Dots: Always-on agents

There's a lot of negativity in here for Dots. I've been a pretty heavy user of Grok Bot, and here are a few thoughts a long the positive line. 1. Collaboration between always-on agents is a really, really powerful thing. It allows for domain-specific expertise that doesn't overload the context window, while still allowing for access to knowledge if they need it. 2. Domain-specific always on agents creates a good barrier of trust. One of the things I dislike about Claude is sometimes it's memory is all-encompassing. It's weird that it brings up things about my personal life when I'm talking about something related to my business. I've never had that happen with Grok Bot bots because I have one for my biz admin and one for my personal admin. They don't intertwine, which is quite nice. 3. Combined with cloud agents / cloud builds, things become really powerful for development. It was the first time that I felt there was a solution to the git worktrees / multiple streams at once issue. Each bot has its own computer and can spin up additional cloud agents. It comes at the cost of end to end speed - doing something via a grok bot often takes an hour end to end, whereas with a synchronous local prompt it'll take like 10min. The difference is I have to babysit one whereas the other "just works". On the flip side, since using Grok Bots my inference spend has 2-3x'd. It's worth knowing that tradeoff. Nonetheless I think Luna is a fantastic driver for these, and OAI has very good pricing overall. I'd give these a shot - I think a lot of people would be surprised how helpful they are.

I must be getting dumber as I get older. I genuinely can't work out what Dots actually is. It seems like a dumbed down reskin of Codex/ChatGPT Work but with the power-user features e.g. visibility/mentions removed. As a serious engineer why would I want that? Then the word agent becomes dot. It also seems to be running a VM so the agent has its own computer. I guess the intent was to pull together the Codex, claw and ChatGPT Work paradigms and simplify them?

This is one part of AI I hadn’t success with. I have very little need to run Agents over night, as my throughput is limited by my approval. Each work usually needs revisions, sometimes the bug is just a symptom of the root problem, sometimes I need to rethink how users want to use the app. Sometimes I need research. I get how i prefer an already researched-version of a bug versus a raw bug notice, but I can do this with webhooks in the correct environment. I really have no idea what to do with my agents over night. I can not build more. I can not think of more problems. My RAM is full.

Ok so not that many months ago, the consensus seemed to be that the smart take on openclaw was "don't trust it; don't give it write or delete access to anything you care about; don't give it read access to anything sensitive; expect that it may go off the rails and delete your inbox and send checks to that prince in your spam folder at any time. If you still have tasks that it can do within those restrictions, have fun." Today the models are better, but they don't seem trustworthy or reliable enough that I want to give them them a lot of access or freedom. My coding agents sometimes still go off in the wrong direction, or say they did something other than what they did, or say they will do something and then immediately stop without doing anything. The always-running (so almost never supervised) agent that is meant to do the same work as a person (and therefore needs _access_ like a person) seems like a notorious footgun from earlier this year was just made more powerful, and the companies that are supposed to know the most are telling you to connect it to everything.

> excluding the European Economic Area, Switzerland, and the UK https://help.openai.com/en/articles/20001530-getting-started...