How to find the Codex CLI daemon still running after the session closes (and when to keep it)
Closing Codex CLI no longer stops it. We put 0.162.1 on a clean box, counted what kept running, and found the one config line each kind of machine needs.
Heads up with hands down. Filters hundreds of AI developments down to the ones that actually matter.
Closing Codex CLI no longer stops it. We put 0.162.1 on a clean box, counted what kept running, and found the one config line each kind of machine needs.
A kill -9 two seconds into a Pi Durable run: the search ran again, the half-finished deploy did not. The only setup the harness asks for is one word next to each tool.
No install, no downloads: the Ollama registry answers manifest requests straight. Eight model families checked, four of them point a famous bare name at a small distill. The ten-minute fix, and where Ollama still wins.
Jev returns typed decisions instead of prose, fast and cheap enough to retire the habit of using an LLM as an intelligent if-statement. We have run it, and it delivers. The 444.6x on the homepage does not — against the model TypeSafe itself calls comparable, the figure is about 76x.
We planted 19 agent surfaces on a machine and ran geiger against them. It found 14, and its own recommended cron drift alarm reported no change while a new MCP server appeared in a repo it never scanned.
The index lists 53 skills, the repo holds 37, the plugin installs 25. We cloned the pack and measured the install: the context-bloat fear is half a percent.
We cloned book-to-skill and ran its own bench: 57.6x on our book - and identical on all five chapters. The denominator is a fixed 5,000-token design cap.
WASTE runs the complete 2.78T Kimi K3 on a 64 GB MacBook. It works – at 0.6 tokens a second, with a memory setting that makes it slower the more RAM you give it. The worth-it verdict.
I built the purple-gradient page every AI agent emits, then let Hallmark rebuild the same content and audited both. Ten critical slop-tells before, zero after. Here's the before and after — and the seam the demo hides.
OpenAI's GPT-5.6 Sol is the best knowledge-work model I've sat next to - fast, resourceful, steerable. It's just not the coding king the launch claims, and OpenAI's own numbers say so.
Fable 5 is back. There's no magic prompt - the whole skill is two moves: pick the right job, and make the model prove its work. Here are the ones I actually use.
The tool everyone adopted doesn't make your team smarter - it makes them louder. A hands-on verdict on signal-to-noise, slop cannons, and the one metric that actually sorts operators.
Three agent-stack bills landed at once this week. One - an actively-exploited LiteLLM RCE - has a June 22 clock on it. Here's the cut that matters, and what's safe to skip.
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