The Age of Intent: From prototype to transformation

This article is the second in our Age of Intent series, exploring what it takes to move from building prototypes to transforming organizations for an intent-driven future.

What happens when we stop designing interfaces and start designing for human intent?

When I declared “the interface is dead,” it wasn’t a prediction of extinction — it was a call to evolution.

Today, as generative AI, multimodal agents, and adaptive interfaces reshape how people interact with technology, intent has emerged as the new interface. Users are no longer navigating screens — they’re expressing goals. And systems must now understand, reason and act on those goals in real time.

This moment matters because the shift is already underway. AI copilots interpret our requests inside productivity tools. Voice assistants and agentic systems now book appointments, draft proposals, and answer questions across ecosystems. The “Age of Intent” is no longer hypothetical — it’s operational.

Over the past weeks, I’ve explored what it actually takes to build for this new paradigm. The findings were clear: creating a prototype is effortless. Transforming your systems and organization to act on intent is anything but.

From prototype to complexity: why transformation is hard

To explore what an intent-first world might look like, we built a simple flight-booking prototype. Using dummy data and a lightweight Model Context Protocol (MCP) server in Python — a tool that enables a language model to connect with real data sources and functions — we wired it to a React UI. Within hours, we had a working conversational experience.

It was thrilling. A few lines of code, a quick API integration, and users could type natural language requests like “Show me flights from Sydney to Melbourne.”

And then the complexity began.

In a traditional web form, users fill in every field upfront — origin, destination, dates, passengers. A conversational interface doesn’t work that way. Users start with a goal (“I need to get to Melbourne”) and clarify details later (“on Tuesday,” “with two kids”). The system must handle ambiguity, remember context and update its understanding dynamically.

In our case, ChatGPT managed the contextual memory, recalling prior messages and prompting clarifications like “Did you mean next Tuesday or this Tuesday?” But what surprised us most wasn’t how the model handled conversation — it was how much that changed the interface.

We discovered that users still needed to see the journey holistically — both outbound and return legs — and to adjust details visually, just as they would in a traditional booking engine. The difference was that they did it with less data and fewer steps. Instead of listing dozens of prices, for example, the interface might show a daily timetable with an average or minimum fare, surfacing only what’s relevant to the intent.

In other words, designing for intent didn’t eliminate the UI — it reshaped it. The intelligence wasn’t just in the backend; it was in deciding what to reveal, when, and how to best support the user’s goal.

Redesigning interaction patterns for the age of intent

Conversational experiences challenge decades of interface design assumptions. For years, digital experiences have been about screens, forms, and clicks. Now, users express goals, not inputs — and the system must infer, reason, and orchestrate what comes next.

What’s striking is that conversational interfaces aren’t new: organizations have been building chatbots for years. But what’s changed is where these experiences now live.

Traditional chatbots existed inside an organization’s owned ecosystem — embedded within websites or mobile apps, bound to internal data sources. Today, intent-driven interactions increasingly happen outside those walls, in open ecosystems where AI assistants can connect and compose across multiple services.

When a user expresses an intent, eg “Find me a family home in Bondi Beach”,  that query no longer lives inside a single brand’s app. An agent can gather listings from multiple property sites, overlay public data on flood zones, schools and amenities, and present a synthesized view that shapes the user’s preference before they ever reach your site. These kinds of cross-source experiences show how intent is becoming the organizing principle of digital ecosystems — not just within a brand, but across them.

For organizations, that’s a profound shift: your brand is no longer just the destination of a search, but a participant in a shared intent ecosystem. Designing for this means thinking beyond your owned interfaces — ensuring your data, APIs, and brand context are discoverable, composable and trustworthy enough to be included in those external conversations.

Traditional APIs are rigid — they expect structured, complete input. Intent-first systems require APIs that can work with partial information, reason under uncertainty, and integrate contextual signals like calendars, travel history, or personal preferences.

We’re moving from responding to user actions to reasoning about user purpose. It’s a profound shift — one that turns designers into orchestrators of context and developers into modelers of meaning.

