I don’t have a background in academia, so I’m naturally much less likely to come across new research publications than I am a blog post, conference talk or security write-up.
As more of our industry’s news feeds become awash with thinly veiled marketing, some of the most interesting security work, particularly around AI, is becoming increasingly harder to find through channels I usually follow. I’ve started using the tools available to us today to discover research that someone with my background may otherwise miss.
I also find academic papers harder to consume than most practitioner-focused writing. There’s often a lot of structure, convention and academic machinery around the useful bits I actually care about. At the same time, I’ve become reasonably good at using these tools to learn unfamiliar concepts and turn that material into short podcasts I can listen to.
This page is an attempt to bridge that gap: finding research I’d otherwise miss, stripping away some of the ceremony, and making the actual ideas easier to follow.
The papers are discovered automatically through a number of online sources, but the ones published here are generally hand-picked before being turned into short podcasts using either Qwen3-TTS or ElevenLabs. If it’s here, either I or one of my friends has listened to it before publication. The selection inevitably reflects what we find interesting and useful, so some parts of the industry will get more attention than others due to personal interest (or, in some cases, disinterest—sorry, blockchain).
You can follow new publications through the podcast RSS feed.
The podcasting format is something I’ve been iterating on over the past 12 months. The aim is to explain concepts progressively, so the knowledge needed to understand the paper builds and develops as you listen. It assumes you already have a cybersecurity background, so it won’t spend much time on the basics, but it should use practical examples, anecdotes and metaphors where they make difficult concepts easier to understand.
In spirit, it’s a little like The Phoenix Project: introduce the concepts as they become relevant, rather than front-loading all of the theory.