We made it to 100 episodes, so naturally, we decided to look back and see how wrong we’ve been. In this episode, we revisit some of our past topics, predictions, and hot takes to figure out what still holds up and what didn’t quite land. From “we don’t know what we don’t know” to the evolution of security tools, we reflect on what’s changed, what hasn’t, and why some problems never seem to go away. Along the way, we compare where we were then to where things stand now, calling out a few wins, a few misses, and everything in between. After all this time, are we actually any smarter, or just better at explaining the same problems? This episode is part reflection, part reality check, and a look at what 100 episodes have really taught us.

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In this episode, we dive into the messy reality of AI agents acting inside your systems and what that means for modern security. We explore the idea of agents as actors with real access—credentials, APIs, and permissions—and why this isn’t as new as it sounds (hint: it’s just applications all over again). We unpack where things actually get risky, from over-permissioned agents to unpredictable behavior driven by prompts, and why “it won’t go rogue” might be missing the point entirely. We also question the growing hype around AI governance, whether security teams are actually gaining control or just making more lists, and what happens when agents start talking to each other… and running up your bill. Per usual, the conversation is filled with sarcasm, skepticism, and a healthy dose of “maybe just add parental controls.”

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In this episode, we dive into the strange world of invisible Unicode attacks and what they could mean for modern software security. We explore how hidden characters can be used to conceal malicious code within packages, why this isn’t entirely a new problem, and whether current tools, such as linters and SAST, are equipped to detect it. We also question the role of LLMs in both enabling and detecting these attacks, and whether this is a real emerging threat or just another overhyped security scare. Per usual, the conversation is filled with sarcasm, skepticism, and a healthy dose of “just don’t do it.

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In this episode, we discuss the implications of AI technologies like OpenClaw and Moltbot, exploring the potential threats and societal changes that may arise from their integration into daily life. We talk about the nature of AI communication, the concept of agentic AI, and the philosophical questions surrounding the future of human and machine interaction. Per usual our conversation is laced with humor and skepticism about the rapid advancements in AI and their impact on society.

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Are cybersecurity technologies really dead, or are reports of their demise greatly exaggerated? Today’s episode is a discussion on how AI is reshaping the classic build vs. buy debate, empowering non-engineers to create working prototypes and potentially reviving the DIY coding culture of pre-open-source days. We also talk about how developers trained on open source are now leveraging AI built from that same foundation, raising questions about innovation and originality in modern programming.

Build vs Buy is Dead - AI Just Killed It

Traditional Code Review is Dead

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We’re predicting what 2026 has in store for AI and cybersecurity. We explore the wild possibilities of AI integration gone wrong, from people accidentally connecting their AI to sensitive file systems to blaming their AI agents for losing critical data. The conversation takes a thoughtful turn as they debate which jobs might fall to AI automation and if the human touch is still irreplaceable? Examining real examples like the "Y'allbot" weather monitoring system and photorealistic AI actress Tilly Norwood to illustrate how rapidly AI is transforming industries.Tune in and learn how to navigate the AI-powered future responsibly.

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We’re pulling back the curtain on the technology industry to reveal what life looks like when you're constantly aware of what can go wrong. From the loss of childlike wonder when encountering new tech to the ethical dilemmas posed by autonomous vehicles, we discuss the unique burden of seeing technology's darker possibilities. We’re examining how years of witnessing security breaches and system failures shape a professional outlook that balances innovation with caution.

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What do roller coasters and threat modeling have in common? More than you'd think. In this episode, we explore how security professionals view risk differently than everyone else—and why that matters. From roller coaster anxiety to the ethics of identifying danger, we dive into the unique mindset that comes with being a threat modeler. Because once you learn to see threats everywhere, there's no going back.

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