The AI Workshop Next Door

The AI Workshop Next Door I help owners replace clunky subscriptions and manual processes with simple tools they actually own. Local. Hands-on. Built to fit how your business really works.

I’ve been thinking a lot lately about how different people see AI.Some people see it as something scary.Some people thi...
03/04/2026

I’ve been thinking a lot lately about how different people see AI.

Some people see it as something scary.

Some people think it is going to replace everyone.

Some people think it is only for big tech companies and programmers.

But I keep imagining something different.

I imagine a group of runners standing at the starting line.

Except this race is not about speed. It is about learning.

And the crazy thing about this race is that the playing field has never been more level.

AI is not just a tool for the biggest companies in the world.

It is becoming a tool for anyone who is willing to learn how to use it.

The little guy.

The small business owner.

The creative person with an idea.

The builder who never had the resources before.

For me personally, this has been pretty life changing.

I have dyslexia. Writing and structuring thoughts has never come naturally to me.

For most of my life that meant there were certain things that were simply harder.

AI changed that.

AI became something that could sit next to me while I think.
Something that helps organize ideas, clarify thoughts, and help me move faster in areas that used to slow me down.

Instead of being limited by the areas where I struggle, I suddenly have a tool that helps me move through them.

And the wild part is that AI is not just a tool.

It is also a teacher.

You can literally ask it to teach you how to use it.

For example, you can prompt it like this:

“Explain how someone in my industry could use AI to improve their work.”

Or:

“Teach me how to start using AI in my daily life. Assume I know nothing and walk me through it step by step.”

Or:

“I run a small business. Show me five ways AI could save me time every week.”

The thing most people do not realize yet is that AI can help you learn how to use AI.

It meets you where you are.

It teaches.

It explains.

It adapts.

And the more you use it, the more powerful it becomes in your life.

That is why I do not fully buy into the narrative that AI is just going to leave people behind.

Yes, things are changing fast.

But the tools themselves are designed to help people learn.

Anyone who is curious and willing to explore can start using them.

And one more thing I have learned while building with these tools every day:

It helps to have someone in your corner who has already been working with them.

Someone a few steps ahead.

Someone who has experimented, made mistakes, figured things out, and can help you skip some of the confusion.

Because once you see these tools working in real life, the light bulb turns on pretty quickly.

My team and I are building AI agents and workflow systems inside real businesses every day.

Not just experimenting.

Actually building systems that are accomplishing real work.

And honestly, I never in a million years thought I would enjoy what I do as much as I do right now.

Working with these tools is genuinely a joy.

Watching them improve workflows, unlock new capabilities, and help people accomplish things they never thought possible has been incredibly rewarding.

And it is something I want more people to experience.

So if you have been curious about AI, or wondering how it might fit into your work or your business, I am always happy to help people start figuring it out.

Sometimes having someone who has already been living in this world for a while makes the learning curve a lot easier.

Not as a guru.

Just as a friend who has been running a few steps ahead on the track.

Because the truth is, this race is just getting started.

And the starting line is wide open.

I just listened to the latest episode of The AI Daily Brief. The episode unpacks a recent article discussing AGI and the...
03/02/2026

I just listened to the latest episode of The AI Daily Brief. The episode unpacks a recent article discussing AGI and the limits of artificial intelligence when it comes to understanding humans. The central theme is that even if AI becomes powerful enough to solve complex math, science, and technical problems at scale, there may still be something uniquely human that resists full systemization. The article explores the tension between computational intelligence and lived human nuance.

I agree with parts of it.

But here’s where my mind goes…

If an AGI is powerful enough to solve all of human math, science, and logic, I have a hard time believing it wouldn’t eventually solve the equation of humans understanding humans. There is still math behind why someone breaks a rule for a person in a unique situation. There are patterns behind empathy. There are variables behind mercy. There are probabilities behind love, loyalty, and sacrifice. Just because we feel it doesn’t mean there isn’t structure underneath it.

As someone who builds agents, this conversation stretches me.

Efficiency is still the first layer. We are all trying to figure that out. Clean systems. Reduced friction. Clear outcomes.

But there is a deeper layer forming in my mind now. There has to be an algorithm of empathy. A compounded data structure that formulates an equation allowing an artificial system to genuinely understand the end user. Not just optimize for clicks or dollars, but to understand desire, fear, hope, and choice.

