Simular discusses decision architecture for personal agents
A Simular team member on an SFTechWeek panel covered when personal agents should think, act or ask, how much autonomy to grant, and what the architecture looks like after Muse Gadgets and OpenAI Dots launched.
Our MTS @Richard_simular, part of the team that built @sai_borg, answered 4 critical questions on personal agents on a panel at #SFTechWeek: 1. When should an agent think, when should it just act, and when must it stop and ask — what’s your decision architecture? Start super strict then slowly relax the guard. User & personal agent have a continual "bonding" process, and people have different preferences so it's never going to a one size fits all 2. Do agents overthink into paralysis? Usually it's not an agent, but a weak model overthinking. Some models do this to benchmaxx so you will see an agent thinks for 4 minutes for a simple task like open http://google.com. 3. How do we know how much autonomy to give to an agent? Running on sandbox is (almost) always the best approach. Factors: 1. how safe is sandbox 2. how reachable is the request to you 3. how quickly it learns and relax permission 4. With Muse Gadgets and OpenAI Dots launching last week, what does personal-agent decision architecture look like 12 months from now How to give more information to agents. If we can find out a way to send explicit and exact request to agent then we don't need any context. Thanks for having us on!