In aviation, waypoints guide pilots through complex flight plans, providing some structure but maintaining flexibility. Kevin Dooley, a senior Agile transformation leader at the SEI, adopted this concept to solve one of defense acquisition's most persistent challenges: synchronizing dozens of interdependent teams without drowning in administrative noise and overhead. In the latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Dooley, who co-developed the Waypoints Framework with Air Force Major Adam Satterfield, sits down with Eileen Wrubel, SEI technical director for Smart Software Acquisition to discuss Waypoints and how it can help teams visualize their work and own processes so they can start collaborating.

Experimentation and validation of LLM performance is critical when building LLM-driven systems that must reliably deliver a service, from customer service chat bots to intelligence analysis tools. To help teams meet the need for rigorous evaluation methods, a research team in the SEI's AI Division led by Violet Turri has developed the Evaluating Large Language Models (ELM) library, which is built on best practices for LLM evaluation and benchmarking. In the latest episode from the Carnegie Mellon University Software Engineering Institute, Turri sits down with Katie Robinson, a design researcher also in the SEI's AI division, to discuss the ELM library, which turns evaluation from an ad-hoc process into a repeatable, extensible framework.

Data poisoning—where adversaries tamper with training data to corrupt model behavior—poses significant risks as AI adoption expands across critical sectors. Organizations without mechanisms in place to detect or prevent data poisoning are open to an avenue of attack that, once exploited, is difficult to remediate. Machine unlearning and model retraining are not always viable or effective solutions. In today's operational climate, where threat actors look to influence models and degrade the trust of users through incorrect behaviors, preventing data poisoning is more important than ever.

In this episode of the SEI Podcast Series, Julie Lawler and James Cunningham—AI security researchers at Carnegie Mellon University's Software Engineering Institute—discuss the growing threat of data poisoning in AI systems and highlight emerging mitigation strategies, including chain-of-custody controls.