Flux Systems AI

Name: Flux Systems AI
Address: 150 Rue Charbonneau, Gatineau, QC, J8R3J8, CA
Telephone: +16136064143

Accueil
Canada
Gatineau, QC
Flux Systems AI

Flow to Grow

10/15/2026

I don't think most teams should start with AI training.

Training before people have a real reason to use AI doesn't stick: good session, everyone nods, and the next week it's back to the old way.

Humans doing human things, 100% normal.

What I'd do instead: pick one task your team hates, make it faster with AI and automation, and show them the value of that one thing.

The extra time can go back into human development, and the bigger training makes a lot more sense after that.

Where am I wrong?

Stay human out there!

10/14/2026

27% of Canadian business owners are using AI without knowing it. BDC asked entrepreneurs if they used AI:
-39% said yes.
When they showed them a list of tools, it jumped to 66%.

A lot of the software you already pay for has AI built in now. Before buying a new AI tool, list what you pay for every month, check what each one can already do, and ask your team what they actually use.

Turn on what you have, and only buy what's missing.

What's one app you pay for that you suspect does a lot more than you use it for?

10/01/2026

I came across a stat this week that stuck with me.

80% of people say AI made them more productive. But only 37% of companies actually see it in their profits, and that number hasn't really moved since last year.

So where's the disconnect?

From what I see, most businesses start with the tool. Someone says "we should be using AI for this" and then they go looking for a problem to fit it.

When we do an audit, we do it the other way around. We don't even talk about tools for the first sessions. We just ask questions about how the work really gets done, day to day.

One thing that sometimes surprises people: we make a point of including at least one "don't build this" in our recommendations.

If something isn't worth the money, I'd rather say it upfront.

Which of the 5 points would be the hardest to answer in your business?

09/29/2026

Your team doesn't need more AI training.
They need time.

In one year, companies offering AI training went from 25% to 58%.

Yet 56% of employees say they get no time at work to practice.

More training. Same results.

As a teacher, I know this: nobody learns by watching a demo. People learn by practicing on real work.

A ChatGPT demo on Tuesday. Back to the email pile on Wednesday. Nothing changes.

What works:

1. Teach from a real task in each person's week, not a generic example
2. Block protected time to practice, during work hours
3. Follow up a week later: what stuck? What didn't?

Yes, some teams are starting from zero and need the basics. But more hours of demos won't fix the real problem.

Training that doesn't change someone's Monday morning is entertainment.

On your team, what's really in the way: knowledge, or time to practice?

09/23/2026

You can outsource thinking now
but you cannot outsource understanding

That’s the part people keep missing with AI
AI can help a lot

It can write, summarize, analyze, and move fast

But if the human in the loop doesn’t really understand what’s happening, then you’re just getting faster output with more risk

The real magic is having the right human in the loop
Get that right...the RIGHT human

Because the right human brings judgment
Context
Common sense
And accountability

That’s when AI becomes something huge

Not just a tool
A real multiplier
A leverage bar

AI + the right human = exponential power.

09/10/2026

We have been building hard and strong here at Flux Systems. But what really stands out lately is the connections.

For the past couple of months me and my partner have had the opportunity of meeting wonderfull people.

One of them is Kyle Paquette, a one of a kind great guy! He is a bag of knowledge and a genuine great human.

Helping and bringing value to people is where true purpose lives.

Bring value to people, we believe in that truth.

Stay human guys!

08/20/2026

Generic software is dying.

Not because software is bad. Quite the opposite.

Businesses are just tired of changing how they work to fit inside someone else’s app.

Then you still use spreadsheets, emails, and manual workarounds.

And honestly: how many of the features you pay for do you actually use?

The future is custom software built around the way your business already works.

This means SiaS, software inside a service.

Instead of giving clients a tool and hoping they use it, build simple software into the service you deliver.

The best software will not feel like software.

It will just make work easier. Add real value.

