Angelina YangFounder and Host, TwoSetAI · AI builder for visibility and discoverability

The trick to making AI agents reliable (run once, then automate it)

17 Jun 2026 · 1 min

Watch on YouTube

0:31

In this segment, the speaker explains a method to make browser‑based LLM agents as reliable as traditional deterministic web scrapers. The core idea is to execute the agent once, record its actions, and transform that execution into a deterministic workflow. This workflow can be repeatedly rerun until it fails, at which point the original agent is run again to generate a new deterministic flow. By alternating between agent runs and deterministic flow executions, the approach mitigates the high variance inherent in browser agents, delivering consistent results while improving speed and reducing computational cost.

Chapters

It's less reliable, right? Because every time an LLM processes the website. So people who traditionally do like scraping, they are very used to like a deterministic workflow. And now you can give them browser agents, which solve some problems of them. But suddenly browser agents have much more variance. Maybe they do something different. What we built out is if you run your agent once, you can convert this agent into a deterministic flow. And then you can rerun the deterministic flow until it breaks. And then you can run the agent again. With this, you can solve this consistency, the speed, and the cost issue.