Jay Mount Consulting

Most revenue teams are building with borrowed tools.
The same CRMs. The same databases. The same cold email sequences.
It’s no wonder results feel flat — everyone’s playing the same game.

At JMC, we help you build your own.
We design Revenue Intelligence Architectures — proprietary systems that turn raw data, messy ops, and stale tactics into leverage your competitors can’t copy.

Our systems give you:
• Decision-making engines that route leads automatically
• Custom TAMs built from scratch (not scraped from ZoomInfo)
• Cross-channel orchestration that learns, adapts, and compounds
• A foundation your team can own, scale, and evolve

This isn’t RevOps.
It’s competitive advantage — built through automation, intelligence, and strategic clarity.

Want to see what that looks like in your business?
Start with a 48-hour architecture evaluation. We’ll map the risks, identify the upside, and show you exactly where the edge lives.

Founder

Growth Steps Newsletter

Join a community of 30,000+ Leaders Growing Smarter Every Week

The Growth Steps Newsletter delivers practical, no-fluff business insights straight to your inbox. Every week, I share simple, actionable strategies to help you lead with clarity, grow your business, and make real progress.

No theory. No wasted words. Just real-world advice you can apply immediately.

Lead better – Sharpen your decision-making and leadership skills.

Grow faster – Unlock smarter ways to scale your business.

Make progress – Cut through complexity and take action that matters.

Join the 30,000+ leaders who already get their weekly advantage. Subscribe now.

Writer

Clay

Solutions Partner

Predictable Revenue™ Inc.

Advisor

Techstars

Startup Mentor

Kinext

Hybrid Financial Ltd.

Responsible for product, growth, and scaling for Hybrid Financial. Early employee at the company to implement sales enablement tools, systems, and processes to grow from:

- Under 10 employees to over 180
- 20 customers to over 200.

Developed proprietary sales enablement AI-based platform to drive growth and create a different category.

Chief Growth Officer | Building Investor Audiences

basix.ai

We started basix.ai because we saw firsthand how doing “sales as usual” prevented sales from happening. Once we isolated and focused on the activities that drive revenue, we were able to boil it down to its simplest components; do the things that drive prospects forward, and stop doing the things that hinder sales. 

Most sales reps inadvertently spend time:

- Chasing deals that were never going to close (based on bad or incomplete data)
- Deciding who should be contacted based on gut feel
- Spending time on endless research, going between systems and databases

We built a technology platform that actually works with the salesperson to keep them in sales conversations and in their sales flow. 

Our experience has shown the answer is not to try to surround the salesperson with more activities and just increase performance, but rather keep the focus on just selling.  

With basix, the smart workflow engine learns what activities and what prospects to focus on so your sales team can get better results. This happens because the system learns who is the current “low-hanging fruit” and constantly serves them up. At the same time, the highest and best activities are matched, taking those prospects further into the buyer’s journey, and moving them to the close.

CEO & Co-Founder, basix.ai | Rapidly scaling sales teams

Architected and delivered 11% of net new income across $660MM of incentive compensation within RBC's P&C Banking Division.
- 400% lift in the number of products sold per Agent/Rep.
- 27,000 Agents/Reps selling financial services/insurance to individuals and companies.

Director, Performance & Incentive Design

National Sales Management Performance - Deposit, Investment, Lending Products

Mackenzie Investments

Product Development & Sales Growth, Reported to the Head of Product

Founder Helping You Grow | Follow for Daily Leadership & Growth Insights | Serial Entrepreneur | Ex-RBC

My story isn't typical - it's not about steady corporate progression or entrepreneurship from the start.

At 23, as a single dad, my journey took an unexpected turn.

In big corporations, where I stayed longer than planned, I experienced a different kind of growth.

Each night, after my son slept, my dual life as a father and ambitious professional unfolded.

But here's something you might not know: in these big companies, I didn't just get by; I excelled. Leading teams from two to 550, I was more than just another face.

I was a leader, learning about product development and large-scale expansion.

Yet, I constantly wondered, 'Am I too late to start my own business?'

This internal struggle, balancing comfort and ambition, kept me restless.

Outwardly successful in corporate, inwardly, I yearned for something of my own.

Skeptics called my desire to leave a stable career crazy, intensifying my internal conflict.

As my son became more independent, my perspective shifted.

A change was brewing, a readiness for something new.

That's when I left my corporate safety net, embracing the unknown.

The excitement of change was tangible, but what was to come?

My journey, initially thought to be solo, became a collaborative effort.

My first customer, my peers - they were more than connections; they were catalysts for transformation.

This transformation led to founding two startups in seven years.

Leaving corporate life for entrepreneurship was more than a business move; it was self-discovery, realizing my potential.

My achievements are clear:

→ Generated 9-figure revenue growth for clients and employers.
→ Progressed through 10 roles in two companies before venturing out.
→ Grew bootstrapped businesses to 7 and 8-figure heights.
→ Developed numerous leaders.
→ Launched several products.
→ Built two startups in seven years.

I share my story to inspire those on similar paths, not for self-praise.

If you're wondering if it's too late or too risky, let my experience guide you.

