The xAI piece is the one that stands out to me. $258B for a lab that's burning $1.46B/quarter against $430M revenue, valued almost entirely on a merger anchor from four months ago.
The hooks performance finding matches what I've seen. I run multiple Claude Code agents in parallel on a remote VM and the first thing I learned was that anything blocking in the agent's critical path kills throughput. Even a few hundred milliseconds per hook call compounds fast when you have agents making dozens of tool calls per minute.
The docker-based service pattern is smart too. I went a different direction for my own setup -- tmux sessions with worktree isolation per agent, which keeps things lightweight but means I have zero observability into what each agent is actually doing beyond tailing logs manually. This solves that gap in a way that doesn't add overhead to the agent itself, which is the right tradeoff.
Curious about one thing -- how does the dashboard handle the case where a sub-agent spawns its own sub-agents? Does it track the full tree or just one level deep?
The closing point is the one that should get more attention — every single one of these apps could be replaced by a web page. And from a product standpoint, there's really only one reason to ship a native app when your content is just press releases and weather alerts: you want access to APIs
the browser won't give you. Background location, biometrics, device identity, boot triggers — none of that is available through a browser, and that's by, unfortunately, design.
The thruster fix is the part that gets me. They sent a command that would either revive thrusters dead since 2004 or cause a catastrophic explosion, then waited 46 hours for the round trip with zero ability to intervene. That's a production deployment with no rollback, no monitoring dashboard, and a 23-hour latency on your logs. They nailed it.
yes, I do agree with that sentiment, there are times when I'm spending way too much time restarting a service that went down, but it doesn't take as long as it used to, especially with AI assistance nowadays. If I'm spending too much time on it, then I'm also probably learning something along the way, so I don't mind spending that time.
The article's dystopia section is dramatic but the practical point is real. I've been self-hosting more and more over the past year specifically because I got uncomfortable with how much of my stack depended on someone else's
servers.
Running a VPS with Tailscale for private access, SQLite instead of
managed databases, flat files synced with git instead of cloud storage. None
of this requires expensive hardware, it just requires caring enough to set it up
you do lose context, but if you generate a plan beforehand and save it, then it makes it easier to gain that context when you come back. I've been able to get out things a lot more quickly this way, because instead of "working" that day, I'll just review the work that's been queued up and focus on it one at a time, so I'm still the bottle neck but it has allowed me to move more quickly at times
the way I handle this is that I just create pull requests (tell the agent to do it at the end), and then I'll come back at a later time to review, so I always have stuff queued up to review.