The infrastructure readiness gap

Through conversations with clients and internal teams, one thing became clear: while the tools for intent-based experiences exist, most organizations aren’t ready to use them.

Many still treat ChatGPT, copilots or voice assistants as novelty experiments rather than as new distribution channels. But once leaders see their brand represented conversationally — through an agent or prototype — they quickly grasp both the potential and the challenge.

To be discoverable in the age of intent means being visible and usable by these intermediaries. When a customer says, “Find me travel insurance,” or “Book me a plumber near me to fix my boiler,” the assistant, not the app, decides which business surfaces.

That means:

• Structuring data and APIs so that AI agents can interpret and act on them.

• Establishing brand tone and guardrails that travel across ecosystems.

• Ensuring your systems expose trustworthy, machine-readable information.

Without these foundations, your conversational experience will remain a demo — not a differentiator.

Broader transformations on the horizon

Intent-driven design won’t stop at travel.

• In banking and financial services, an assistant could understand “Help me get my spending under control” — pulling together budgets, alerts and behavioral insights across accounts, automatically suggesting savings or investment opportunities.

• In energy and utilities, a customer could say “Reduce my energy bill this month” — prompting the system to analyze usage patterns, recommend tariff changes or trigger smart-device adjustments in real time.

• In retail, a shopper might say “I need something to wear for an outdoor wedding” and the AI could understand context — location, season, budget — to recommend sustainable options, check local availability or suggest rentals.

• In public transport or mobility, a commuter could ask “What’s the fastest way to get to the airport with my luggage?” and receive a combined answer pulling from real-time transit, rideshare and parking data.

In each case, success depends not on prettier interfaces but on how intelligently systems can interpret and act on intent.

The unanswered question: value in an intent-driven world

As intent-driven systems mature, a deeper question emerges: where does value flow when interactions are mediated by AI?

When a customer’s request — “find me travel insurance” — is fulfilled by an assistant that chooses between multiple brands, who earns the recognition, the data or the margin? The interface once anchored brand identity and commerce. In an age of invisible interfaces, the mechanisms of discovery, trust and revenue are being rewritten.

We’re still learning what the new value exchange looks like. But those who experiment early will be best placed to shape it.

Lessons from the front lines

Based on our work so far, four lessons stand out for organizations preparing for this shift:

1. Map intents, not journeys

Identify what your customers are trying to achieve, not just where they click.
For example, in insurance, instead of mapping the “quote and buy” journey, map intents like protect, compare, renew, claim. These verbs reveal friction points your interfaces hide today.

2. Design APIs that think

Audit your APIs and data products for conversational readiness. Can they handle partial inputs? Can they provide contextual responses?
One client added an orchestration layer that converted vague natural-language requests (“Book my regular doctor”) into structured backend calls — without rewriting core systems.

3. Prototype with purpose

Start small, but make it real. Choose one high-impact use case, connect it to live data, and observe how users behave when freed from rigid UI constraints.

For example, a telco could start with “change my plan” and learn how intent shifts between “upgrade,” “pause,” or “add data” based on context.

4. Prepare to participate, not control

In an intent-first world, your brand will live across ecosystems — in chat assistants, agent networks and voice interfaces. Define your tone, governance and guardrails so that your brand feels consistent even when it’s not inside your own app.

The road ahead

The age of intent isn’t about eliminating interfaces; it’s about making them invisible.

We’re shifting from designing paths to designing purpose — from clicking buttons to expressing goals.

This isn’t a UI revolution; it’s an organizational one. To succeed, businesses need not just better technology but a new mindset — one that treats customer intent as the starting point for every interaction, and context as the connective tissue that binds it all together.

Generative AI has made understanding language effortless. Acting on intent, however, requires coherence across data, design, and decision-making.

The tools are here. The possibilities are real.

The question is: are we ready to build for intent — not just for interaction?

In the next article, “Building for Intent: What It Takes to Become an Intent-Ready Organization,” we shift focus from the prototype to the enterprise — unpacking what leaders need to do across architecture, culture, and governance to turn these experiments into lasting capability.