Thought Exercise: Design a Self-Improving Web Agent
Explore how to design a self-improving web agent that overcomes repeated task inefficiencies by creating reusable functions. Understand how to structure the agent's learning process, build a skill library, and manage evolving capabilities for smarter autonomous web interaction.
In our previous lessons, we explored the architecture of WebVoyager, an agent designed to complete live web tasks with a higher probability of success than traditional web agents. But what happens after the task is done? How does an agent continue to get smarter over time?
One of the key limitations of many web agents is the generalization problem. While they often perform well on the specific tasks they are designed for, they struggle to adapt to new websites or apply what they’ve learned in one context to another. This is because most agents lack a built-in mechanism for self-improvement and the ability to abstract procedural knowledge that can be reused across tasks.
The goal: An agent that learns skills
To ...