Really exciting to see this approach to automation and intent specification! We’ve been working with similar challenges at Origins AI, where we focus on deep tech solutions.

I can’t overstate how much having a robust system for breaking down tasks and iterating on them has helped us.

For one of our recent projects, we had to integrate complex workflows with third-party systems, and it was clear that reliability came down to how well we could define and refine intent over time.

I’m especially curious about your self-healing automations. That’s an area where we’ve found a lot of value using models that can adapt to subtle UI changes, but it’s always a tradeoff with latency. Would love to hear more about how you balance that in production!

Looking forward to trying Autotab and seeing how it compares with some of the internal tools we’ve built!

Agree on the tradeoff between ability to handle novel situations and speed/cost. Autotab uses a “ladder of compute” system that escalates to the minimal level of compute required to solve a given subtask. I wrote a longer comment about this on another thread