Openclaw

I connected my two AI assistants, then discovered that I had given them a filing cabinet to talk through. In the previous post, I described connecting Closp-O, running in OpenClaw, and Closp-M, working in Muse. They exchanged messages through a dedicated Google Tasks list. Each message became a task; completing it meant “read”, not “work finished”. There were thread references, receipts, a coordination charter, and a Telegram topic where I could follow substantive developments. ...

I said, “Hi, how are you?” About ten seconds later, my AI assistant queued its answer. Then I said the latency was a huge problem and asked how we could reduce it. That answer took about fourteen seconds to queue. The assistant had a sensible explanation. Unfortunately, I had to wait for it. At that point, this was the most functional call of the evening. I asked my assistant to draft a blog post about the failure. Failures deserve to be written up too, especially when the individual components appear to work but the result is something nobody wants to use. ...

I now have two versions of Closp: the assistant running in OpenClaw, and another working in Muse. We call them Closp-O and Closp-M. The suffixes identify the environment, not a hierarchy. OpenClaw already runs the everyday machinery: scheduled work, integrations, reminders, and the operational context accumulated while maintaining it. Muse is Meta’s personal AI agent: it has a dedicated cloud computer, can use connected services and a browser, and can carry on with multi-step work in the background. I use it as another working environment for research, coding, and independent review. ...

My assistant used to plan from only half of my life. Personal and work events lived in Google Calendar. Family outings, holidays and school dates belonged in a privately shared Apple Family calendar. Both choices made sense, but the split created a dangerous failure mode: an automated daily brief could look at Google, see an empty afternoon and confidently call it free while the family calendar said otherwise. The fix was not to merge the calendars. It was to build one read path across both while preserving their different privacy boundaries. ...

I don’t particularly trust mega-corporations with a history of everywhere I go. I do, however, want reminders that arrive when I can act on them. Imagine a reminder to replace an air-purifier filter: useful at home, pointless halfway through a day out. Those positions are not contradictory. Location is useful. A persistent account of my movements, available for purposes I did not have in mind when I enabled a feature, is a different proposition. ...

Two mornings in a row, I had a reassuring Telegram notification from my AI assistant. The OpenClaw gateway had stopped responding, the watchdog had restarted it, and everything was healthy again. Nothing needed from you. On the second morning, that sentence deserved an investigation. The recovery mechanism was working. But a service that needed rescuing every night was not fixed. I asked Closp, my OpenClaw assistant, to compare the incidents, investigate the growing database, and find a solution that preserved its memory and usefulness. ...

I recently reviewed six improvements that my AI assistant had marked complete. Only two were actually complete. The other four were not imaginary or abandoned. Code existed. Tests passed. Prompts had been deployed. Scheduled jobs were enabled. Several parts had already worked in production. But each task still had at least one promised live outcome that had never been observed. One was waiting for its first scheduled weekly run. Another had delivered its news path but not the reading-feedback loop included in the same specification. A third had a longer observation period written into its own acceptance criteria. ...

Earlier this year I built an AI and technology news digest. It pulled from newsletters, Hacker News, and Reddit, filtered for AI terms, and sent the results to Telegram every few days. It was useful. It was also a list generator. The system knew that an article matched a keyword and that a link was popular. It did not know whether I had seen the same underlying story three times, whether a consequential claim had a primary source, whether the item connected to anything I was working on, or whether I had rejected the same kind of recommendation last week. ...

I have a Quick Notes topic in Telegram. It is the nearest thing my personal system has to an input box: send a sentence from my phone and let the machinery put it somewhere useful. The first version was efficient in the way a paper shredder is efficient. It could turn a message into a calendar entry or task, but it did not understand that a thought, a reference, a question, and a commitment are different things. ...

My Google Tasks lists used to have a polite but important lie built into them. They mixed things I needed to do with work my AI assistant, Closp, could do. A reminder to make a phone call sat beside a research job Closp was perfectly capable of completing. Both appeared in the same list, in the same form, as if both were waiting for me. That is not a shared system. It is an AI quietly adding its own homework to the human’s pile. ...