Technical Context
I latched onto this case not because of the drama around a "fried MacBook," but because it's a very down-to-earth problem for AI automation. If an agent tool holds a single core at 100% in the background, it breaks not just your laptop—it breaks trust in the entire automation scheme.
According to user reports, both Claude Code and Codex can leave phantom processes after a seemingly normal session. On the surface, everything is quiet, the terminal looks idle, but inside, an orphaned Node process or hook keeps spinning the CPU uselessly.
I'd look in three places at once: background Node processes, auto-starting hooks, and overly long sessions with bloated context. For Claude Code, the community has already found workable fixes: kill stuck Node processes, disable the superpowers hook, enable streaming mode, cap parallelism at max-jobs = 2, and clear context with /clear.
One practical nugget I liked: a 5-minute inactivity timeout. It's not an "architecture fix," but as a safety valve, it works fine. Especially if you have several agent channels, each tending to leave a tail behind.
The advice to "run it in a VM" sounds crude, but there's wisdom in it. When I design AI integration for long sessions, I almost always try to isolate the agent runtime from the main machine: a separate VM, container, CPU limits, process monitoring, and strict task termination rules.
What This Means for Business
First: running agent IDEs and CLIs locally can no longer be considered harmless. If a team is building AI solution development around developer laptops, the hidden load quickly turns into overheating, noise, battery drain, and strange "floating" bugs.
Second: the winners are those who bake in isolation and observability from the start. The losers are those who let agents live in endless terminals without timeouts, limits, or watchdog checks.
Third: this hits total cost of ownership. A single phantom process is cheaper to spot on a CPU graph than later dealing with hardware issues, downtime, and lost team time.
If your agents are already running in the background and the machine is behaving "somewhat odd," I wouldn't wait for an official fix. You can quickly re-engineer the setup so that AI automation doesn't kill workstations: at Nahornyi AI Lab, we hand-pick such cases and build safe AI architecture for real workloads, not just for a flashy demo.