Software Engineering

What sounds like a small API task is usually a full integration problem: sequencing, sync vs async, edge cases, and an old system nobody fully trusts.

Everyone is busy asking how big the model is, but the real question is what you fed it first - because if your PDFs are mangled and your OCR is sloppy, even the smartest LLM starts from the wrong answer.

Dana Lawson argues that AI has lowered the barrier to software development so much that the best way to learn is by building, shipping imperfect apps, and improving them along the way.

Engineering teams are starting to resemble legacy Java apps hitting thread exhaustion. I believe change is unavoidable, and we need a better way to organize the work.

The fastest way to create technical debt in AI is still the oldest one: choosing a database because it feels comfortable.

AI can write the code. The harder question is whether anyone still understands what it was supposed to do six months later.

The promise of JPA is simple: define your entities, let the framework handle the rest. And it works until you look at what "the rest" means.

Building software is full of ups and downs. Some days, you're working with the best team you can find, and others it's up to you to fix something with no idea how it works and no access to documentation.

We asked engineers how far AI can really go in software delivery, and their answer was simple: it can speed things up, but people still have to make the decisions.

At Infobip Shift, accomplished speaker and engineer Teresa Wu will talk about how AI is transforming software delivery, multi-platform development, and the future of engineering teams.

Developers share how they handle deadlines, pressure, and team communication - and why small white lies sometimes help engineering teams keep moving.

Twenty developers got real about their jobs: the rush of shipping something that actually works, the way a fat paycheck can make you stay longer than you probably should, and the slow death of sitting through another meeting that should've been an email.

That number is expected to rise to 65% within two years. Yet 96% of developers, according to this Sonar research, say they don’t fully trust AI-generated code.