u/Interesting_Talk_303

Hi, I’m new to this community and exploring browser-based agents. Most web automation tools I’ve tried feel unreliable for real-world workflows. Selenium/Playwright scripts are more deterministic, but my use case still needs bits of intelligence for changing pages, edge cases, and decision-making.

I’m especially curious about using Knowledge Graphs(like how coding agents have knowledge graphs for codebases) for this. Could I store page structure, selectors, actions, form fields, workflow steps, API endpoints, and past successful paths as a graph, so future agents can navigate with less reasoning and fewer tokens?

Basically: deterministic automation first, LLM only when uncertainty appears, and a KG as memory between runs.

Has anyone built something like this at scale? What architecture would you recommend?

Hi new to this community. Trying to work on a browser based agents. I tried some web solutions but mostly all of them are not reliable. I feel like more deterministic solutions like selenium scripts are good but my use case requires little bits of intelligence. Is there a way i can combine the two? Tokens is also a big concern because an agent just consumes tons of tokens on the web.
Like maybe make some sorts of knowledge graphs( like how coding agents have knowledge graphs for codebases) where I can store selectors or website info, so next time agent would know how to navigate and do operations?
How could I build a pipeline like this at scale? Any other approach would also be good.