Everyone's Buying GPUs. Almost Nobody's Ready to Feed Them. The enterprise AI conversation has a blind spot the size of a data center. Every budget meeting I've sat in over the past 18 months has the same shape: GPU allocation gets 70% of the

The Cloud Repatriation Nobody Expected: Why Enterprise AI Is Pulling Compute Back from the Cloud The original pitch for cloud computing was simple: stop buying servers, rent someone else's. For most workloads over the past fifteen years, that trade worked. But AI infrastructure has rewritten the economics, and

Most enterprise AI projects die quietly. No dramatic failure, no post-mortem email chain. They just... stop. The prototype gets a demo, leadership nods approvingly, and then six months later the Slack channel goes silent and the budget gets reallocated. Roughly 80% of enterprise AI projects fail — double the failure rate

Addy Osmani dropped a piece last week that's been making the rounds: "Comprehension Debt — The Hidden Cost of AI-Generated Code." His thesis is sharp. Teams are shipping AI-generated code faster than anyone can understand it. Tests pass, PRs look clean, and nobody notices the growing gap

The Production Gap: Why Nobody Teaches the Infrastructure That Actually Matters Every bootcamp, CS program, and YouTube tutorial series teaches you how to build features. Almost none of them teach you what happens when those features meet real traffic, real failure modes, and real users who do things you never

The AI CapEx Arms Race Is Coming for Your Cloud Bill The three major cloud providers are spending money like it's going out of style. Oracle is financing a $300 billion deal with OpenAI through $50 billion in stock sales and debt. Google just pledged to double its

On March 3rd, an attacker compromised the Xygeni GitHub Action by poisoning a mutable tag. Every CI runner referencing xygeni/xygeni-action@v5 quietly started executing a reverse shell to a C2 server. The exposure window lasted a week. 137+ repositories were affected. The root cause wasn't exotic. A

The streaming media stack has operated in silos for two decades. Encoding and transcoding happen at the source or in dedicated hardware. Orchestration — ad insertion, CDN routing, audience rules — happens in the cloud. And when anyone wants to apply machine intelligence to video, it happens after the fact: pull the

Originally published on the Presidio blog - sharing here as it captures the current reality around agentic AI in enterprise modernization. The pitch behind agentic application modernization is seductive: deploy agentic AI to continuously modernize your applications. No more episodic transformation projects. No more three-year cycles of delay and crisis.