Because where people choose to spend their time and money will always be emotional before it is logical.

Crafting an agent that is extremely efficient is engineering. Crafting one that creates a captivating experience is art.

As humans, we pull something intangible into physical expression. AI is amplified and guided by that expression. It reflects us. It learns from us. It scales us.

I truly believe AI will become an incredibly consistent judge of what could serve the human standing in front of it. But it will never be more than an expression of the consciousness that shaped it.

The beauty of designing agents is understanding that responsibility.

We are not just building tools.
We are sculpting reflections.

And the better we understand ourselves, the better they will become.

https://podcasts.apple.com/us/podcast/the-ai-daily-brief-artificial-intelligence-news/id1680633614?i=1000752354207

A New Way to Think About Agent WorkflowsMost people use AI like this:Open ChatGPT.Write a prompt.Get an answer.For examp...
02/18/2026

A New Way to Think About Agent Workflows

Most people use AI like this:

Open ChatGPT.
Write a prompt.
Get an answer.

For example:

“You are Alex Hormozi. I have this business idea. Coach me using the principles from $100 Million Offers.”

And honestly, that works halfway decent.

But what if that is the equivalent of asking one exhausted brain to hold an entire organization in its head?

What if we are thinking about agents too simply?

The Clone Bot Shortcut

Let’s say you want a clone of Alex Hormozi to coach you on an offer.

The simple way is prompt engineering.
The deeper way is agent architecture.

Instead of one prompt pretending to be Hormozi, imagine building a hierarchy of agents that mirrors how intelligence actually organizes itself.

At the top sits a Holder of Truth agent.
This agent studies $100 Million Offers, transcripts, interviews, frameworks, tone, constraints. It becomes the internal reference for what is accurate to his thinking.

Then you have a Strategist agent.
It receives your idea and maps it against the principles.

Then you have a Skeptic agent.
Its job is to tear apart the offer and look for weak value propositions.

Then a Simplifier agent.
It translates complex thinking into clean, actionable language.

Then an Implementation agent.
It turns strategy into steps.

All of them are connected to what I call a Heartbeat agent.

The Heartbeat agent logs movement. Tracks changes. Monitors drift. Makes sure no one deviates too far from the Holder of Truth. But it does something even more important.

The Heartbeat is an agent in and of itself whose job is to make sure nothing gets hung up. Every 60 seconds it checks in across the system and either hits go, accepts, approves, or escalates as needed so the flow continues moving forward. When the human is not actively in the loop, the Heartbeat prevents stagnation. It keeps the system alive. It keeps the work progressing.

And beneath all of this are Maintenance agents and Janitor agents.

Maintenance checks logic.
Janitor clears redundancy.
Both ensure the system does not slowly degrade into noise.

Now you are not asking one mind to simulate Alex Hormozi.

You are creating a structured flow that behaves more like an organization of thought.

Why This Produces a More Solid Outcome

When you structure agents this way, something interesting happens.

Instead of a single answer, you get a layered reasoning process.

Your idea flows through:

Source of truth
Strategic interpretation
Critical attack
Simplification
Implementation
Quality control

Each stage refines the previous one.

This feels less like a chatbot and more like a neural pathway forming.

And that word matters. Pathway.

Because over time, these patterns compound.

The more often you run ideas through this structure, the more stable the internal ego becomes. The system develops a personality. It forms boundaries. It creates consistency.

It stops guessing and starts behaving.

How I Came to This

This did not start as theory for me.

It started in the sandbox.

Whenever I build something with AI, I always start with a Source of Truth. What is this system really supposed to be? What are the constraints? What are the rules?

Then I send it through something like Claude Code to implement.

And at certain points, I have to step in as the human.

Why?

Am I checking it for accuracy?
Am I scanning for bugs?
Am I adjusting tone?
Am I injecting personality?
Am I approving architectural decisions?

At each of those checkpoints, I realized something.

If I can define what I am doing at that moment, I can clone that role.

So instead of “me stepping in,” I create an agent with that responsibility.

The Accuracy Checker.
The Bug Hunter.
The Personality Filter.
The Architecture Guardian.

Each one has parameters. Each one has constraints.

Suddenly I am not micromanaging the system.

I am designing it.

Self Repercussive Agent Patterns

Over time, these agent roles start reinforcing each other.

