2025-11-19
Â
If you don’t want to read anything, and just want to play with an Agent-First App, you can try SqSquare!
The Cut and paste madness
The magic happens only when user and LLMs are sharing the same context.
But we're currently in an absurd phase of AI interaction: 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 AI-assisted tasks feel so frustrating.
The Agent First Paradigm
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.
Â
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.
From Mobile First to Agent First
It took 10 years between the first iPhone and Uber, which truly leveraged the full power of the mobile-first paradigm. "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're forced to define clear, tool-friendly interactions and structured data. This approach makes development faster—all the intelligence of LLMs comes for free—and creates emergent features that adapt to the various use cases your users want to solve.
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.
Â
This is fundamentally different from the classical paradigm where an AI agent can use your web-browser on your behalf. With Agent first app, the provider of the app is in control of the context, the tools it give to the agent and the human. It is still in control of the experience the user will have.
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.
How to make an Agent first app
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.
The path forward for developers is clear:
- Design for LLMs: Build your app so that a language model can understand and interact with it.
- 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 Agent have to be able to read the UI and write it. This is what will enable emergent features.
- Implement Granular Security: Create permission levels that differentiate between what a user must do manually and what an agent can do on their behalf.
Conclusion
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.