as bad as things have gotten in the past 4 days, they are going to get a lot worse before they get better. security leaders, never let a crisis go to waste: please go to your boards and ask for help right now. not for ai, for the basics. (we need to hold on for ~18 months.)

My thoughts of late have returned to this amazing scene by @WilliamShatner, made decades ago. As a young person, I found it tremendously inspiring. A code to live by. But it didn’t play out quite like we expected. The “fantastically advanced” life that we actually ended up encountering is right here, on Earth. All around us now. The key issue of our time is becoming this: Not everyone signed up for this mission, or the risk. And what we do about that, ultimately, is where the debate about AI will end up.

There are two approaches to cybersecurity now that we’re in the vulnpolcalypse: 1. “patch the planet” by burning mountains of tokens, red teaming, and patching until you think there are no more exploitable bugs in the software 2. Shrink software components into their most minimal essence, tailor them to a particular system, and then formally verify it Both approches are now enabled by LLMs. But only the second one can be done on a budget and without having access to frontier cyber models like mythos. This is why I’m excited to see more legacy software get boiled down, hardened, and verified

I finally answered the cloud question I usually hate answering: who has the best cloud? My answer: AWS — narrowly, conditionally, and with a lot of caveats. I built a generic scoring model across 20 criteria and applied it to AWS, Microsoft Azure, and Google Cloud. The criteria are an abstraction of what I see every day when I walk clients through cloud provider selection: security, compliance, cost, reliability, compute, storage, databases, networking, AI readiness, hybrid cloud, migration, support, observability, governance, vendor viability, innovation, and the operational realities that show up after the purchase order is signed. The result was close. AWS came out on top at 84.7, Azure followed at 82.7, and Google Cloud landed at 78.9. AWS wins overall because it performs well where the weighting matters most: security, compute, storage, reliability, ecosystem depth, and maturity. Azure is the best answer for many Microsoft-centric enterprises, especially those dealing with compliance, hybrid cloud, identity, and existing enterprise agreements. Google Cloud is the strongest fit for AI-native, data-heavy, and cost-sensitive workloads, and it continues to show real momentum. But the real answer is still the one architects and consultants give whether people like it or not: it depends. In the real world, the answer is almost never one public cloud. It is usually a heterogeneous mix of public cloud providers, private clouds, owned infrastructure, edge computing, SaaS platforms, legacy systems, and whatever else the business has accumulated over the last 20 years. The job is not to crown a vendor and move on. The job is to design the right configuration for the business, the workloads, the compliance model, the skills available, the cost structure, and the future direction of the company. That is why I usually avoid the “best cloud” debate. It oversimplifies a decision that is rarely simple. Still, it was fun to finally put a stake in the ground. If forced to answer the question using broad enterprise criteria, AWS is the best overall public cloud today. Azure may be the better answer for Microsoft-heavy enterprises. Google Cloud may be the better answer for AI, analytics, and data-driven platforms. Same market. Different strengths. One narrow winner. That is my answer, and I am sticking to it.