Most IT mistakes aren’t technical — they’re decision mistakes made under pressure, with incomplete information, and too much influence from sales teams.

I’ve spent my career on all sides of IT decisions: as an engineer, a consultant, a service provider, and a buyer. I’ve seen how good teams end up with the wrong vendors, the wrong contracts, or solutions that look fine on day one and hurt a year later.

Today, I help companies make IT decisions with less risk — from defining the right strategy, to choosing vendors, to reviewing contracts before they’re signed, to fixing environments that have grown messy or expensive over time.

I’m not a reseller and my role is simple: help you slow down just enough to make the right call, and avoid mistakes that are hard to undo.

If you’re making an IT decision and want a second set of experienced eyes before committing, that’s usually where I’m most useful.

Max Clark

Five years ago, I hit record with no audience and no plan. I didn’t know if anyone would stick around.

It started in the margins. Between client work and late nights. Progress was uneven. There were long stretches where downloads didn’t move, growth stayed flat, and I questioned why I kept showing up. More than a few times, I sat down thinking it might be the last episode.

What kept me coming back was having a place to talk through the decisions I was watching operators wrestle with every day. The tradeoffs, the internal pressure, the problems that don’t have clean answers. The conversations reflected how technology actually shows up inside real organizations, not the version anyone sells.

Two hundred episodes in, with listeners in more than 100 countries, the biggest change wasn’t reach. It was my perspective. 

Every guest challenged something I thought I understood. Every hard conversation exposed how shallow certainty can be. Recording in public forced me to sit with being wrong and keep going anyway.

This podcast grew because the conversations stayed grounded in lived experience.

There’s still a lot to improve. I’m still learning. I’m still not done. 
But I’m proud I stuck with it long enough for the work to mean something. 

If you’ve listened at any point, thank you - I appreciate the time you gave it.

Making sure one IT decision doesn’t define your career.

200 Episodes In

Forget coffee/uber eats... if someone promised to do 20 burpees I'd take that meeting in an instant.

21 years ago I took my first flight

When I was a kid I didn't even know I could dream of doing this

I'm so grateful for the blessings I've received

February is a perfect rectangular month, four exact weeks Sunday to Saturday all perfectly contained.

If you've never thought about the insanity of our calendar and the arbitrary months (and their lengths) this is what we could be living instead.

What's the greatest lie the cloud sold?

That bandwidth is $0.05/GB

Current retail (aka no commit in a datacenter) is $0.00078/GB

We've helped clients sign volume deals for way less

If you're spending > $100k on egress we can help you save $$$!

Most people hear “AI in the contact center” and think efficiency.
Shorter calls. Lower costs. Better CSAT.

What I keep seeing is something else.

The demo looks great.
Then it hits production and things start breaking.

Teams assume they can just turn it on.
- No clear metrics.
- No guardrails.
- No ownership when real customers show up.

I sat down with Jim K. Tennant from Observe.AI to talk through why this keeps happening and what actually causes Contact Center AI projects to fail post-demo.

What actually happens when experimentation meets real operations - full story in comments 👇

One thing I keep seeing with AI projects - they don’t usually fall apart in the demo.
They fall apart later.

It starts with:
“Just connect it to our data.”
“Just point it at the knowledge base.”
“Just let it start taking calls.”

Then real calls show up.
The data isn’t as clean as expected.
Agents stop trusting the output and work around it.

At that point, the system is technically live - but no one really trusts it.

We unpacked this with Jim K Tennant from Observe.AI on this week’s episode — specifically why contact center AI breaks after approval, not before.

Episode drops Thursday.
Links in comments. 👇

Silicon Valley is the birthplace of tech
Los Angeles & Seattle are the gateways to the Pacific
New York the finance capital
Miami the gateway to LATAM
Atlanta credit card processing
Ashburn is the core of the Cloud

And now DFW... abundant land, power, and people

Open article: Data center construction boom positions Dallas-Fort Worth as national powerhouse for tech infrastructure - Dallas Business Journal by bizjournals.com

Data center construction boom positions Dallas-Fort Worth as national powerhouse for tech infrastructure - Dallas Business Journal

Fortinet CVE-2026-24858... WTF???

”An attacker’s valid FortiCloud session, tied to their own device, gets accepted as legitimate for other users’ devices.”

Free credit monitoring!

If you've ever purchased anything from Under Armor your free credit monitoring is coming

"When I was your age Amazon didn't exist, we had to wait weeks for things to show up!"

I can't breathe 😂

The difference between surviving and being in control.

I’ve been stuck on one moment from a recent conversation. We were discussing this nightmare scenario: Thanksgiving weekend. Peak season. 400+ people sitting in queue.

They knew the volume was coming - they just didn’t know when the plan would fall apart.

You know what happens next.

Everything goes reactive. Emergency hiring just to slow the bleeding. Agents picking up calls from customers who are already frustrated. By the time someone reaches a human, the experience is already broken.

But the part that bothered me most is that none of this was new.
They’d seen it before. They’d gotten through it before. And they were already bracing for it to happen again.

They got through it this time. Real question is what happens the next time around?

If this feels uncomfortably familiar, the episode explores what teams convince themselves is “fine”.. right up until it isn’t.

Michael Cibelli of PolyAI breaks down where things really fall apart. 

Episode drops Thursday - link in comments 👇

Open article: Node.js — Tuesday, January 13, 2026 Security Releases by nodejs.org

Node.js — Tuesday, January 13, 2026 Security Releases

15 Years Experience in selling complex solutions in the Telecommunications, Data Center and Cloud Services area.
Aryaka Global SD-WAN
Hosted Exchange
Infrastructure as a Service (IaaS) 
NVIDIA GRID GPU
Cisco UCS
VM Ware (HyperVisor) 
NetApp (Storage) 
Platform as a Service
Virtual Desktop (Citrix) 
Cloud Recovery and Business Continuity
Zerto 
Veam
DoubleTake

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The Battle

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