The ITF World 2026 keynote in Antwerp was not a roadmap preview. Imec CEO Patrick Vandenameele used it to name the actual bottleneck on AI scaling: not transistors, not process nodes, but the absence of coordinated optimization across the foundry, fabless, EDA, equipment, and hyperscaler layers. Rani Borkar, president of Azure hardware systems at Microsoft, reinforced this from the buyer side: "We are moving into a world that is multi-modal and multi-model. There is no one model." Chips designed to a single workload profile are being designed to a target that will not exist by tape-out.
The mechanism imec is describing is a coordination failure, not a physics failure. Today, foundries optimize process nodes independently of the EDA tools that will run on those nodes, and independently of the AI architectures that will run on those chips. Each layer is competent; the stack as a whole is not co-optimized. What imec offers - as a neutral precompetitive research site with access to every process generation and relationships across EDA vendors, foundries, and hyperscalers - is a coordination substrate. The CFET roadmap through 2033 and 2D semiconductor materials through 2041 (covered earlier this week from IEEE Spectrum) are outputs of that coordination. The deeper product is the methodology for co-optimization across layers that individual companies cannot do alone.
Vertically integrated players (Google with TPU, AWS with Trainium, NVIDIA with its full-stack platform) already have internal co-design loops that close across architecture, silicon, and systems. Fabless teams without hyperscaler relationships or foundry co-development agreements are designing in the dark relative to the workload trajectory. The 12-18 month implication: fabless AI silicon vendors who want competitive positioning in 2028 need co-design agreements in place now, while TSMC's 2nm and 1.6nm capacity windows are still being allocated.