We’ve entered a new phase in the evolution of intelligent systems. Unlike the earlier days of AI, where the focus was on automating well-defined tasks, today’s systems are increasingly context-aware, adaptive, and capable of emergent behaviour. These “agents” don’t merely execute rigid scripts; they reason, collaborate, and continuously learn from their environments.
This shift is more than an incremental tweak to traditional user experience. We can’t simply wrap a typical UI around these things and expect them to work. Instead, agentic design calls for rethinking how we build AI systems to solve real problems, multiply efficiency, and act with authenticity and purpose.
To help navigate this transformation, I’ve put together a high-level framework focused on four foundational components:
Context - What does it know?
Intent - What does it want?
Tools - What can it do?
Experience - How can I interact with it?
Each of these plays a critical role in shaping how agents understand and act in the world, and together they form a cohesive strategy for designing meaningful AI experiences.
1. Context
Context is the agent’s evolving understanding of its environment. It includes the current state of the world, as well as the steps taken and decisions made to arrive here. Effective context provides an agent with the lens through which it perceives and interprets information.
Imagine a diligent employee stepping into a new role. To perform effectively, they need to understand their specific job description and task areas, but also situate themselves within their broader workplace, industry, and culture. Context, in this sense, is not static—it’s a continuously updated synthesis of relevant information.
For agents, maintaining robust context is essential for adapting to changes and making informed decisions. For example, an agent reporting on customer product sales history must know everything about the customers, the products, and the sales history. It must be able to adjust its behaviour to reflect recent changes, such as new products, new prices, a new advertising campaign or a new competitor.
Context enables the agent to see patterns, anticipate needs, and provide recommendations that feel intuitive. The ability to connect past, present, and possible futures is what sets intelligent agents apart from static tools.
Managing this context poses challenges. Scale is a significant hurdle—agents must process vast amounts of data without causing information overload. Balancing granularity and relevance is equally critical. How do you ensure an agent retrieves the right piece of context without wasting time or resources?
Ultimately, without a dynamic understanding of constantly evolving context, agents cannot act intelligently or provide meaningful support.
2. Intent
If context is the foundation, intent is the blueprint guiding the agent’s immediate actions. Intent bridges the gap between what the agent knows and what it needs to do. It’s akin to giving an employee a clear, concise project brief. Without intent, even the most well-informed agent will struggle to act purposefully.
Intent reflects the alignment of the agent’s efforts with the user’s broader goals. For instance, when a user asks for help drafting an email, the agent must determine its purpose—is it to persuade, apologise for a mistake, or provide critical information? The agent must connect this immediate action to the larger context: how this email contributes to the relationship between the user and the recipient, and how that relationship in turn fits into broader organisation objectives.
Establishing intent is inherently collaborative. A well-designed agent doesn’t make assumptions—it engages in dialogue to clarify and refine its understanding. For example, if an agent is uncertain about the tone or specifics of a request, it should ask follow-up questions: “Is this a formal email, or should it feel more personal?” Seeking confirmation builds trust and ensures alignment with user expectations.
Intent is also dynamic. As new information becomes available or circumstances change, the agent must reassess its goals and adjust its actions accordingly. In fast-moving environments, where priorities shift rapidly, this flexibility is critical. An agent coordinating a complex project across teams must continuously check in with users and refine its understanding of intent.
Effective design treats the agent as a proactive collaborator. It should anticipate potential challenges, flag inconsistencies, and suggest solutions—all while keeping the user in the loop.
3. Tools
Tools are the agent’s means of execution—the resources it draws upon to achieve its goals. These include APIs, databases, specialised functions, and even other agents. Think of tools as an employee’s equipment, training, and network of contacts. They represent what the agent can access and leverage to get the job done.
The breadth of tools available to an agent defines its capabilities, while the depth of integration ensures its effectiveness. For instance, an agent assisting with research might pull from multiple databases, synthesise results, and present a concise summary. An agent tasked with event planning could use a mapping API to suggest venues, a pricing tool to calculate costs, and a communication tool to send invitations, managing dependencies across tasks.
Effective use of tools requires careful consideration of accessibility and latency. An agent must know what tools are available and understand their limitations. For example, agents using third-party APIs should anticipate rate limits or downtime and handle errors gracefully. Minimising latency ensures responsiveness, keeping user interactions smooth.
Ultimately, tools are the enablers of action. They transform intent into results, bridging the gap between what the agent knows and what it can do. Equipping agents with robust, well-integrated tools creates systems that are adaptable, efficient, and innovative.
4. Experience
Experience is where all the other components come together. It’s the interface between the agent and the user, shaping how the agent communicates its understanding, actions, and results. This is more than just designing a clean UI—it’s about fostering trust and clarity in the relationship between humans and AI.
Traditional UX principles often fall short in agentic systems. Unlike static tools, agents operate in open-ended environments where the input space is infinite and outcomes are not always predictable. This calls for a different approach, one that acknowledges the need for flexibility, adaptability, and transparency.
The interface is no longer a fixed menu of options or static displays of information—it’s a dynamic interplay between the agent and the user. The agent must actively demonstrate understanding, communicate reasoning, and engage the user meaningfully. This will involve new metaphors for interaction, such as dynamic forms, contextual tooltips or conversational overlays that adapt to the user’s needs.
User trust is paramount. Agents should explain their actions, provide opportunities for correction and confirmation, and offer visibility into decision-making. For example, instead of presenting a result, the agent could highlight the steps it took to arrive there, fostering confidence and collaboration. While speed is always desirable, the goal is smooth and intuitive interactions. Progress indicators, intermediate feedback, and incremental results make even complex processes feel responsive and manageable.
The new paradigm of agentic experience design challenges us to think holistically about the relationship between users and AI. It’s not just about solving problems—it’s about creating systems that enhance understanding and inspire trust through thoughtful, adaptive interaction.
Conclusion
The CITE framework—Context, Intent, Tools, and Engagement—offers a roadmap for designing agents that are adaptive, purposeful, and user-centric.
As we move forward, the potential for agentic systems to revolutionise industries and amplify human potential is enormous. Realizing this vision requires careful thought, experimentation, and a willingness to rethink traditional design paradigms.
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