SQLite

A single readiness percentage is a number you can fool yourself with. Waypoint replaced it with ten independent gates that each pass or fail on their own evidence.

Listing sites edit and pull their own pages. Homestead keeps every capture as immutable evidence and rebuilds the searchable database from it, so a delisted house keeps its record.

The timer that snapshots Loupe's databases reported success while the newest snapshot in the destination was three days old. Two scheduled runs had failed and a manual test run had overwritten the status. Then a real restore drill, which checked four properties and first failed on my own script's assumption.

Breadcrumbs grew a price-history service over 17 months of my own grocery orders. Two facts about the data shaped the whole design, a passing test suite hid a false alert that only a replay against real orders exposed, and raising the threshold provably could not fix the promo problem.

Prospect's two AI background workers were quietly overwriting each other's status, so every service restart redid work that was already done. The handoff called it a one-row cosmetic cleanup. Reading the two workers against each other showed something worse, and the fix cost no GPU time.

Prospect's migration runner picks the live database when you forget to tell it otherwise. I found that out by running it without the environment variable, against production.

Three database backups written to network storage two weeks earlier were all zero bytes. The cause was an idle timeout on the mount tearing it down mid-write. The obvious retry then failed instantly for a second, unrelated reason, and the worker stopped and asked instead of improvising.

Prospect got meaning-based search fused with its keyword search, and a semantic check for reposted listings. Both had to be designed so they could fail without taking anything down, and the duplicate threshold was calibrated on a copy before it touched the real database.

A wide day: shipped a dormant glass redesign and a fully responsive header, chased a stats box that kept clipping, traced six photo-pairing mis-binds down to a filename suffix, sorted out the faithful way to pull edited photos, relocated my notes vault, and ran a security review I'm keeping vague on purpose.

A long, many-threaded day. I built the full path that lets a second person's Apple-photo metadata become my app's enrichment database, turned the setup console into something that can actually start the pipeline stages itself, split the frontend out of the monolith, unified the brand across app and marketing site, stood up real email, and fixed a couple of bugs that had been silently breaking the photo pipeline for a while.

A long, many-threaded day: renamed both repos to loupe, shipped the Map and Cutting Room pages, built the in-app People view on top of face embeddings, redrew the brand mark down to the favicon, and stood up the onboarding front door.

The day Loupe stopped being a thing that only runs on my machine. I reframed it as a self-hostable product, made the pipeline portable through environment variables, scrubbed both repos clean for publishing, finalized a brand and header, fixed the photobook's repetition problem, and registered loupeculling.com for a marketing site.

The day the project got a name and a spine: I came back to a box that had silently rebooted, merged two sibling photo-review apps into one managed service called Loupe, added a cloud backup and AI-written period summaries, and built an enrichment layer that joins Apple's own labels, people, and scores back onto my library by UUID.

A long day: turning a 462 GB copy into an instant rename by understanding the filesystem, catching two backup processes about to trample each other, and building two browser tools to actually review ~91,000 photos without ever deleting one by accident.

An aggressive package cleanup quietly broke my storage box's admin UI through a dependency I didn't know mattered. Then a filename-normalizer bug taught me to trust byte sizes over names when matching files back to a database.

With the metadata database built, I started defining rules to surface delete-candidates. Two of the rules found nothing, one was secretly broken, and the biggest 'junk' bucket turned out to be footage I'd never delete. The lesson of the day: rules lie, pixels don't.

Day one of the photo project: build an ingest tool that reads ~91,000 photos and videos into a SQLite database so I can cull systematically. The build went fine. The environment fought me, and the performance lessons were not where I expected.