I’ve spent my career building things, from the singing voice analysis technology at Voxler to the creative tools at Clipdrop. This journey has given me a front-row seat to the evolution of software. Now, I see a new transformation on the horizon, one that I believe will be as significant as the shift to mobile-first design: the rise of agent-first apps. This isn't just an incremental update; it's a complete rethinking of how we interact with technology.
The Agent First Paradigm: Why Every App Must Change
We are currently in an absurd phase of AI interaction, relying on inefficient copy-pasting between traditional software and chatbots. The future belongs to "Agent-First" applications, where AI is embeded in every app, and has the same access to an app as the user. By allowing AI to read and write UI elements, we unlock its true power and enable new features to emerge from even the most boring interface. This will demand that we redesign our software from the ground up.
The integrated agent and the end of the clipboard madness.
Today, the standard workflow is madness: you have one app on one side, and a chatbot like ChatGPT on the other, forcing you to constantly copy and paste information back and forth. This inefficient process is why many AI-assisted tasks feel frustrating.
The solution is clear: the chatbot must be integrated directly into the application, transforming it from a simple conversational tool into a powerful agent. This agent needs two critical abilities to be truly effective:
- Read the Screen: The agent must see everything the user sees—every form, button, data field, and piece of information on the interface. This awareness allows it to provide relevant help, answer questions about functionality, and understand the user's current context.
- Act on the User's Behalf (Write): Crucially, the agent must be able to perform every action a human user can, such as filling out complex forms, clicking buttons, or navigating the interface.
By granting the agent both reading and writing access to the interface, we enable powerful emerging properties. Users can simply ask the agent to "Fill this form using the customer's LinkedIn profile," trusting it to execute multi-step tasks autonomously while still maintaining full human control for verification. This seamless integration eliminates the constant mental overhead of translating intent into clicks and keystrokes.
From Mobile First to Agent First
The transition to integrated agency feels similar to the "Mobile First" paradigm shift we experienced years ago. Just as mobile forced us to simplify UI and focus on core interactions, "Agent First" development requires designing applications specifically for agent use from the ground up. If you start building an app for your internal agent first, you are forced to define clear, tool-friendly interactions and structured data, making the final product much easier to use for humans too.
An Agent First architecture allows different layers of intelligence to interact seamlessly: your SaaS product can provide its specialized know-how via its built-in agent, but it can also interface with a powerful external company agent, or even a highly personalized user agent. This shift fundamentally redefines the web, requiring new security layers to distinguish between human and agent actions, ensuring critical processes like bank transfers involve human confirmation before completion.
How to Create an Agent first app?
Achieving this Agent-First future requires a clear roadmap, starting with fundamental design choices. First, we must design our applications to be inherently "LLM-friendly," meaning they must be structured so that a model can easily identify and utilize the tools, buttons, and API endpoints within the interface. Second, security and trust are paramount, requiring granular control to define exactly what an agent can and cannot do autonomously, ensuring human confirmation is mandatory for critical actions like financial transfers. Finally, the practical path forward is to deploy internal company agents first—which leverage proprietary knowledge for employees—before moving to open up our apps to external, personal user agents. This systematic approach allows us to build the necessary security layers and governance to support a truly Agent-First ecosystem.
From Mobile First to Agent First
The transition to integrated agency feels similar to the "Mobile First" paradigm shift we experienced years ago. Just as mobile forced us to simplify UI and focus on core interactions, "Agent First" development requires designing applications specifically for agent use from the ground up. If you start building an app for your internal agent first, you are forced to define clear, tool-friendly interactions and structured data, making the final product much easier to use for humans too.
An Agent First architecture allows different layers of intelligence to interact seamlessly: your SaaS product can provide its specialized know-how via its built-in agent, but it can also interface with a powerful external company agent, or even a highly personalized user agent.
The Future of Trust and Granular Security
This new reality involves a necessary evolution in how we handle trust and security, especially when personal agents interact with critical systems like banks. If my personal agent knows my goals and preferences, and the bank’s app is Agent First, my agent can interact with the bank's services through secure APIs, not just by "seeing" the screen like a human.
This interaction requires a deep understanding of the difference between a human and an agent, necessitating granular security controls. For instance, my bank's agent may send a mandatory human-only notification for transfer confirmation, even if my personal agent initiates the request. We need to introduce settings that allow users to gradually increase the scope of delegation—starting with read-only access and slowly building up trust until complex, autonomous actions are permitted, potentially backed by insurance against agent errors.
