Software Engineering Institute (SEI) Podcast Series

Artificial intelligence (AI) is a transformational technology, but it has limitations in challenging operational settings. Researchers in the AI Division of the Carnegie Mellon University Software Engineering Institute (SEI) work to deliver reliable and secure AI capabilities to warfighters in mission-critical environments. In our latest podcast, Matt Gaston, director of the SEI’s AI Division, sits down with Matt Butkovic, technical director of the SEI CERT Division’s Cyber Risk and Resilience program, to discuss the SEI's ongoing and future work in AI, including test and evaluation, the importance of gaining hands-on experience with AI systems, and why government needs to continue partnering with industry to spur innovation in national defense.

A recent Google survey found that many developers felt comfortable using the Rust programming language in two months or less. Yet barriers to Rust adoption remain, particularly in safety-critical systems, where features such as memory and processing power are in short supply and compliance with regulations is mandatory. In our latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Vaughn Coates, an engineer in the SEI’s Software Solutions Division, sits down with Joe Yankel, initiative Lead of the DevSecOps Innovations team at the SEI, to discuss the barriers and benefits of Rust adoption.

In response to Executive Order (EO) 14028, Improving the Nation’s Cybersecurity, the National Institute of Standards and Technology (NIST) recommended 11 practices for software verification. Threat modeling is at the top of the list. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Natasha Shevchenko and Alex Vesey, both engineers with the SEI’s CERT Division, sit down with Timothy Chick, technical manager of CERT’s Applied Systems Group, to discuss how threat modeling can be used to protect software-intensive systems from attack. Specifically, they explore how threat models can guide system requirements, system design, and operational choices to identify and mitigate threats.

Container images are increasingly being used as the main method for software deployment, so ensuring the reproducibility of container images is becoming a critical step in protecting the software supply chain. However, in practice builds are often not reproducible due to elements of the build environment that rely on nondeterministic factors such as timestamps and external dependencies. Lack of reproducibility can lead to lack of trust, broken builds, and possibly mask hidden malware insertion. Vessel, a recent tool from the Carnegie Mellon University Software Institute (SEI), helps developers identify the difference between two container images to help sort benign from problematic issues. In this SEI Podcast, Kevin Pitstick, a senior software engineer at the SEI and Vessel’s lead developer, and Lihan Zhan, a software engineer at the SEI working on tactical and AI-enabled systems, sit down with Grace Lewis, lead of the Tactical and AI-Enabled Systems (TAS) applied research and development team at the SEI, to discuss the Vessel tool, its development, and application in mission-critical settings.

Software enables our way of life, but market forces have sidelined security concerns leaving systems vulnerable to attack. Fixing this problem will require the software industry to develop an initial standard for creating software that is secure by design. These are the findings of a recently released paper coauthored by Greg Touhill, director of the Software Engineering Institute (SEI) CERT Division. In this latest SEI podcast, Touhill and Matthew Butkovic, director of Cyber Risk and Resilience at CERT, discuss the paper including its recommendations for making software secure by design.

A January 2025 Defense Innovation Board study on scaling nontraditional defense innovation stated, “We must act swiftly to ensure the DoD leads in global innovation and competition over AI and autonomous systems – and is a trendsetter for their responsible use in modern warfare." In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), chief technical officer Tom Longstaff discusses the SEI’s long-standing work to help the DoD rapidly scale technology including artificial intelligence (AI) and autonomous systems.

Warfighters in the Department of Defense (DoD) operate in high-stakes environments where security, efficiency, and speed are critical. In such environments DevSecOps has become crucial in the drive toward modernization and overall mission success. A recent study led by researchers at the Carnegie Mellon University Software Engineering Institute (SEI) examined the state of DevSecOps within the Department of Defense. In this podcast, Eileen Wrubel, the SEI’s Transforming Software Acquisition Policy and Practice technical director, sits down with George Lamb, director for DoD Cloud and Software Modernization in the Information Enterprise Office of the DoD CIO, which is responsible for the DoD Software Modernization Strategy and its associated implementation plan, and Bill Nichols, lead of the SEI’s Software Engineering Measurement and Analysis work. They discuss DevSecOps successes in the DoD and opportunities for scaling its impact.

Deploying cloud-centric technologies such as Kubernetes in edge environments poses challenges, especially for mission-critical defense systems. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Patrick Earl, Doug Reynolds, and Jeffrey Hamed, all DevOps engineers in the SEI's Software Solutions Division, sit down with senior reesearcher Jose Morales to discuss a recent case study involving the deployment of a hypervisor onto edge devices in a resource-constrained environment.

