The AI conversation is getting healthier. You can feel it in the way people are writing and talking about 2026. Less obsession over who has the biggest model and more attention on what actually ships, gets adopted, and holds up under real constraints. TechCrunch framed 2026 as a shift from hype to pragmatism, with “physical AI” and on-device intelligence becoming part of everyday products and workflows.  

What’s interesting is what pragmatism tends to reveal. The moment AI leaves the lab and shows up inside products and operations, everything becomes physical and bounded. Latency matters. Power matters. Thermal limits matter. Reliability matters. And suddenly, the story isn’t only about intelligence, but about the system that can sustain it. That’s where semiconductors stop being infrastructure in the background and start becoming the pacing factor again.

Forbes points towards agentic AI as a defining theme for 2026, with systems that don’t just respond but take on bounded tasks and coordinate work. That future is exciting, but it also raises the bar. Agents only create value when they’re deeply integrated, auditable, and trustworthy enough to run alongside humans. When that becomes the baseline expectation, the chips beneath those agents need to evolve right along with them.

From the Moores Lab AI lens, the prediction we’re most confident in is simple, and the winners in 2026 won’t just have smarter models. They’ll have faster feedback loops across the whole stack, from software down to silicon, so new ideas can become real systems without getting stuck in slow and expensive bottlenecks. That’s the difference between AI as a headline and AI as an era.