My team at Factory’s growing (FTE, onsite in San Francisco). Come work with me to beef up 1) our security stance, and 2) our IT program. We’re growing rapidly and I want to get ahead of scaling issues. You’ll work directly with me, with agency to define and evolve your own role. Today we need hands-on-keyboard IC work. Want to grow that into a director-level role? This is the time to join.

Security Engineer: factory.ai/careers/s…

IT Operations Specialist: factory.ai/careers/i…

My OpenClaw, summarizing my day’s adventures:

“Solid evening flow though. Car bodywork → Animal Crossing → Cyberpunk. The perfect arc of ‘paid labor, chill labor, and violent labor.’”

Even our fruit is getting into the AI business.

AI prompt of the day:

You export an app’s user list and want to import it into Okta before you sync the 2. Okta gives you a CSV template to download, usually (always?) called okta-csv-template.csv, but its format varies per-application.

“Please rewrite employees-export.csv in the format of okta-csv-template.csv.”

This saves so much tedium.

Why yes, you can run Factory’s Droid on a Raspberry Pi. Not officially, sure. This isn’t part of our CI/CD pipeline and we’re not publishing packages for it the way we do for our supported platforms. Still, it works!

Anthropic’s leaning in to the whole nanny state thing.

(This is a real, actual screenshot.)

I was talking to some AI industry leaders last night. Their words helped crystalize my own thoughts on Anthropic’s “guardrails” around using their models.

A lot of what I do is legal only because of context. I carry lock picks in my bag. I use them to get into my own stuff (and to satisfy my own curiosity) and never use them to gain access I shouldn’t have. Is it bad to use lock picks? That’s impossible to say without knowing why they’re used.

I ask AI to find security flaws in my software to identify those problems (and to satisfy my own curiosity) and never use it to gain access I shouldn’t have. Is it bad to use Fable — or any number of “hacking” tools like Burp Suite or Metasploit or John The Ripper? That’s impossible to say without knowing why they’re used.

And damned if I want to come to Anthropic, hat in hand, and beg them to please, sir, may I use this tool I’m paying you for, and I’ll let you watch over my shoulder the whole time to see if I’m doing it alright? If they think they might not want my money sometimes, they shouldn’t take it at all.

I didn’t have to explain to the lock picks guy what I’m doing with them.

I’ve been running Ollama on my Mac Studio for local AI experiments. I followed advice to try oMLX instead and it’s ludicrously faster, like maybe 5-10x for both time to first token and completing the response. I haven’t benchmarked it, but it subjectively feels like when I replaced a hard drive with an SSD.

AI is fantastic at configuring Emacs.

Me: Why does Emacs format this TS differently than Prettier does?

Droid: There’s the problem. Apheleia’s prettier-typescript formatter includes (apheleia-formatters-js-indent “–use-tabs” “–tab-width”), which injects –tab-width and –use-tabs flags based on your Emacs buffer settings. These override the project’s .prettierrc.json config, so Prettier gets different arguments than when your coworkers run it from the command line.

Atlassian Enables Default Data Collection to Train AI:

Atlassian is changing its data contribution policy so that, starting August 17, 2026, it will use customer metadata and in-app content from Jira, Confluence, and other Atlassian Cloud products to train its AI capabilities, including Rovo and Rovo Dev. The update applies to about 300,000 customers and implements tiered defaults: lower tiers cannot opt out of metadata collection, while Enterprise plans retain opt-out controls. Atlassian will retain contributed data for up to seven years.

Buh-bye! 👋