WhitePaper – Autonomous Decision Making Agents
ActorDo started as exploring a new kind of AI assistant for knowledge workers: one that does not only suggest, summarize, or draft, but can also act within safe and clearly defined boundaries.
I’ve published the current whitepaper here. Skip intro and read current version: https://docs.google.com/document/d/1qNYtXkUx9rna8M9_A5Y9gS5pkI4bUSBZ6dgAyHVEBjE/edit?tab=t.0
The practical research focuses on a key question: when should an AI assistant act autonomously, and when should it stop and ask for confirmation?
The paper introduces a practical autonomy model based on risk, reversibility, user control, and trust, showing that low-risk tasks like labeling emails, drafting replies, or suggesting follow-ups are the best starting points.
A core principle is that every autonomous action must be visible, explainable, logged, and reversible. The goal is to build an assistant that reduces daily micro-decisions without removing the user’s control.
While ActorDo evolved and product was built, some aspects in the document were built in a slightly different dirrection.
Feel free to read, share, or use it if it’s useful.
I’d be happy to discuss the topic further, exchange ideas, or provide a reference if it helps with your own work.
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