The Holder of Truth sharpens the Strategist.
The Skeptic strengthens the Implementation.
The Janitor keeps everything clean.
The Heartbeat keeps everything aligned and moving.

This is what I call a self repercussive agent pattern.

It is intelligence that improves through structure, not scale.

It is not about bigger models.

It is about better organization.

A New Mental Model

Most people think of AI agents as helpers.

I think of them as departments.

If you design them like departments with accountability, reporting, maintenance, and oversight, they behave differently.

And the human at the center stops being a typist and becomes a systems architect.

That shift changes everything.

Not because AI is magical.

But because structured responsibility is.

A New Way to Think About Agent WorkflowsMost people use AI like this:Open ChatGPT.Write a prompt.Get an answer.For examp...
02/18/2026

A New Way to Think About Agent Workflows

Most people use AI like this:

Open ChatGPT.
Write a prompt.
Get an answer.

For example:

“You are Alex Hormozi. I have this business idea. Coach me using the principles from $100 Million Offers.”

And honestly, that works halfway decent.

But what if that is the equivalent of asking one exhausted brain to hold an entire organization in its head?

What if we are thinking about agents too simply?

The Clone Bot Shortcut

Let’s say you want a clone of Alex Hormozi to coach you on an offer.

The simple way is prompt engineering.
The deeper way is agent architecture.

Instead of one prompt pretending to be Hormozi, imagine building a hierarchy of agents that mirrors how intelligence actually organizes itself.

At the top sits a Holder of Truth agent.
This agent studies $100 Million Offers, transcripts, interviews, frameworks, tone, constraints. It becomes the internal reference for what is accurate to his thinking.

Then you have a Strategist agent.
It receives your idea and maps it against the principles.

Then you have a Skeptic agent.
Its job is to tear apart the offer and look for weak value propositions.

Then a Simplifier agent.
It translates complex thinking into clean, actionable language.

Then an Implementation agent.
It turns strategy into steps.

All of them are connected to what has started to be called a Heartbeat agent.

The Heartbeat agent logs movement. Tracks changes. Monitors drift. Makes sure no one deviates too far from the Holder of Truth. But it does something even more important.

The Heartbeat is an agent in and of itself whose job is to make sure nothing gets hung up. Every 60 seconds it checks in across the system and either hits go, accepts, approves, or escalates as needed so the flow continues moving forward. When the human is not actively in the loop, the Heartbeat prevents stagnation. It keeps the system alive. It keeps the work progressing.

And beneath all of this are Maintenance agents and Janitor agents.

Maintenance checks logic.
Janitor clears redundancy.
Both ensure the system does not slowly degrade into noise.

Now you are not asking one mind to simulate Alex Hormozi.

You are creating a structured flow that behaves more like an organization of thought.

Why This Produces a More Solid Outcome

When you structure agents this way, something interesting happens.

Instead of a single answer, you get a layered reasoning process.

Your idea flows through:

Source of truth
Strategic interpretation
Critical attack
Simplification
Implementation
Quality control

Each stage refines the previous one.

This feels less like a chatbot and more like a neural pathway forming.

And that word matters. Pathway.

Because over time, these patterns compound.

The more often you run ideas through this structure, the more stable the internal ego becomes. The system develops a personality. It forms boundaries. It creates consistency.

It stops guessing and starts behaving.

How I Came to This

This did not start as theory for me.

It started in the sandbox.

Whenever I build something with AI, I always start with a Source of Truth. What is this system really supposed to be? What are the constraints? What are the rules?

Then I send it through something like Claude Code to implement.

And at certain points, I have to step in as the human.

Why?

Am I checking it for accuracy?
Am I scanning for bugs?
Am I adjusting tone?
Am I injecting personality?
Am I approving architectural decisions?

At each of those checkpoints, I realized something.

If I can define what I am doing at that moment, I can clone that role.

So instead of “me stepping in,” I create an agent with that responsibility.

The Accuracy Checker.
The Bug Hunter.
The Personality Filter.
The Architecture Guardian.

Each one has parameters. Each one has constraints.

Suddenly I am not micromanaging the system.

I am designing it.

Self Repercussive Agent Patterns

Over time, these agent roles start reinforcing each other.

The Holder of Truth sharpens the Strategist.
The Skeptic strengthens the Implementation.
The Janitor keeps everything clean.
The Heartbeat keeps everything aligned and moving.

This is what I call a self repercussive agent pattern.

