentic Design Community (separate, £49/month).
Team licenses (3-5 people) save 60% and include shared resources. Enterprise (6+ people) includes custom training sessions. Email [email protected] for team pricing.