A strong cyber defense is vital to public- and private-sector activities in the United States. In 2019, in response to an executive order to strengthen America’s cybersecurity workforce, the Department of Homeland Security’s Cybersecurity and Infrastructure Security Agency (CISA) partnered with the SEI to develop and run the President’s Cup Cybersecurity Competition, a national cyber competition that identifies and rewards the best cybersecurity talent in the federal workforce. In six years, more than 8,000 people have taken part in the President’s Cup. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Jarrett Booz, technical lead for the President’s Cup, and John DiRicco, a training specialist in the SEI’s CERT Division, sit down with Matthew Butkovic, the CERT technical director of cyber risk and resilience, to reflect on six years of hosting the cup, including challenges, lessons learned, the path forward, and publicly available resources.

Bringing a codebase into compliance with the SEI CERT Coding Standards, requires a cost of time and effort, namely in the form of a static analysis tool. But those who are familiar with static analysis tools know that the alerts are not always reliable and produce false positives that must be detected and disregarded. This year, we plan on making some exciting updates to the SEI CERT C Coding Standard to better harmonize with the current state of the art for static analysis tools, as well as simplify the process of source code security auditing. In this podcast David Svoboda and Joseph Sible, both engineers in CERT’s Applied Systems Group and primary developers and maintainers of the standard, sit down with Robert Schiela, deputy technical director of the Cybersecurity Foundations team in CERT, to discuss the proposed changes, specifically in the area of risk assessment.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Gregory Touhill, director of the SEI CERT Division, sits down with Matthew Butkovic, technical director of Cyber Risk and Resilience at CERT, to discuss ways in which CERT researchers and technologists are working to deliver rapid capability to warfighters in the Department of Defense.

Insider incidents cause around 35 percent of data breaches, creating financial and security risks for organizations. In this podcast from the Carnegie Mellon University Software Engineering Institute, Austin Whisnant and Dan Costa discuss the Insider Incident Data Expression Standard (IIDES), a new schema for collecting and sharing data about insider incidents. IIDES facilitates insider incident information handling to help organizations better protect themselves against the compromise of sensitive information and mission-critical systems, which is essential to maintaining national security and defense.

Grace Lewis, a principal researcher at the Carnegie Mellon University Software Engineering Institute (SEI) and lead of the SEI’s Tactical and AI-Enabled Systems Initiative, was elected the 2026 president of the IEEE Computer Society (CS), the largest community of computer scientists and engineers, with more than 370,000 members around the world. In this SEI podcast, Lewis sits down with Ipek Ozkaya, technical director of Engineering Intelligent Software Systems, to discuss her vision and plans for the IEEE CS presidency.

Machine learning (ML) models commonly experience issues when integrated into production systems. In this podcast, researchers from the Carnegie Mellon University Software Engineering Institute and the U.S. Army AI Integration Center (AI2C) discuss Machine Learning Test and Evaluation (MLTE), a new tool that provides a process and infrastructure for ML test and evaluation. MLTE can aid organizations across the DoD in more effectively negotiating, documenting, and evaluating model and system qualities.

As software size, complexity, and interconnectedness has grown, software modernization within the Department of Defense (DoD) has become more important than ever. In this discussion moderated by Matthew Butkovic, technical director of risk and resilience in the SEI CERT Division, SEI director Paul Nielsen outlines the SEI’s work with the DoD on software modernization, including controlling the attack surface, incorporating industry practices such as DevSecOps, and the interplay between software, cybersecurity, and AI.

Containerization allows developers to run individual software applications in an isolated, controlled, repeatable way. With the increasing prevalence of cloud computing environments, containers are providing more and more of their underlying architecture. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Sasank Venkata Vishnubhatla and Maxwell Trdina, both engineers in the SEI CERT Division, sit down with Tim Chick, technical manager of the Applied Systems Group, to explore issues surrounding containerization, including recent vulnerabilities.

Software cost estimation is an important first step when beginning a project. It addresses important questions regarding budget, staffing, scheduling, and determining if the current environment will support the project. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Anandi Hira, a data scientist on the SEI’s Software Engineering Measurement and Analysis team sits down with Bill Nichols, principal engineer and SEI data science team lead, to discuss software cost estimation including various metrics, best practices, and common challenges when developing or building a model.

One of the biggest challenges in collecting cybersecurity metrics is scoping down objectives and determining what kinds of data to gather. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Bill Nichols, who leads the SEI’s Software Engineering Measurements and Analysis Group, discusses the importance of cybersecurity measurement, what kinds of measurements are used in cybersecurity, and what those metrics can tell us about cyber systems.

To make secure software by design a reality, engineers must intentionally build security throughout the software development lifecycle. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Timothy A. Chick, technical manager of the Applied Systems Group in the SEI’s CERT Division, discusses building, designing, and operating secure systems.

Harmful biases in large language models (LLMs) make AI less trustworthy and secure. Auditing for biases can help identify potential solutions and develop better guardrails to make AI safer. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Katie Robinson and Violet Turri, researchers in the SEI’s AI Division, discuss their recent work using role-playing game scenarios to identify biases in LLMs.