Field notes
Notes from real project work: what it takes to get an AI feature past a demo, why we still build on Laravel, how to make a page fast enough to rank, and what changed now that search engines answer instead of link.
Why /nl/pricing loses to /nl/tarieven, how to build translated slugs in Laravel, and the hreflang mistakes that quietly cost you the other languages.
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Three acronyms, one shift: search engines now answer instead of link. What that changes about how pages should be written, and what it does not change at all.
What actually moves LCP, INP and CLS on an application with a decade of code behind it, in the order that gets the most improvement for the least risk.
An honest argument for a ten-year-old framework: what Laravel does better than the alternatives, what it does worse, and the cases where we would pick something else.
How to work out the monthly bill for an AI feature before you build it, which factor dominates, and the four changes that reliably cut it.
Retrieval teaches a model what you know; fine-tuning teaches it how to behave. Most product features need the first, a few need both, and almost none need only the second.
A practical sequence for putting an AI feature into an application that already has users: pick a job, ground it in your data, set budgets, and ship behind a flag.
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