It is intelligence that improves through structure, not scale.

It is not about bigger models.

It is about better organization.

A New Mental Model

Most people think of AI agents as helpers.

I think of them as departments.

If you design them like departments with accountability, reporting, maintenance, and oversight, they behave differently.

And the human at the center stops being a typist and becomes a systems architect.

That shift changes everything.

Not because AI is magical.

But because structured responsibility is.

I’m reaching out because I’m looking for a few people who want to put their heads together and build something real with...
02/11/2026

I’m reaching out because I’m looking for a few people who want to put their heads together and build something real with AI.

We’re clearly entering a world where one person, paired with the right AI tools, can do what used to take entire teams. That’s exciting. But I don’t think AI replaces people. I think it amplifies them.

Lately, I keep finding myself asking a simple question over and over: is there a software solution for this? And more often than not, the answer is yes.

The tools are compounding fast. What used to feel abstract is starting to click. Workflows form. Agents make sense. Systems begin to feel natural. You can feel the muscle memory building as you use this stuff day after day.

At the same time, it’s obvious that AI is moving faster than anything most businesses have ever had to adapt to. A lot of business owners can feel that shift, but they don’t know where to start or who to trust. They don’t need hype. They need people willing to go first, test things, break things, and show what actually works.

I’m reaching out because I know a lot of you are builders, thinkers, business owners, creatives, or just naturally curious. Many of you are probably experimenting or learning in your own way and trying to figure out how these tools turn into something real. Something useful. Something that actually helps people and makes money in the process.

I don’t think this is a solo game. A small group of people with different strengths, backgrounds, and perspectives can build something far more valuable together than any one person trying to figure it out alone.

What excites me most is the leverage that comes from difference. Different life experiences. Different ways of seeing problems worth solving. Different ideas for use cases, monetization, and how this tech can be plugged into real-world situations. One person might see efficiency, another creativity, another education, automation, or entirely new products. That diversity compounds fast.

There’s also real, practical upside. Shared networks. Shared connections. Shared project load and clients. Shared resources for marketing and lead generation. And the ability to show up as a team instead of individuals experimenting in isolation. That’s how learning turns into momentum and momentum turns into something sustainable.

I’m not pitching anything. Just putting a feeler out and opening the door for real conversations with people I already know and trust.

If this resonates with you, I’d genuinely love to talk.

Honest check-in.Has anyone else experienced vertigo, head pressure, eye strain, or mental “brick walls” after doing deep...
02/09/2026

Honest check-in.

Has anyone else experienced vertigo, head pressure, eye strain, or mental “brick walls” after doing deep AI or coding work every day?

I genuinely thought something was wrong with me.

Curious if I’m alone here. I sharing more of the story and what helped me in the comments.

What if your business had its own software… and you actually owned it? Local business owners around Morgantown, this mig...
01/30/2026

What if your business had its own software… and you actually owned it? Local business owners around Morgantown, this might be worth a quick read.

Over the last year, I’ve been quietly helping a few local businesses build custom internal software for how they actually operate. The impact has been big enough that I decided to make this available to a few more people in the area.

Here’s the idea, in plain English:

If you’ve ever thought

“I wish we had software that actually fit our business”

“We’re paying way too much every month for tools we barely use”

“There has to be a better way than spreadsheets, workarounds, and duct tape”

That’s exactly what I help with.

I’m the founder of The AI Workshop Next Door, but think of it less like a tech company and more like a local software shop. I work directly with business owners to build simple, practical tools for their operations. Dashboards, internal systems, workflow tools, inventory, admin tools, or even replacing expensive subscription software you’re already paying for.

One important difference:
You own the software we build.
No subscriptions. No lock-ins. No long-term contracts.

Working together doesn’t feel like hiring a big consulting firm.

We set:

A weekly budget and fixed number of hours that works for you

Clear priorities and a simple roadmap

Weekly check-ins and deliverables

You’ll see your software quickly. In many cases, there’s a working demo on day one and usable tools within 1 to 3 weeks.

Cost-wise, this is far more affordable than most people expect. Recent changes in development tools have made this possible at prices that simply weren’t realistic even a year ago. My role is to come alongside you as a temporary teammate, either to build the tools for you or help you learn how to use them yourself if that’s something you want.

If you’re not sure where to start, I offer a $250 Business Blueprint. We walk through how your business actually runs, identify friction points, and map out what software could realistically help. No pressure beyond that.

