AI is no longer scarce—but most orgs still think like it is. Alex Danco’s latest unpacks what shifts when code becomes labor, not capital. Great read on ops, value creation & the future of “heavy” vs “light” companies: https://alexdanco.com/2025/03/27/scarcity-and-abundance-in-2025/
jdchristopher
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stepdad & husband | Dragos Inc. cyber risk director | STEM do-gooder | SANS Institute instructor | fmr. CTO, researcher, & regulator on ICS security | engineer
Why do so many cybersecurity startups fail? It’s not just execution—it’s misreading the game.
🔹 Find a niche or get crushed.
🔹 Tech ≠ Success: CISOs buy risk reduction, not features.
🔹 Adapt fast or fall behind.
Good discussion here: https://longform.asmartbear.com/startup-drake-equation/
New report from Google combines cyber intel & Gemini in order to show how adversaries are using GenAI. The results are not too surprising— productivity, research, & similar— but interesting to see regardless: https://cloud.google.com/blog/topics/threat-intelligence/adversarial-misuse-generative-ai
🤖 Robots now make up ~10% of South Korea's labor force:
As AI and automation become more intertwined, understanding the skills and knowledge replaced by automation is vital, alongside strategies for enabling workforce evolution.
Ensuring the "human-in-the-loop" is essential for maintaining safety, reliability, and security.
https://www.ibtimes.com/south-korea-robots-workforce-3752293
Now that more enterprises have embraced AI, security teams are… benefitting?
Turns out, productivity is universal as we explore how to apply this technology. Of all the statistics I’m impressed by, seeing an improvement in incident response due to AI is perhaps the most promising of all…
Trust is the entire reason our industry exists— and Schneier, as always, does a great job of breaking down this concept and hits to the heart of where AI needs to improve: we need to be able to trust the models and technology.
https://www.schneier.com/blog/archives/2024/12/trust-issues.html
Trust Issues - Schneier on Security
This essay appeared as a response to Evgeny Morozov in Boston Review‘s forum, “The AI We Deserve.” For a technology that seems startling in its modernity, AI sure has a long history. Google Translate, OpenAI chatbots, and Meta AI image generators are built on decades of advancements in linguistics, signal processing, statistics, and other fields going back to the early days of computing—and, often, on seed funding from the U.S. Department of Defense. But today’s tools are hardly the intentional product of the diverse generations of innovators that came before. We agree with Morozov that the “refuseniks,” as he ...
One of the few use cases for current generation AI is pattern recognition. What better place to use that then in your SOC, where Tier I analysts are bombarded by thousands false-positives and poor processes for resolution?
At last year’s SANS ICS Summit, I held a workshop on cybersecurity regulations over the years. And 2025 is going to be unprecedented.
Pay attention to the trends and prepare your contingency plans (including budgets) for the various requirements you may need to add to your program in the future.
..the clock is ticking for my utility friends still using dial up to avoid additional NERC CIP requirements. If you’ve not been convinced yet, it soon won’t matter as more and more landline capabilities are being replaced.
I’ve spoken at conferences on why we need more diversity — of background, thought, and experiences— in cybersecurity. Over the years, I’ve helped grow teams and individuals alike.
The practices in this article give a good starting point for leaders looking to cultivate better neurodivergent talent: