The plan was to spend a weekend validating whether a complete PCB design library was actually buildable at AI velocity.
Not a prototype. Not a demo with curated inputs. Something that could consume real Gerber RS-274X files — the manufacturing format that PCB designers actually export from KiCad, Altium, Eagle — parse them completely, and produce manufacturing-ready outputs.
I have been writing software for thirty years. In that time I have sat through thousands of daily standups, hundreds of onboarding sessions, and more planning ceremonies than I care to count. Most of them existed for one reason: transferring context from people who had it to people who did not. The new developer needs to know how the deployment pipeline works. The team lead missed yesterday's discussion about the API change. The architect needs to understand why the data model looks the way it does before approving the next feature.
These are not bad reasons to meet. But they are expensive reasons. And increasingly, they are avoidable ones.
You'd think parsing a part number would be trivial.
A string of characters. Match it against a pattern. Done.
Then you actually try to do it across a real component database, and you discover how much institutional knowledge is packed into those strings — and how little of it is documented anywhere.