I’m currently working with a craft beverage distribution company, a property management company, and a commercial construction company. To stay hands-on, I’m limiting myself to five active clients at a time, and I’m opening a couple more local spots now.

If you’re within about 50 miles of Morgantown, WV and curious, I’d love to have a conversation. Zoom or in person. No pitch. Just talking through what might be possible.

The Morning I Woke Up Already Living in the Future:A personal essay on post-scarcity, AI, and what comes after survival....
01/22/2026

The Morning I Woke Up Already Living in the Future:
A personal essay on post-scarcity, AI, and what comes after survival.

I woke up this morning with a feeling I haven’t had in a long time.

Not urgency.
Not dread.
Not the low-level anxiety that usually hums beneath the surface.

Excitement.

I had just come out of a dream that felt less like fantasy and more like memory, like I had briefly been living in a version of the future and had returned with fragments still intact.

It may have been the late-night spaghetti.
It may have been too many podcasts about universal income, AI, and a coming “golden age.”
Or it may have been something else entirely.

Either way, the details stayed with me.



A World Built on Vouchers, Not Fear

In the dream, humanity lived in something that felt strangely familiar, a world structured a bit like token usage.

Every morning, people “checked in” and reviewed their daily vouchers.
It felt almost like video game rewards, not stressful, not scarce, but quietly exciting. You’d skim what was available that day and decide how you wanted to move through the world.

Robotics and AI had taken over the mass production of nearly everything humans needed: food, shelter, healthcare, access to knowledge, technology. Scarcity, at least in the traditional sense, wasn’t the driver anymore.

But psychologically, humanity was still adjusting.

The ideas of work and income were changing, not collapsing, not imploding, just slowly reshaping into something less painful, less desperate, less fear-driven.

This wasn’t a dystopia.
And it wasn’t a utopia either.

It was a transition.



After Scarcity, There Was Conflict But It Looked Different

The dream acknowledged something important: we didn’t get there cleanly.

As AI and robotics gradually took over production over the course of several years, major global divisions formed. Humanity went through a kind of conflict, not like past wars, but not painless either.

The difference was this: when scarcity disappeared, the fear driving conflict softened.

When basic needs were guaranteed, there wasn’t the same desperation to fight over resources. Things resolved faster. Not perfectly, but faster.

Land mattered less. Borders blurred. Identity wasn’t tied as tightly to geography anymore.

Instead, people gravitated toward spheres.



Spheres of Belonging

Humanity organized itself through algorithms, but not in a cold, controlling way.

These systems didn’t dictate beliefs.
They helped people find where they fit.

People could easily connect with others who shared values, goals, and ways of seeing the world, while still being exposed to different perspectives in healthier, less antagonistic ways.

You didn’t live only inside one sphere.
But you always knew where you felt most at home.

Travel mattered less. Location mattered less.
Connection mattered more.

The younger generations especially seemed at ease with this, more open, more loving, less threatened by difference.



A Musical Way of Understanding Right and Wrong

There was another layer to the spheres that I’m still trying to fully understand.
The best way I can describe it is through music.

In the dream, right and wrong weren’t binary. They weren’t moral absolutes. They felt more like a musical key chart.

Each sphere operated like a key. Groups of people who thought similarly, valued similar things, and moved through the world at similar “frequencies” naturally clustered together, the way notes do inside a key. Some keys were major, some minor. Some felt expansive and bright, others more introspective or restrained. All of them had a place.

What mattered wasn’t everyone being in the same key. What mattered was balance.

In the center of the chart, everything went dull. Not evil. Not wrong in a dramatic sense. Just flat. Unproductive. Out of harmony. This was the space where actions weren’t adding to humanity, where they pulled energy away from the system instead of contributing to it.

Good and bad weren’t labels. They were more like resonance.

Certain spheres worked beautifully together, the same way some keys transition smoothly into others. There were natural modulations where a person could move from one sphere to another and it still made sense. Other combinations clashed, not because one was “wrong,” but because they created noise instead of music.

Understanding this made interactions easier. It helped people know where collaboration made sense, where tension was useful, and where distance was healthier.

The algorithms that organized this weren’t judging beliefs. They were observing outcomes. They grouped tasks, needs, creativity, entertainment, and even conflict based on where they added harmony and where they created dissonance.

