Event

NVIDIA’s Igor Dmochowski explained that LLMs are no longer limited just by model size or benchmark scores; the cost of longer reasoning means runtime, context length, memory use, and throughput matter just as much.

Two-thirds of organizations run AI workloads on Kubernetes, but only 7% do it daily. Katie Gamanji says the ecosystem still needs better operational maturity and standards.

Figma’s Designer Advocate argued that AI can make prototypes look finished too early, which can hide dangerous assumptions.

We’re waiting for the next big AI leap - systems learning from their own experience rather than just human data - and at Infobip Shift, Google DeepMind’s Benoit Schillings said that’s exactly where the field is headed.

Infobip Shift 2026 is officially open, and OpenAI’s Luis Velasco said the real work now is bringing together the data, process, and systems agents need to do the job well and keep improving.

I first met Benoit Schillings, VP of Research at Google DeepMind, in San Francisco to talk about what engineers do when AI writes more of the code. His answer: make sense of the massive systems we inherit. Now, he’s bringing that perspective to Zadar for Infobip Shift 2026.

Jordan Topoleski (COO, Cursor) and Pallavi Mahajan (CTO, Nokia) made the case that the next real breakthrough in AI development is agent orchestration.

AI agents are already being trusted with real work, but handing them raw credentials is a dangerous shortcut. That's why the next security challenge is controlling what an agent can do once it gets access.

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.

I went to Raise Summit in Paris to see whether Lovable is just another tool for non-technical founders - or something developers can actually use to build faster.

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.

A 1,000 libraries, 90% coverage, 1,700 in API tokens. Nobody typed a single test by hand.

Hearing how Uber scaled to 1.500 AI agents made me realize just how quickly things can spiral when those agents start acting faster than humans can keep up.