Care to share your thoughts on muscle-mem, the recent, related "meta-tool" for caching "agent trajectories"? https://github.com/pig-dot-dev/muscle-mem
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A few months ago, we launched Browser Use (https://news.ycombinator.com/item?id=43173378), which let LLMs perform tasks in the browser using natural language prompts. It was great for one-off tasks like booking flights or finding products—but we soon realized enterprises have somewhat different needs:
They typically have one workflow with dynamic variables (e.g., filling out a form and downloading a PDF) that they want to reliably run a million times without breaking. Pure LLM agents were slow, expensive, and unpredictable for these high-frequency tasks.
So we just started working on Workflow Use:
- You show the browser what to do (by manually recording steps; show don’t tell).
- An LLM converts these recordings into deterministic scripts with variables (scripts include AI steps as well, where it’s 100% agentic)
- Scripts run reliably, 10x faster, and ~90% cheaper than Browser Use.
- If a step breaks, workflow will fallback to Browser Use and agentically run the step. (This self-healing functionality is still very early.)
This project just kicked off, so lots of things will break, it’s definitely not production-ready yet, and plenty of stuff is still missing (like a solid editor and proper self-healing). But we wanted to share early, get feedback, and figure out what workflows you’d want to automate this way.
Try it out and let us know what you think!