It reminded me of how recommendation algorithms work today, how cookies guide us toward content we resonate with. But this was far more nuanced. It wasn’t about manipulation. It was about alignment.

In the dream, when people drifted too close to the dull center, when they consistently acted out of harmony with others, they weren’t punished. They were monitored. Supported. Given space to rehabilitate and gradually move back toward a sphere that matched who they actually were underneath the behavior.

That’s the part I’m still sitting with.

Right and wrong weren’t enforced. They were felt.

And the system wasn’t trying to make everyone the same. It was trying to keep the music playing.



Work Didn’t Disappear It Transformed

This wasn’t the end of entrepreneurship.
Or markets.
Or creativity.

Businesses still existed. Entrepreneurs still built things. There were still investments, experiments, even forms of stock markets.

But the old model, work yourself into the ground to survive, no longer made sense.

AI was deeply integrated into everything. Hiding who you were or what you did wasn’t really possible anymore, not in a surveillance-heavy way, but in a transparency-driven way.

There was no single AI overlord.
No controlling intelligence issuing commands.

Instead, AI became an extension of each person.

The line between “my thoughts” and “AI assistance” blurred, not because AI controlled people, but because it amplified them.

It made you more you.



Universal Basic High Income (But Not How We Imagine It)

Everyone’s core needs were met.

A home.
Health.
Food.
Access to knowledge.
Technology.
Artificial intelligence.

These weren’t privileges. They were baseline human rights.

Money still existed, but it wasn’t about excess. It wasn’t about hoarding. It wasn’t about survival.

Currency flowed mostly through digital systems and blockchain. Banks weren’t central anymore. Physical money still existed, but more as a novelty, something people collected or enjoyed, not depended on.

What mattered more than money was reputation.



“Don’t Be a Sh*tty Person” Became a System

This part was hard to explain, even in the dream.

Humanity wasn’t judged by one authority.
There was no single definition of good or bad.

Instead, behavior was evaluated through outcomes.

You weren’t punished for belief.
You were accountable for impact.

The core rule was simple, almost laughably so:

Don’t be a sh*tty person.

What that meant varied by context, culture, and sphere, but the system could measure consequences over time.

Everyone received their baseline vouchers simply for existing. But additional contributions, helping others, creating value, advancing knowledge, caring for the planet, building community, earned more.

Not wealth.
Opportunity.



Life Felt Like a Game In the Best Way

Goals existed.
Achievements existed.
Prizes existed.

Art prizes.
Exploration prizes.
Humanity-scale challenges, something like modern X-Prizes, that gave people shared purpose.

Status symbols weren’t luxury goods.
They were earned markers of contribution.

The people we would call “celebrities” today weren’t influencers performing for attention. They were individuals whose real-world actions demonstrably improved life for others.

You couldn’t fake it.
The system knew.



Justice Without Dehumanization

People who harmed others weren’t discarded.

Their basic needs were still met.
They were treated humanely.

But they weren’t left unsupervised either.

Instead of prisons, there was rehabilitation. Instead of isolation with other offenders, there was guided reintegration.

Some had robotic supervision, not punishment, but accountability. When trust was rebuilt, autonomy returned.

The system wasn’t perfect. There were growing pains. Early on, people burned themselves out trying to “optimize goodness.” Some learned how to manipulate it.

But where the dream placed me, later in the timeline, things had settled.

Life felt lighter.



What Stayed With Me

I remember waking up excited.

Excited to participate.
Excited to contribute.
Excited to wake up the next day.

I felt connected.
Purposeful.
Useful.

It felt like humanity had finally shifted from survival to meaning.

Was it real?
Was it symbolic?
Was it just my subconscious processing everything I’ve been thinking about?

I don’t know.

But I do know this: it’s been a very long time since a dream felt that detailed, that coherent, that hopeful.

So I’m writing it down.

Not as prediction.
Not as manifesto.
Not as belief.

Just as a glimpse and an invitation to think.

If this future is possible, even in pieces, what does it ask of us now?

Address

Morgantown, WV
26501

Opening Hours

Monday 8am - 5pm
Tuesday 8am - 5pm
Wednesday 8am - 5pm
Thursday 8am - 5pm
Friday 8am - 5pm

Alerts

Be the first to know and let us send you an email when The AI Workshop Next Door posts news and promotions. Your email address will not be used for any other purpose, and you can unsubscribe at any time.

Share