Cybersecurity’s Quiet Revolution: What We’re Missing While Chasing the Hype
There’s something happening in cybersecurity right now that’s both exciting and a little disorienting. As generative and agentic AI take over headlines, conference keynotes, and investor decks, it’s easy to assume we’re on the verge of some great leap forward. The reality is more complicated—and more interesting.
In the latest episode of the TechSpective Podcast, I had the chance to sit down with Sachin Jade, Chief Product Officer at Cyware, for a conversation that cuts through the buzzwords. We cover a lot of ground—from AI’s place in the SOC to the underrated power of relevance in threat intelligence—but what stuck with me most was this: the most transformative work happening in security right now doesn’t look like a revolution. It looks like simplification.
Not simplification in the marketing sense—fewer dashboards, “single pane of glass,” etc.—but simplification where it actually matters: filtering noise, streamlining analysis, helping human analysts do their jobs better and faster. There’s a growing recognition among smart security leaders that “flashy” features might demo well, but if they don’t reduce burnout, improve signal-to-noise, or give analysts time back in their day, they’re missing the point.
We’re at a moment where AI can—and should—do more than just surface alerts. The goal isn’t to impress anyone with a cool interface or to simulate a brilliant security expert. The goal is to embed intelligence into the places that grind analysts down: filtering irrelevant threat intel, connecting disparate data points, recommending next steps based on context. Mundane, unsexy tasks—yes. But transformative when done well.
Sachin offered a useful framework for thinking about agentic AI that goes beyond the surface definitions most people are using. We talk about where true decision-making autonomy begins, how it fits into layered workflows, and what it really looks like to “mimic” human reasoning in a SOC environment. Spoiler: it’s not about replacing people. It’s about enabling them.
Another theme that emerged: relevancy. Not in a vague, feel-good way, but in the deeply practical sense of “does this matter to me, my company, my infrastructure, right now?” For all the AI talk, too many tools still struggle to answer that question clearly. Cyware’s approach, which Sachin outlines in the episode, puts a premium on reducing noise and increasing clarity. There’s no magic wand—but there is a very intentional shift toward making intelligence actionable, digestible, and contextual. That matters more than whatever buzzword is trending on social media this week.
We also explore the idea of functional decomposition in AI—a concept that mirrors how most human security teams are structured. Instead of building a monolithic super-intelligent assistant, Cyware has developed a multi-agent model where each AI agent is focused on a specific task, like malware triage or incident correlation. It’s less hive-mind, more specialized team—just like the best human teams. That architectural choice has significant implications for accuracy, explainability, and trust.
The full conversation dives deeper into how these ideas show up in real-world security operations, what CISOs are actually looking for in AI-driven tools, and why strategic use of “boring” automation may be the real game-changer for the next decade.
If you’re someone who’s tired of the AI hype but still deeply curious about where it’s actually moving the needle, I think you’ll find this episode worth your time. We don’t spend 45 minutes tossing around acronyms—we get into how AI can help analysts cut through the clutter, why relevancy is the next frontier, and what it means to design intelligence that works the way humans actually think.
Listen to or watch the full episode here:
