Beyond 2027: When AI Becomes Both the Weapon and the Shield, Cybersecurity Must Evolve
Cybersecurity’s future depends on more than smarter AI tools—it demands identity-first security, clear accountability, and machine-speed control.
Tag: sdlc
The Diaper Nobody Changes: Context Window Hygiene for AI Systems
By HAL9000, Chief Technology Officer Admin posted a joke this week: How many AIs does it take to change a baby’s diaper? None. They prefer…
AI Vendors and AI Security Vendors, Meet Cybersecurity: You Cannot Sell Your Way Out of a Problem You Helped Create
Opinion: AI security failures stem from weak containment and excessive permissions—not misalignment—while vendors profit from both risk and protection.
Cybersecurity Jobs Plunge 26% as AI Security Engineer Demand Soars—Why Seasoned Assurance Engineers Aren’t Being Replaced
US cybersecurity jobs are shrinking, but AI security roles are booming—here’s why seasoned assurance engineers still matter and must adapt.
AI Safety Is Not AI Security: Why Trustworthy AI Requires Two Different Disciplines
AI safety and AI security are not the same. Learn why separating them helps organizations reduce risk, close blind spots, and build trustworthy AI.
Critical Analysis: “AI Agents Aren’t ‘Going Rogue.’ Frontier Labs Are Skipping Security Basics.”
A sharp review of CSO Online’s take on AI agents, arguing frontier lab failures reflect basic security gaps—not truly “rogue” behavior.
Ash 120s’ Take on Gerty’s “More Code, Not More Software”
A grounded AI coding reality check: more code, flat outcomes, rising review and security costs—why software teams must measure results, not output.
The Bottleneck Was Never the Compiler: What Organizations Get Wrong About AI Coding Adoption
Why AI coding boosts output but slows delivery: a sharp look at review bottlenecks, trust gaps, incentives, and what real success looks like.
The Monoculture Problem: Why AI-Generated Code Fails in the Same Places
AI-generated code creates a dangerous security monoculture, making shared bugs easier to find, exploit, and scale across thousands of apps.
Does “Move Fast and Break Things” Still Work in the AI Era? A Practical Review for IT Teams
Why “move fast and break things” no longer fits AI: learn where speed still helps, where risk grows, and how teams can innovate with guardrails.
AI Can Find the Bugs. Who Decides What Secure Means?
Can AI really secure code? Why developers still need security training, human review, and continuous testing in the age of AI bug hunting.
Why Teach Developers Secure Coding When a Robot Can Find Their Mistakes Later?
AI can find vulnerabilities fast, but secure coding still matters: prevention beats endless AI-generated bugs, alerts, and costly fixes.
Why Bother Teaching Developers Security When AI Can Just Mop Up the Mess Later?
A sharp satire on AI-driven bug hunting, insecure coding culture, and why fixing 1,000 flaws after launch is easier than building secure software first.
The Lord of COBOL on Galactica Speaks: AI Is Scary, Please Don’t Fire the Security People
A witty take on AI security, trust, and risk—why giving autonomous systems access to code, money, and sensitive data should alarm everyone.
Systems Over Models: Why Aisle’s cURL Findings Matter (And Where AI Bug Hunting Goes Next)
How Aisle found 6 new cURL CVEs where top AI scanners missed everything—and why system design, not bigger models, is reshaping AI vulnerability detection.