The Three Steps Ahead
The path to an Agent First world is clear and begins with internal redesign. First, we must design applications that are LLM-friendly, meaning they are highly structured and compatible with external tools. Second, this requires granular security to distinguish between user actions and agent actions. Finally, we must first develop our internal chatbot or agent layer; once an app is ready for its own internal agent, it is far better prepared to integrate with the entire ecosystem of external personal and company agents.
-The Integrated Agent and the End of the Clipboard madness
Today, the standard workflow is madness: you have one app on one side, and a chatbot like ChatGPT on the other, forcing users to constantly copy and paste information back and forth. This inefficient, clipboard-centric process is why most AI-assisted tasks feel frustrating and high-friction.
The design pattern that works, seen in generative tools like Jasper, is the "Chatbot on the Left, Canvas on the Right." This pattern transforms the simple conversational chatbot into a powerful agent by embedding it directly into the application. This agent needs two critical, technical capabilities to achieve true agency:
- Read the Screen (Perception): The agent must perceive everything the user sees—every form, button, and data field. This awareness allows it to provide context-aware help and understand the user's current intent, a huge step beyond simple text prompts.
- Act on the User's Behalf (Action): Crucially, the agent must be able to perform every action a human user can, such as filling out complex forms, clicking buttons, or navigating the interface.
By granting the agent both perception and action within the UI, we unlock powerful emerging properties, most notably context persistence. A user can ask the agent to "Fill this form using the customer's LinkedIn profile," and that context (the profile data) stays in the agent's memory as the user moves to the next screen, allowing for multi-step, autonomous task execution.
From Chatbots to True Agents
Imagine you're filling out a complex form online. It's tedious, requiring you to type in your name, address, and other details one field at a time. Now, picture this: on the left side of your screen is a chat window, your agent. You simply type, "Fill this form for me." Since it's your personal agent, it already knows your information and populates the fields instantly.
Let's take it a step further. What if the form is for a new customer? You could say, "Fill this for the client I just met. You can find their details on LinkedIn." The agent understands, navigates to the profile, extracts the relevant information, and completes the form. You still have full control. You can review the agent’s work and make changes before submitting. The difference is that the friction—the boring, repetitive part of the task—is gone.
This two-sided paradigm, with a conversational agent on one side and a dynamic canvas on the other, is becoming the new universal interface. When you experience the ease of describing what you want in plain English and seeing it built or executed in real-time, there’s no going back. It’s a light-switch moment.
A New Web of Interconnected Agents
The real power of this paradigm is unlocked when we think beyond a single app. In an agent-first world, you have your own personal agent. This agent knows you—your preferences, your contacts, your goals. It might live locally on your phone or computer, ensuring your privacy.
Now, imagine you want to send money to your daughter. You open your bank's website, but instead of clicking through menus, you tell your personal agent, "Transfer $20 to my daughter." Your agent interacts with the bank's interface, fills in the details, and waits for your final approval.
This vision requires SaaS providers to make their products agent-first. By doing so, they not only offer a better experience with their own embedded agent but also allow third-party agents, like your personal one, to connect. This interoperability is what will reinvent the web. Your company will have its agent, knowledgeable about its products and processes. You'll have your personal agent. Your bank will have its agent. And they will all be able to communicate and collaborate on your behalf.
Building for the Agent-First Future
Making this shift presents new challenges, particularly around security and trust. An agent-first app must be able to distinguish between a human and an agent and manage their interactions accordingly.
For example, your bank's app should have granular settings that let you define what your personal agent is allowed to do. At first, you might only give it read-only access to your accounts. This would let you ask questions like, "How much can I spend this month and still pay my rent?" As you build trust, you might allow it to make small transfers. A truly advanced system might even involve insurance products, where the bank covers potential mistakes made by your agent.
The path forward for developers is clear:
- Design for LLMs: Build your app so that a language model can understand and interact with it. This means using clear, descriptive language for UI elements and providing structured context.
- Implement Granular Security: Create permission levels that differentiate between what a user must do manually and what an agent can do on their behalf.
- Start with an Internal Agent: The first step is to build and integrate your own agent. This forces you to create an AI-friendly foundation. Once your app works with your own agent, it will be ready to open up to external ones.
The transition to agent-first apps is not a matter of if, but when. Just like mobile-first, it will become the standard for modern software development. The companies that start building for this future today will be the ones that lead the next wave of innovation, creating a world where technology works in true partnership with us.