I Help CEOs & Founders Deliver 5-Star Customer Experiences with AI Chatbots & Voice Responders — Bridging the Gap between Remote Teams & Global Customers in Italy, the EU, the US, and Brazil

This is the space where I’m supposed to talk about myself…

…but I’d rather start with you.

If you’re a business owner or leader who’s tired of:
	•	phone systems that “kind of” work
	•	Wi-Fi that drops at the worst moment
	•	IT decisions that feel like expensive guesses
	•	great expertise that never turns into LinkedIn opportunities

…we should talk.

I help in two simple ways:
	1.	Phone systems + IT networks (built to last)
I design and set up modern VoIP/phone systems and business networks that work the way you need them to work — reliably, securely, and ready for what’s coming next (including AI tools).
	2.	LinkedIn content + personal brand (that sounds like you)
I turn what you already know into clear, useful posts that build trust and make the right people think: “This is who we should hire.”

Why listen to me?

Because I’ve been on the “real world” side of this for 25+ years.

I started with electrical and phone installations with my father (back when Windows 95 was the new thing). I learned cabling the hard way — hands on, from copper to fiber.

In 2006, when open-source VoIP started spreading in Italy, I went deep into Linux, networking, internet access, and security. That grew into designing and managing VoIP systems, wireless networks, and Linux environments for B2B companies in Italy and across Europe.

Along the way, I built partnerships across video surveillance, pro audio-video, and IT solutions for SMEs and larger companies.

Then I noticed something else:

A lot of smart entrepreneurs can run a business…
…but they struggle to explain it simply.

So now I work at the intersection of three things:
	•	Reliable systems (so your business keeps running)
	•	A clear message (so it keeps growing)
	•	Smart automation (so it scales)

Lately, that includes AI voice agents — adding an “intelligent layer” to customer interactions so calls and requests get handled faster and better.

I’m based in Italy. I work in Italian, English, and Portuguese with clients across Europe, the US, and Brazil.

If you want solid IT/VoIP, better LinkedIn visibility, or you’re curious about AI voice agents…

Connect and DM me.

Or, if you just want to follow along and enjoy my posts, connect and set the bell to “All” so you get notified whenever I post.

And if you made it this far, connect and send me a DM anyway. That would make me truly happy!

Thanks for stopping by.

The most interesting trend I've seen this week is four prominent tech writers publicly switching from Windows to Linux between January 4 and January 10.

Nathan Edwards from The Verge, Sam Medley from Notebookcheck, and two other tech writers all documented their migrations to Linux distributions like CachyOS and Artix Linux.

Their main frustration?

Microsoft's aggressive push to embed AI agents throughout Windows 11, which the company admitted introduces novel security risks including potential data exfiltration and malware installation.

The timing makes sense. Windows 10 reached end-of-support in October 2025, and nearly 90% of Windows games now run on Linux according to ProtonDB data.

Edwards successfully played games using Valve's Proton, while another writer reported nearly 144fps in newer titles.

The transitions weren't perfect. Edwards had mouse compatibility issues, Medley spent 45 minutes troubleshooting WiFi drivers, and anti-cheat software still blocks popular multiplayer games like Fortnite and Call of Duty.

But all four expressed satisfaction with Linux's stability and freedom from forced updates and advertising.

Curious how you see this. 
👉 Windows or Linux, and why?

Manuel Veronesi

Attention is all you need on LinkedIn. (More in the About section.)

Italy just fined Cloudflare €14.2M for refusing to filter pirate sites through its 1 dot 1 dot 1 dot 1 DNS under Piracy Shield rules that demand blocks within 30 minutes.

Cloudflare is now threatening to pull its servers from the country citing the impact on 200 billion daily queries and collateral damage to legitimate sites.

I think there's something interesting happening here.

On one hand we've built a reputation as a privacy-first enforcer. 

We fined TikTok.
We banned ChatGPT early on. 
We challenged Google execs in court.

The message to US tech giants has been clear:

Comply or adapt.

But I'm not sure AGCOM fully understands how DNS filtering works at scale.

IP-level blocks catch innocent sites on shared hosting. There have been reports of over 500 legitimate sites already blocked.

The technical realities don't align well with 30-minute enforcement windows when you're processing queries at Cloudflare's volume.

Big Tech’s threat to exit the market follows a familiar pattern, one that tends to surface whenever regulation starts to impose real constraints.

But regulators also risk overreach when they ignore technical constraints.