What part of your business still runs on spreadsheets, emails, or sticky notes?

08/13/2026

I’ve been thinking a lot lately about the next generation.

Not just about the world they’re inheriting, but about the tools, skills, and mindsets we’re handing them.

The truth is simple: the skills of today won’t all have the same value tomorrow. Some will be automated, others will explode in importance.

And in this transition, we (parents, entrepreneurs, leaders, educators) don’t get to be passive spectators.

We have a responsibility to help steer them in the right direction.

That means teaching them how to:
-Think critically in a world flooded with information
-Collaborate with AI instead of fearing it
-Build systems, not just consume them

Stay curious, adaptable, and resilient when the “rules” keep changing

For me, this isn’t theoretical. It’s personal. I’m a dad, I’m building Flux Systems, and every day I see how fast the landscape is moving.

At Flux, we see ourselves as partners in building the skills and reflexes that will matter tomorrow – both inside organizations and in the broader community.

That’s why we’re working on something I’m really excited about:

Flux will be developing a course for teens specifically designed to bridge the gap between the “ancient” skills schools still focus on and the new skills tomorrow’s world will demand.

We want to help young people:
-Understand and use AI as a tool, not a threat
-Learn automation thinking and systems design
-Build real projects that connect tech, creativity, and problem-solving

If that’s something that resonates with you as a parent, leader, or educator, stay tuned and keep in touch—I’ll be sharing more as we get closer to launch.

If we want a future where our kids thrive, not just survive, we need to start teaching differently now.

I deeply believe that what we build today – in our companies, our families, and our communities – will define their options tomorrow.

And I’m committed to doing my part, both as a founder and as a father.

Because they’re watching us.

And we owe them more than “we’ll see what happens.”

08/11/2026

AI today is basically programming… but with the English language.

Once that clicks, things get way less mystical.

You stop seeing “magic” and start seeing another layer in the stack.

At the bottom, you’ve got the hardware: transistors, instructions, how a CPU actually moves data around.

On top of that, you’ve got classic code: Python, JS, whatever you use to tell the machine exactly what to do.

LLMs are just the next layer.

Under the hood, they’re turning your natural language into instructions — and in a lot of dev tools, that literally becomes Python, JavaScript, SQL, or shell commands that run on a CPU.

So instead of writing functions directly, you’re shaping behavior with language:
-How you describe the task becomes your “API design.”

-How you set constraints becomes your “type system.”

-How you structure context becomes your “architecture.”

When you understand how CPUs work and how LLMs work, you stop treating AI like a black box.

You:
-Use prompts with more precision.

-Reduce “dead angles” where the model guesses wrong.

-Design workflows where each agent plays a clear role, just like services in a backend.

The people who win with AI aren’t just “prompting.”

They’re building systems—thinking in layers, from silicon to syntax to strategy.

If you’re technical, your unfair advantage is simple:
Treat English like code, and treat AI like another tool in your stack.

Once you see that your words are turning into actual instructions (often real code), you stop chasing hacks and start building infrastructure.

08/10/2026

Most AI agents are way over-engineered.

Vector databases for "memory"? Orchestrator frameworks for "workflows"?

Three microservices just to read a file?

Nah.

Two standards dropped in 2026 that make all that obsolete:

-Folders. And markdown files.

That's it.

Your agent's memory = folder of .md files

Your agent's workflow = numbered folders with a CONTEXT.md in each

No database. No framework. No orchestration layer.

Even Anthropic gets this. They're pushing folder-native hard because it works.

The filesystem won in 1978 with Unix. It's winning again for AI.

Plain text outlasts the scaffolding built on top of it.

If your stack is more than:

-A folder structure
-Markdown files
-A model pointed at them

You're overcomplicating it.

Your move.

Adresse

150 Rue Charbonneau
Gatineau, QC
J8R3J8

Téléphone

+16136064143

Site Web

http://fluxsystems.ca/

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