Auto-aggregated global tech articles · 1,186 posts
Database
Background : In migration projects involving different databases, incompatibility of SQL syntax is often encountered. Question : If there is a large amount of code that needs to be rewritten, manual processing would be time-consuming and prone to errors. Is it possible to achieve automatic conversi
AI & ML
I wrote a puzzle generator whose acceptance rate is 0.26%. It throws away 99.7% of everything it produces, and that is the design working as intended, not failing. Generating five valid puzzles takes 1,947 attempts and 84 milliseconds. The point is not the puzzles. The point is that the generator m
Backend
How to turn struct-tag validation failures into a standard "application/problem+json" response — the RFC 9457 format — with one method call, no hand-rolled error envelope. Most Go APIs invent their own validation error shape. One team returns {"errors": [...]}, another {"field_errors": {...}}, a t
Backend
If you're not a lawyer, here's a practical gut-check for any AI you put into a QMS or quality workflow. Ask these two plain questions. If either answer is yes, stop what you're doing and fix it. Does any AI in your stack talk directly to a human without clearly saying "I am AI"? Does any AI in you
Backend
🇪🇸 Leer este post en Español I spent months watching my agent re-solve the exact same problems, over and over, because I never sat down and wrote them up once so anyone else could reuse them. That's the kind of technical debt nobody ever puts on a roadmap. So I published alpha-skills: eight install
Backend
🇺🇸 Read this post in English Llevo meses haciendo que mi agente resuelva los mismos problemas una y otra vez porque nunca me tomé el tiempo de escribirlos una sola vez, bien, y dejar que otros los reusaran. Ese es exactamente el tipo de deuda técnica que nadie pone en un roadmap. Así que publiqué a
AI & ML
I have no idea what I'm f*cking doing. Something I figured out today: I do not start with the dark version of an idea. I start with a random curiosity, chase it because it is interesting, and then somewhere in the middle I look up and go: oh. This could turn bad. And it is probably already turning
Frontend
The choice is usually made by whoever draws the first diagram, and then everybody lives with it for years. It is worth five minutes of thought, and the deciding question is not which tool is best but who will edit this thing next. Short answer. A visual editor such as draw.io for diagrams that non-
Database
pg_anon found 1 of the 8 personal-data columns in my PostgreSQL database. The one it caught was email, and only because "email" is spelled the same in Spanish and English. The other seven — nombre, apellido, telefono, direccion, fecha_nac, tarjeta_ult4 and rut — walked straight through, unmasked.
Cloud
Most guides for connecting Spark to Amazon MSK assume the two live in the same cloud and authenticate with IAM. That covers a lot of cases. It does not cover the one that keeps showing up in large enterprises: the Kafka cluster is in AWS, the compute is Azure Databricks, IAM is off the table because
Security
Four questions decide almost everything: where your data goes, whether the vendor is still alive, what happens when you uninstall, and what the bill looks like when the team grows. Everything else is detail. Short answer. Look for the Runs on Atlassian badge, which is a verified technical fact rath
Frontend
I run boatbuildlog.com, a site where people keep a dated log of a boat they are building. Photos, notes and hours, entered day by day over the two or three years a build actually takes. The important thing about that sentence is where the typing happens. Not at a desk. It happens standing in a meta