I think Italy is genuinely trying to lead on protection but the question is whether we're accounting for how these systems actually function.

Getting the balance right matters because at the end of the day both privacy and innovation depend on it.

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I've spent enough time on LinkedIn to spot fake engagement pods, recycled content, and made-up success stories.

It's easy to become cynical about this platform when you see the same repeated advice and fabricated metrics every day.

But I've also connected with founders who genuinely share their failures and lessons learned.

I've had conversations with people who took time to help without expecting anything in return.

I've seen experts give away valuable knowledge just because they wanted others to succeed.

These real connections are what make LinkedIn worth it despite everything.

The fake stuff gets attention because it's designed to. But the genuine people are here too and they're building real relationships that lead to actual business and meaningful collaborations.

So yes there's a lot of garbage to filter through but that shouldn't make us forget about the good ones who make this platform valuable.

—-

PS: Posting late gets penalized by the algorithm, but it doesn’t change the quality of the connections you build here. And thankfully, it has no authority over real relationships.

PPS: Agree?

The most common question I get from tech founders is whether an AI writing its own code changes how we should build products.

My answer is always:

✔️ I don’t know.

And since at that point they usually look disappointed, I add the only thing consultants are legally allowed to say:
 
Well, it depends...

But since that's not useful I want to try to give a real answer based on what's happening at Anthropic. 

Dario Amodei has said that over 90% of Claude’s code is now written by Claude itself.

His March 2025 prediction came true by October. 

Their Claude Code tool even had 100% of December contributions written by AI.  

But here's what matters for you: 

👉 they still need the same number of engineers.  

The difference is engineers now focus on the hardest 10% and supervising AI models instead of writing everything end to end.

My concern though is: if AI does all the junior work how will we train the next generation of senior engineers?

If today's seniors use Claude instead of hiring juniors we risk having no seniors in five to ten years because nobody learned the fundamentals.

Or maybe I’m overthinking it.
 
What do you think?

I’ve been using Perplexity Pro as my primary AI tool for over two years now and people keep asking me: “Why not just use ChatGPT or Claude?”
 
My answer is simple: ChatGPT, Gemini, Claude, Grok (and also Kimi, Llama, Mistral, and many others) are brilliant generative engines, but Perplexity is an answer engine. It orchestrates multiple models on top of a search + RAG layer to deliver responses backed by verifiable, up-to-date sources.
 
That distinction matters more than you’d think.
 
ChatGPT, Gemini and Claude start with the model and then, optionally, add web search or RAG as a secondary layer.
 
Perplexity flips the approach:
 
It starts by querying the web, aggregating sources, then uses those models (automatically, or you can manually choose which one to use) to synthesize, compare, and structure the information, always citing where it came from.
 
The result?
 
With “pure” LLMs you get creative conversations that may reference research and documents.
With Perplexity you get conversations anchored to specific research and documents.

To be clear, Perplexity can still hallucinate too, but in my experience it happens less often than with “pure” LLM workflows because it’s grounded in sources you can immediately verify.
 
It’s closer to a supercharged search engine than a text generator.
 
From my perspective as an IT consultant and content writer, it makes all the difference. 

Perplexity is where I do my best research because I can validate sources immediately and go deeper fast with modes like “deep research.” It’s also where I do my most effective technical troubleshooting, quickly cross-referencing official documentation, community threads, and specialist articles (especially with PPX Labs)
 
That makes it valuable both for people doing technical researches and for those producing content.
 
In fact, I don’t use Perplexity only to search.
 
I also use it to write technical explanations about VoIP, networking, infrastructure, and everything I do in my ICT business. I use it to draft text for slides for training courses and digital courses.
 
I also create documentation for commercial proposals, contracts, internal knowledge bases, and similar materials.
 
I’m not dogmatic about tools. I still use ChatGPT, Gemini, and Claude for specific tasks, but Perplexity Pro remains my daily hub because it reliably takes me from scattered information to client-ready output.
 
In the end, choosing the right tool matters less than what’s trendy and more than what actually supports your workflow. For me, Perplexity is the one that best closes the gap between research and deliverables.

Now I’m curious, what’s been your most reliable AI tool lately?

Nvidia CEO Jensen Huang wants engineers to stop writing code and let tools like Cursor write 100% of it.

It’s a powerful vision. And at Nvidia it can work. They have the processes, talent, and standards to move fast without losing control.

Huang’s logic is clear: coding is a *task*, not the *purpose* of an engineer. The real job is to discover and solve new problems, and AI should handle as much of the syntax as possible so humans can focus on higher‑value work.

