Like jean jackets at a punk rock show, today’s IT pros have way too many patches.

This June, Microsoft released its highest volume of security updates of the year: 208 common vulnerabilities and exposures (CVEs).

The company’s past three months of updates have totaled 542, almost doubling the rate from the 286 in the same period in 2025.

Compare that to 10 years ago, when Microsoft released over 500 CVEs for the whole year.

With AI helping rapidly uncover new vulnerabilities (such as Anthropic’s Project Glasswing), IT teams need more than ever to be ready for dense patch deliveries from vendors.

Sewing it all together.—BH

There’s an old saying, “a gem cannot be polished without friction,” and many in the IT sector hope that the same applies to AI.

What IT pros know as tech friction—the increase in toil and noise that comes from added complexity of the tech stack—is increasing with AI deployment. AI is adding a new layer of difficulty, and it’s one that’s hard to fully understand.

Get it done. In a May report from Harness, an agentic platform provider, researchers found that AI is impacting tech investment and ROI by adding friction to established processes. That raises questions for organizations grappling with appropriate deployment, Trevor Stuart, Harness SVP and GM, told IT Brew.

“What is the overall impact or productivity impact of AI-generated code? Are teams able to effectively monitor this? Are they able to effectively measure that ROI? That’s at the core of the report,” Stuart said.

How much friction is too much?—EH

With AI advancements, software professionals may need to brush up on natural language more than programming ones.

For Feroz Sheikh, chief information and digital officer at agricultural-tech company Syngenta, this supposedly new focus on using natural language to program is a callback to a concept called “literate programming,” introduced more than four decades ago by Stanford researcher Donald Knuth.

With a “literate” development approach, you explain the program in natural language, like an essayist, using both words and code snippets. This forces programmers to concentrate not on instructing a computer, but explaining to humans what a computer can do.

“My programs are not only explained better than ever before; they also are better programs, because the new methodology encourages me to do a better job,” Knuth wrote in a 1984 paper.

Talk to me.—BH

More than half of IT professionals say a lack of clear strategy is their biggest AI and automation challenge. Join IT Brew and Console on July 9 for a practical discussion on modernizing internal support, automating the right requests, and building a foundation that actually scales. Register here.

CollabWORK connects you to the hidden job market through IT Brew and other trusted channels. Browse roles curated specifically for this community by clicking through to the job board.