Last week, the Computing Community Consortium (CCC) hosted the AI Research Ecosystem (AIRE) Workshop at The Chaminade Resort in Santa Cruz, CA. Held from October 13-15, 2026, the workshop brought together 34 non-organizer experts from academia, industry, national labs, and government to examine the pressures facing AI research today and develop recommendations for a stronger, more sustainable research ecosystem. Working alongside CCC staff, the workshop was organized by Vandana Janeja (University of Maryland Baltimore County), Manish Parashar (University of Utah), Abhishek Bhattacharjee (Princeton University), Edith Elkind (Northwestern University), David Jensen (University of Massachusetts Amherst), William (Bill) Regli (University of Maryland), and Michela Taufer (University of Tennessee Knoxville). The workshop builds […]

The Computing Community Consortium’s (CCC) latest report, Beyond Code: Engineering Trustworthy Software Systems with AI at Scale, examines what happens to software engineering as AI takes over most of the work of writing code. Between 84% and 90% of developers now use these tools. The report is primarily addressed to researchers, but several of its findings describe conditions that research alone cannot resolve. Beyond Code: Engineering Trustworthy Software Systems with AI at Scale was authored by Randal Burns (Johns Hopkins University), Sebastian Elbaum (University of Virginia), Gabrielle Allen (University of Wyoming), Nils Aschenbruck (Osnabrück University), Terry Benzel (University of Southern California), William Gropp (University of Illinois Urbana-Champaign), Rick Kazman (University […]

In mid-October, the Computing Community Consortium (CCC) will convene a visioning workshop designed to define and recommend improvements to the core components of the artificial intelligence research ecosystem (AIRE). The AIRE workshop — led by Manish Parashar (University of Utah), Vandana Janeja (University of Maryland Baltimore County), Abhishek Bhattacharjee (Princeton University), Edith Elkind (Northwestern University), David Jensen (University of Massachusetts Amherst), Jofish Kaye (Inflection AI & CRA-I Council), William Regli (University of Maryland), and Michela Taufer (University of Tennessee Knoxville) — brings together research community leaders to examine how the structures that support AI research, from peer review and publishing to funding and partnerships, can keep pace with a rapidly […]

The Computing Community Consortium’s (CCC) latest report, Beyond Code: Engineering Trustworthy Software Systems with AI at Scale, takes up the question of what has to change in software engineering once implementation is largely automated. With adoption of AI coding tools now reported at 84% to 90% of developers, much of the work shifts to specifying, verifying, and maintaining what AI produces. This report, however, documents a widening gap between what AI-assisted development is expected to deliver and what these systems can currently do — as well as between the sheer amount of code being generated and the current ability to verify it. The report presents a way forward for closing […]

The Computing Community Consortium (CCC) is excited to release a new key recommendations brief drawn from the recent Computing on the Fly: Navigating a Vision for the Future of Drone Computing report. The report lays out a vision for non-military drone infrastructure by 2035 and identifies twelve technical challenges standing in the way. This brief, Key Recommendations for the Future of Drone Computing, outlines the next steps, translating those challenges into specific actions for the four computing communities whose decisions will determine whether that vision is met: scientific funders, policymakers, industry, and academia. Action is urgent to realize the full potential of non-military drones. The report establishes milestones for 2028, […]

The role of the software engineer is fundamentally changing. AI-assisted software development has, in many cases, become a new norm, fostering a demand for unprecedented speed in production. Yet the transition from traditional coding to AI-powered development is not as simple as receiving a boost to productivity. It requires both brand-new skills on the part of the developer and a more fundamental rethinking of how software — especially at scale — is generated. In this rapidly evolving field, new understandings of how to capture user intent, ensure system quality at AI-generative scales, and train the next generation of developers are essential. Beyond Code Report Beyond Code: The Workshop To better […]