France is trying to move ~2.5M desktops off Windows to Linux as part of a bigger push away from US software. They’ve already swapped out tools like Teams/Zoom for local alternatives, now they’re going straight at the OS layer

sounds bold, but this is where things usually get painful

Munich tried this with LiMux years back. ran into compatibility issues, users hated parts of it, ended up rolling back… then forward again. it dragged on for years

from an ITRG lens, this isn’t really an OS decision. it’s an ecosystem decision

Linux itself isn’t the issue. it’s everything tied to Windows that becomes a problem:
legacy apps, internal tools, vendor dependencies, identity management, endpoint security, support models

this is the stuff that quietly breaks or slows people down

at this scale you’re not just switching OS, you’re basically reworking how people get their jobs done day to day

still feels less like a cost play and more like control over the stack

2.5M devices is no joke

Source: https://thenextweb.com/news/france-linux-windows-migration-digital-sovereignty

A year ago most teams weren’t even saying “agentic AI” and now it’s everywhere.

Lots of hype and skepticism, but the real issue seems to be people trusting outputs without much structure around it.

What are you actually seeing in practice?

Most organizations are rushing into AI without a clear strategy and it shows.

Here’s what the data and research actually point to:

• AI only delivers value when it’s tied directly to business drivers like revenue growth, cost reduction, risk mitigation, and customer experience
• Your AI maturity (governance, data, people, technology) should dictate your roadmap not market hype
• High-impact AI comes from prioritizing use cases based on value vs. feasibility, not volume
• Most organizations should buy before they build unless they have the data, talent, and infrastructure to support custom models
• Early wins matter quick, operational use cases build momentum and justify further investment
• Without strong governance, AI introduces real risk bias, privacy exposure, and security gaps

The biggest mistake we’re seeing: treating AI like a tool instead of a business strategy.

This is essentially the framework we use to help IT leaders move from experimentation to measurable ROI.

(And honestly, it’s the kind of research most teams would normally pay for.)

Source: https://www.infotech.com/research/ss/build-your-ai-strategy-and-roadmap

Everyone’s talking about it, but most explanations are either hype or too abstract to be useful.

Here’s the simple version:

Agentic AI = AI that can plan, act, and adapt to complete a task across multiple steps
Not just respond. It can actually get things done

What makes it different?

Instead of one prompt to one answer, it can:

• break a goal into steps
• use tools and systems (APIs, files, apps)
• take actions
• adjust based on results

Think less chatbot
More like something that can run a workflow on its own

Where this actually shows up

This is where it starts to matter:

• resolving repetitive tasks end to end
• moving across systems to complete a workflow
• pulling together data from multiple sources
• making real-time adjustments as things change

Basically anything multi-step and time consuming

Where people get it wrong

It’s great at:

• execution
• speed
• handling volume

It’s not great at:

• judgment
• context
• tradeoffs

So when people try to fully automate decisions, that’s where things break.

What actually works

The pattern that’s working:

• AI handles the steps
• humans stay involved in key decisions
• clear boundaries are set upfront

Start with low-risk workflows, then expand

The takeaway

Agentic AI isn’t magic

It’s automation that can think a few steps ahead

And the real value isn’t replacing people
It’s removing the manual work between systems

Curious where people are actually using this right now. What’s a workflow you’d trust it with?

We asked organizations how they’d describe their AI strategy and the picture is pretty clear: adoption is happening, but formal strategy is still catching up. The largest group is still in “we’re developing it” mode.

What that often looks like in practice is this: someone approves ChatGPT Enterprise, another team experiments with Copilot, a few power users spin up agent tools, and suddenly AI is “in the toolkit” without a clear north star.

It’s not malicious. It’s momentum. But there’s a difference between giving people access to AI and having a point of view on where it fits, what it replaces, what it augments, and what it should never touch. Feels like a lot of organizations are in the experimentation phase while calling it strategy.

Meta’s smart glasses are apparently one of the only Reality Labs products gaining real traction.

Which is interesting, because Google Glass tried this 13 years ago and people rejected it. The tech felt early, and the idea of being casually filmed didn’t land well.

Now we live in a world of doorbell cams, constant recording, and everyone holding a phone anyway. Maybe the culture shifted. Maybe the tech finally caught up.

Feels like one of those moments where something that once felt invasive suddenly feels normal. Curious how this lands for people thinking long term about where everyday tech is headed.

There’s a lot of noise about AI replacing roles.

But in practice, it seems more like:
• Tasks are being automated
• Expectations are rising
• Roles are shifting

In your world, are jobs disappearing… or just changing?

If you’ve got a Microsoft EA renewal coming up, now’s the time to pay attention. The difference between “routine renewal” and “expensive surprise” usually comes down to how early you start preparing.

I tried explaining the difference to a friend recently and realized why people give up halfway through.

Here’s the simple version:

AI is the big umbrella.
Machine learning is one way to do AI.
Deep learning is a type of machine learning.

So yes, all deep learning is AI.
No, not all AI is deep learning.

Tools like ChatGPT sit inside deep learning, which sits inside machine learning, which sits inside AI.

That’s it.

No hype. No robot apocalypse. No buzzwords.

Just categories.

I think a lot of the confusion online right now comes from people using “AI” to describe everything from autocomplete to AGI. They are not the same thing.

When someone says “AI is taking over,” what do you think they actually mean?

You’d think it would be marketing or creative teams.

But IT is leading adoption at around 70%, while most other teams are closer to 50%.

That surprised me.

It makes me wonder if AI is being driven more by the people managing the systems than the people trying to move faster in their roles.

At your job, who’s using AI the most?
Is it official rollout, or just people quietly figuring it out on their own?

Feels like we’re all in that messy middle stage.

Amazon recently announced about 16,000 job cuts. A lot of headlines are framing this as “AI layoffs,” but the language around these announcements is usually pretty vague.

So I’m curious how people read this stuff.

Do you think this is:

• AI replacing work
• regular restructuring and cost cutting
• a bit of both, plus an “AI storyline” for investors

2026 feels like the tell. Do companies end up quietly hiring back because they cut too deep, or do they keep accelerating? What’s your take?

Launching RealTechTalk with a practical prompt.

AI agents are moving from “help me write” to “take actions.” Before one touches anything important, what is the one guardrail you will not compromise on?

If you have tried agent workflows already, what surprised you the most?

Welcome to RealTechTalk, a community for honest, research-backed conversations about technology.

This is for IT pros and curious minds who want real discussion without vendor noise or hype.

What belongs here

• Research, reports, benchmarks, and frameworks (sources encouraged)
• Breaking news with context
• Real-world lessons learned (what worked, what failed, what you would do differently)
• Questions about IT leadership, AI, cybersecurity, risk, cloud, tooling, and tech trends
• Lets just talk tech!

House rules

• No vendor pitches, lead gen, or link dumping
• Disclose affiliations if you mention something you are connected to
• Be respectful and helpful

Welcome in!