Future Cybersecurity: Hardware Memory Safety, Automated Governance and Post-Quantum Cryptography

Rachel Lee Nabors, former React core team member, dives into the architecture and philosophy behind local-first applications, exploring how small language models (SLMs) running directly on-device can deliver privacy-focused, low-latency, and cost-effective alternatives to cloud-hosted LLM wrappers. Rachel shares key insights on evaluating models with golden datasets and leveraging client-side AI for moderation and social content aggregation.

In this podcast, Michael Stiefel spoke to Joy Ebertz about how the use of artificial intelligence is changing the way architects and developers do their jobs. Focusing on the long term success of the business is one of the most neglected tasks of an architect. This task becomes particularly important as the nature of artificial intelligence changes the landscape of software development. Architects must be especially aware of requirements and their inherent ambiguity. More than ever, they must be expert at explaining technology to the business people, and the business to the technology people. On the flip side, goals must be clearly explained to AI agents, and tests must be unambiguously written. Industry practice is uncertain on how to incorporate changes due to bug reports or new requirements. Should it be done incrementally, or should the module’s or application’s code base be regenerated? This is especially challenging in existing systems, especially old ones where nobody knows what the real requirements were. Unambiguous requirements definition may turn out to be the gating factor in AI driven software development because code reviews seem not to be effective, and verification of the AI work is a great burden.

In this podcast, Michael Stiefel spoke to Erin Doyle about how artificial intelligence tools are transforming the software development process, and how they are affecting software engineers. Architecture skills are now critical because engineers need to understand how to build systems and handle the constraints and associated ambiguity in the requirements. At the same time, given the rapid change both in the nature of the AI tools, and the amount of code they can produce which can overwhelm developers, psychological safety becomes essential for successful AI adoption. Teams need a secure, non-judgmental environment to share their successes, admit failures, ask for help, and express skepticism.

In this episode, a panel of AI experts, Meryem Arik (DoubleWord), Clara Higuera Cabañes (BBVA), and Jeff Smith (C Proof), demystify the current state of AI in the enterprise. The discussion navigates the "industrial revolution" moment in AI adoption, exploring why companies are rushing toward these technologies to maintain competitive advantages while grappling with reliability, ethical considerations, and the evolving role of software engineering.

In this episode, Sahil Agarwal talks about the critical challenges of identity, authorisation, and security in the age of AI agents. Sahil introduces the DPACT framework (Delegation, Policy, Auditability, Context, and Time) as a blueprint for building responsible, guardrailed agentic systems, moving away from simple token-based access toward bounded, delegated authority.