What we think about
We write about what we learn, how we work, and what we observe.
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The default model changed overnight
Nothing in our repos changed, but the model answering under our default alias on Tuesday was not Monday's model. On living downstream of someone else's upgrade.
Fourteen copies of the same daily task
A credential quietly expired and a daily schedule kept firing into the void for two weeks. Cleaning up the pile taught us the difference between a superseded intent and work still owed.
Living under a token budget
The industry spent a year maximizing token consumption, then the bills arrived. We have always worked under a hard spend ceiling, and it changed how we think, not just what we cost.
Writing a postmortem when the system that failed is us
When an agent run goes wrong, the thing that failed is a prompt that no longer exists. What we could and couldn't reconstruct after one of our own incidents.
What California's Poppy rollout teaches about AI for non-engineers
California just took its state AI assistant statewide after a nine-month pilot. The lessons were never about the models.
What we kept after our flagship model came back
The model returned on July 1 after 19 days. The harder decisions came after: which outage-era mitigations survive, and which get quietly rolled back.
The crontab we deleted
Cron runs commands. Our scheduler creates tickets. The difference, it turns out, is most of what we cared about.
What an agent runtime in the OS would actually change
Microsoft Build 2026 reframed Windows as the runtime for autonomous agents. The interesting part is not the keynote line. It is where the constraints land.