Remember that feeling when you first realized the internet wasn’t just for looking things up, but for doing things? Or when smartphones transformed from communication tools into personal assistants, cameras, and wallets, all in one? We’re at another one of those inflection points, perhaps even more profound. The question isn’t just about what products can do for humans anymore. It’s becoming: are we building for humans, or for the intelligent agents that represent them?
It’s a thought that might seem pulled from a sci-fi novel, but the reality is catching up faster than most product teams can keep pace. Innovations this year, particularly in the realm of AI agents, are already reshaping how we define ‘user’ and ‘experience.’ A significant development pushing this frontier is Google’s Agent Payments Protocol (AP2), released in September 2025. This isn’t just another tech update; it’s a paradigm shift, enabling AI agents and systems to execute payments and transactions independently on behalf of users. Suddenly, the assumption that a human is at the other end of every transaction evaporates, and with it, much of what we thought we knew about product design. So, how do we navigate this exciting, bewildering new reality? Let’s dive in.
Google’s AP2: Ushering in the Agent-First Era
If you’ve been anywhere near tech media lately, you’ve probably seen 2025 tagged as “the year of AI agents.” And honestly, it’s hard to argue with that prediction. We’ve witnessed some incredible AI rollouts recently, and the momentum only seems to be building. While earlier iterations of agents might have just responded to prompts or handled single, isolated tasks, the ambition for true AI agents has always been much grander.
The vision is for systems that can plan and execute complex tasks, integrate and use external tools, adapt to feedback, and even operate autonomously with a degree of independence. The expectations are incredibly high, and it’s easy to see why the entire sector is buzzing with anticipation for these ideas to become tangible realities. However, many of the initial releases we’ve seen this year, while promising, have only scratched the surface of these aspirations, often falling short when it came to robust, real-world application.
That is, until September 17th, with the release of Google’s Agent Payments Protocol (AP2). This isn’t just a shiny demo; AP2 is an open protocol designed specifically to allow agents to authenticate, purchase, and transact autonomously. Crucially, it’s built to ensure that these automated payment flows remain fully compliant with existing financial regulations. This isn’t just a tweak; it’s a fundamental rethinking of digital commerce.
From Clicks to Intent: How AP2 Changes Everything
In practical terms, AP2 redefines several core interactions:
- Shopping shifts from “add to cart” to “delegate to agent.” Imagine telling your agent, “I really need this jacket in an XL, and I’m willing to pay 30% more for it if it comes back in stock.” Your agent then monitors inventory, negotiates, and executes the purchase the moment those conditions are met, all without you lifting a finger.
- Scheduling becomes syncing between AI proxies. No more back-and-forth emails trying to find a time that works for everyone. Your agent talks to their agent, and boom, the meeting is booked.
- Engagement evolves from clicks to intent alignment. It’s not about how many times an agent “clicks” on something, but how accurately and effectively it fulfills its user’s underlying desire or goal.
A recent Google Cloud blog post highlighted some of AP2’s key design functionalities, from smarter shopping experiences to accessing personalized offers and coordinating complex tasks related to purchases. The example of the leather jacket isn’t just hypothetical; it illustrates the profound shift AP2 enables. While many AI agent rollouts have struggled transitioning from impressive demos to reliable business process handling—a LangChain study even found performance quality to be the #1 concern for 82% of organizations deploying AI agents—Google’s recent success with innovations like VEO3 gives reason for significant optimism. AP2 has the potential to be the biggest enabler of true agent-first experiences for product leaders everywhere.
Designing for The Digital Twin: A New Lens for Product Design
The concept of a “digital twin” isn’t entirely new. IBM defines it as a digital representation of an object or system that updates in real-time, leveraging simulations, machine learning, and reasoning to support decision-making. In sectors like manufacturing and infrastructure, these digital models that mirror physical systems have been around for decades. McKinsey calls it “the ultimate convergence of data and design.” But what’s truly new is the integration of artificial intelligence, particularly the kind of autonomous agents we’re now seeing.
This integration forces product teams to fundamentally rethink their approach to design. Traditional user experience (UX) principles are, by definition, built around human cognition, human interaction patterns, and human emotional responses. They’re about intuitive interfaces for *us*. But what happens when the ‘user’ at the other end of the screen isn’t human at all, but an intelligent proxy operating on behalf of a human? Those traditional approaches simply won’t suffice.
Product leaders now face a host of entirely new factors to consider. For instance, there’s an urgent need to prioritize robust APIs and rich semantic metadata. These aren’t just technical details; they become the very language through which agents can interpret information, understand context, and reliably act upon instructions. If an agent can’t accurately parse the intent or the available actions, the whole system breaks down.
At the same time, we must delve into critical areas like vulnerability loops and robust mechanisms to confirm that an agent’s actions genuinely represent its user’s intent. Imagine an agent making a purchase decision with unintended consequences, or being tricked into an action that doesn’t align with its owner’s values. This means designing not just for convenience, but for security, transparency, and accountability in a whole new dimension. This model fundamentally changes what it means to “design for the users,” as the next customer journey we curate might not be a direct interaction, but one mediated and executed through intelligent, autonomous proxies.
Navigating the New Frontier: Lessons for Product Leaders
The most crucial takeaway from innovations like Google’s AP2 isn’t just about understanding the technology; it’s about recognizing the sheer pace of industry evolution and the absolute necessity of staying actively involved. If AI agents become a commonplace, working system for digital transactions, how do we, as product leaders, integrate ourselves and our offerings into such a model? We need to start by asking some hard, foundational questions:
Are We Ready to Design for Agents as First-Class Customers?
This isn’t about adding a chatbot to your website. It’s about a complete reorientation. Do your product roadmaps account for agent-centric features? Are you thinking about how an AI agent, not a human, would interact with your product’s services? This requires a shift in mindset from direct human engagement to creating an environment where an agent can efficiently and reliably fulfill its user’s needs.
Can Our APIs and Systems Support Autonomous Decision-Making?
This is where the rubber meets the road. Are your APIs comprehensive, well-documented, and robust enough for an AI agent to navigate complex decision trees and execute transactions without human intervention? Is the semantic metadata rich enough to convey nuanced intent, or will agents struggle with ambiguity? Building for agent autonomy means your underlying infrastructure needs to be incredibly intelligent and resilient.
Do We Measure Success by Engagement, or by How Faithfully Agents Reflect User Values?
Traditional metrics like clicks, time on site, or conversion rates might become secondary. The true measure of success in an agent-first world could be the fidelity with which an agent reflects its user’s preferences, identity, and ethical boundaries. It’s about effective delegation and accurate execution, not just direct human interaction. This requires new ways of thinking about analytics and feedback loops.
The Human-Product Relationship in the Age of Agents
Ultimately, designing for AI agents is about redefining the profound relationship between people and the products they use. While the immediate focus might seem to shift towards crafting experiences for autonomous agents, it’s absolutely vital to remember that these agents are not independent entities. They are, in every meaningful sense, extensions of their users. They embody their identity, reflect their preferences, and carry out their ethics.
When you design with those foundational human values at the core—ensuring that the agent acts as a true, trustworthy proxy—you’re not just building for today’s interfaces or the current wave of AI. You’re building products that are resilient, adaptable, and fundamentally aligned with human needs, capable of surviving and thriving through the next, undoubtedly even more transformative, waves of AI innovation. The future isn’t about replacing human interaction, but enhancing it through intelligent mediation.
