Plausible diffs are where expensive mistakes hide.
Over the last few months, I’ve been running a product stack end-to-end myself, with no review queue to hide behind when an AI hand-waves a gnarly edge case. For a while, my workflow was the default one: I’d describe a task to Claude, it would write the code, I’d skim the diff, and I’d merge. It worked. Mostly.
[Read More]Extracting deals from emails sounds straightforward until you attempt it at scale. It quickly becomes a deceptively hard NLP problem: unstructured text, image-only creatives, ambiguous marketing language, and no standardized format.
Solving it required multiple architectural shifts. What started as prompt-heavy extraction ultimately evolved into a cost-efficient agent-based system.
I designed this production-grade pipeline for Offerivo to reliably identify deals, coupons, and expiration dates while keeping inference costs under control.
[Read More]
