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Measuring engineering organizations in the age of AI

Engineering leadership is in the middle of a real transition, and most of the leaders I talk to know it. AI has reshaped how software gets built quickly enough that the operating models many of us spent a decade refining no longer fit cleanly, and there is a great deal of serious work happening across the industry to figure out how these models should evolve. The teams I find most impressive right now are the ones treating their operating model as an open question rather than a settled one.

Un-observable AI is Un-trustworthy AI

Recently, someone talked Chipotle’s customer support agent into reversing a linked list – a task completely unrelated to burritos in any way. Screenshots circulated, people laughed, but underneath the joke sat a sharper question. If a production support agent will do that on a public channel, what else will it do that nobody is screenshotting? The bug is funny. The trust gap behind it is not.

Deep AI Investigation for ITOps: What It Is and Why It Matters

Investigation is the most time-consuming and cognitively demanding phase of incident response, and it’s the phase least served by existing tooling. Modern ITOps teams have spent years investing in better detection and alerting. The tools are faster, the dashboards are richer, and anomaly detection keeps improving.

Shadow IT and Discovery AI Blind Spots: What Legacy Tools Miss

Ask three teams what assets exist in your environment, and you’ll get three different answers. Most organizations don’t lack tools. They lack agreement on what actually exists in their environment. Asset, endpoint and cloud data exist — but it’s fragmented, stale and trusted differently by teams across every department and function.

Anthropic Fable 5 & Mythos 5 Suspended AI Risk Revealed!

Your entire AI stack ran on a model that disappeared in three days. The US government issued a directive suspending all access — a few hours' notice, no deprecation window, no roadmap. Launched Tuesday. Gone by Friday. And every enterprise that had built workflows on top of it just found out what the real risk was: not the model itself, but the absence of a governance layer underneath it.

Without Governance, AI Is Just Faster Failure

Kellyn Gorman is a Database and AI Advocate and Engineer at Redgate She's the previous director of Data and AI at Silk, and the Oracle SME in Azure at Microsoft. With a robust background in cloud technology and a passion for promoting its merits and potential, I am thrilled to spearhead conversations and actions that help shape the future of this industry. Kellyn has authored numerous technical books, white papers and solution repositories in GitHub on database, AI and engineering topics.

How Real-Time Lending Decisions Are Improving Through AI

Lending companies are changing fast because of artificial intelligence. In the past, loan decisions could take days or even weeks. Now, many lenders can approve or reject applications in seconds. This shift is mainly driven by better data access, automation, and smarter decision systems. AI helps lenders understand risk more clearly and make decisions in real time. It also improves customer experience by making borrowing faster and simpler.

Why Lawn Care Companies Need Better Operations Management to Scale

Scaling a green industry business looks straightforward until your crew count doubles, and routing slips start vanishing into thin air. Adding more trucks feels like progress, but it often just multiplies the noise without moving the margin needle. True growth requires transitioning from reactive management to absolute field control, shifting your focus from surviving the current season to building repeatable operational equity. Talk about breaking the ceiling of field chaos long term.