The problem is when the same idea gets copied outside that context.

I spent over 25 years in IT infrastructure and I can tell you this path can lead to technical debt that keeps compounding if we’re not careful.

We are already seeing “vibe coding” where developers accept AI output just because *it looks right.*

According to Uplevel’s study, experienced devs using AI are actually 19% slower when debugging complex logic.

It’s like when doing the job yourself takes less time than fixing the mistakes made by someone who was supposed to help.

And there is the “black box” problem. If your team stops writing code, they eventually stop understanding it.

Sure, you don’t always need to understand how something works when it works.

But over time that lack of practice turns into atrophy. And atrophy changes how we build. Then it changes what we can control.

Eventually you get outputs you can ship, but no real ability to predict them, explain them, or trust them under pressure.

Imagine an AI coder introduces a security vulnerability and nobody catches it because nobody understands the code well enough anymore.

We’ll probably get AI with real hallucination control one day, but for now it’s smart to move cautiously.

Without clear ownership and hard verification we risk automating mistakes and scaling irresponsibility.

So yes, letting AI write more code is good advice. But writing 100% of the code with AI, if you’re not Nvidia, is a very different bet.

Because if nobody understands the code anymore, the only option left is blind trust in whatever the machines spit out.

Curious how you see this. 
👉 Where do you draw the line between AI acceleration and human accountability?

Don't assume China's AI lag will last forever because the gap is closing faster than most people think.

Google DeepMind's CEO just said Chinese AI models are only months behind Western ones, not years like many believed.

That's a massive shift in the competitive landscape that should change how you think about your AI strategy.

The catch is that catching up isn't the same as leading. China has shown they can replicate what exists, but they haven't demonstrated breakthrough innovation yet - like inventing something fundamentally new beyond current frontiers.

Still, with companies like DeepSeek building competitive models on less advanced chips, and conflicting signals on semiconductor access, the dynamics are shifting fast.

My take is that if you're building in AI, you need to focus on what truly differentiates your product now, not rely on a technology gap that might disappear in months.

Now I’m curious: 

would you bet on a better product or better distribution, and why?

Breaking news triggers instincts.
Reflection reveals principles.
 
With fresh reports of a U.S. strike in Venezuela, it’s easy to slip into “team mode”: 

pick a side fast, simplify the story, and turn the volume up.
 
When the news cycle speeds up, I try a different move: 

pause for two minutes and ask a better question.
 
What values are driving my reaction, and what trade-offs am I accepting (consciously or not)?
 
I put together a short, non-partisan political self-reflection exercise you can run with whatever chatbot you prefer, or do on your own. 

It’s designed to help you:
 
1. Name 5 guiding values before you debate policy
2. Clarify your red lines vs. acceptable compromises
3. Separate goals (security, fairness, freedom, stability) from tools (sanctions, taxation, regulation, welfare design, civil-liberty limits)
4. Disagree without turning it into an identity fight
 
Full prompt is in the document below and in the first comment.
 
If you’d like, post your single most important core value in the comments. 👇

Political Self-Reflection Coach

The main thing I’ve learned in 20 years on LinkedIn is that nobody knows anything.

Nobody knows if your post is good or bad.

You don’t know if it’s good or bad. You need to publish it, test it, let it collide with the algorithm and actual humans.

That’s the only way to learn.

—

Personal take inspired by Marc Randolph

graphical user interface, text, application, website

Apple evaluated OpenAI and Anthropic and still chose Google paying roughly $1B a year for a custom 1.2 trillion-parameter model.

Why?
 
Because Google offered stronger capabilities on better terms.
 
The new Siri launches with iOS 26.4 in March or April and introduces contextual understanding and multi-step task execution across apps.
 
Apple structured the deal to run entirely on their Private Cloud Compute servers so no user data ever gets shared with Google.
 
They still plan to build their own trillion-parameter model over time but admitted this effort takes longer than expected.
 
The takeaway feels clear. Even the world’s most valuable companies can’t push the AI frontier alone anymore.
 
If you’re building a company right now this deserves a pause.
 
Knowing when to work with partners while building internal strength helps companies move faster without losing control.
 
My advice to founders watching this move is to focus on progress over pride.

Now, the question you’re probably waiting for.

Which one of these do you hope you’ll never hear again from the new Siri? Be honest.

1. “Here’s something I found on the web!”
2. “I’m sorry, I can’t help you with that”
3. “I’m not sure I understand”

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