I'm here to connect, share, and inspire.

Let's discover what lies ahead, together.

Join my free newsletter at https://jaymount.me/newsletter

Jay Mount

Turning Data Into Better Decisions | Follow Me for Daily Tips to Make You More Tech Savvy | Technology Leader & Entrepreneur

Working in technology for 18 years, I knew organizations and clients needed more help than industry was providing:

Here are some of the real challenges I saw clients and organizations facing:

🎯Feeling like people were throwing technology solutions at them without fully understanding the problem
🎯Knowing their data could be used for much more but not knowing how to do this
🎯Not having trusted and skilled advisors to be able to help them make technology decisions
🎯Feeling overwhelmed by the rate of technological change and not knowing where to begin
🎯Not having enough training or understanding to evaluate technology solutions
🎯Technology transformation failing because the people element was ignored
🎯Consultants not connecting the mission with the solution and technology

To solve these challenges, I knew I needed to start a dynamic technology company to bring together world-class talent to help our clients be more tech savvy and to help organizations adapt to new technologies.  

In 2022, Avenir Technology was born. Avenir means future. Because as Peter Drucker said, "the best way to predict the future is to create it." 

We are a team of 15 people who help our clients feel more comfortable with technology and help them adapt to new technologies faster and solve their organizational problems.

Our clients are in the public and commercial sectors. 

To learn more, visit: www.avenirtechnology.net. 

🚀 Ready to get started?  Book a 1-1 call with me: https://calendly.com/anicholson-dfa/30min.

👋 Want to be more tech savvy? Follow me!

Ashley Nicholson

The $200,000 Stanford AI degree just became worth a lot less.
Not because the education isn't world-class:

Because Stanford just released all their flagship AI and Machine Learning courses for free on YouTube.

This changes everything about how we learn AI.

1/ The legendary courses are now accessible to everyone for free:

These aren't watered down versions. These are the exact same courses Stanford charges tens of thousands for:

↳ CS221 – Artificial Intelligence: Principles & Techniques (Core AI foundations)
See: https://lnkd.in/dD-zCpRV. 

↳ CS224U – Natural Language Understanding (How machines interpret meaning)  
See: https://lnkd.in/dvyKbgni. 

↳ CS224N – NLP with Deep Learning (transformers, embeddings, modern NLP)
See: https://lnkd.in/dWdzHA6B.

↳ CS229 – Machine Learning by Andrew Ng (the legendary ML course)
See: https://lnkd.in/dNuiW9BM.

↳ CS229M – Machine Learning Theory (Mathematical backbone)
See: https://lnkd.in/dmyS2WZr. 

↳ CS329H – ML from Human Preferences (reinforcement learning meets alignment)
See: https://lnkd.in/dz6uVz-N.

↳ CS230 – Deep Learning by Andrew Ng (Neural networks, CNNs, RNNs)
See: https://lnkd.in/dZRdJhWb.

↳ CS234 – Reinforcement Learning (Agents, environments, reward-driven learning)
See: https://lnkd.in/dh6QWS_f. 

↳ CS330 – Deep Multi-Task & Meta Learning (How models learn to learn)
See: https://lnkd.in/dFDYNMbj. 

2/ Why this matters more than you think:

The AI skills gap isn't closing because of cost barriers.
↳ Traditional education takes 4+ years and costs a fortune.
↳ Most professionals can't afford to go back to school.
↳ By the time you graduate, the field has already moved on.

Stanford just eliminated the biggest barrier to AI education.

3/ The real opportunity here:

You don't need a Stanford degree to work in AI anymore.
You need Stanford level knowledge.

And that knowledge is now free.

The question isn't whether you can afford AI education.
It's whether you can afford not to take advantage of it.

What's stopping you from diving into AI learning now that these barriers are gone?

Which course are you most excited to explore?

Share below. 

♻️ Share this with someone who needs to see this.
➕ Follow me, Ashley Nicholson, for more tech insights.

Credit: Dr. Kion Ahadi for surfacing these incredible resources. Give him a follow!

Turning Data Into Better Decisions | Follow Me for More Tech Insights | Technology Leader & Entrepreneur

Your employees won't tell you the truth.
But they told me:

They're afraid.

Afraid of AI.
Afraid of change.
Afraid of being replaced.
Afraid of losing their jobs.

So, I'm saying it for them.
Saying the quiet part out loud.

The part I'm not supposed to say.

Because the future of implementing AI responsibly and successfully in your organization,
↳  Depends on addressing human emotions. 

Here's the thing.

People get most of their ideas about AI from movies:
↳  Skynet from Terminator.
↳  Replicants from Bladerunner.
↳  Violent robots from Ex Machina. 

Newsflash: none of these are positive associations.

If you don't take this time to talk to your people about change,
And address their fears, your AI projects will fail.

Here's how to address these fears effectively and compassionately:

1/ Recognize that people manage change differently and at different speeds:
↳  Your team likely has diverse people from different generations.
↳  3 months for a radical, technology transformation is not realistic.
↳  Start small and scale up.
↳  Give your team time to get buy-in. 

2/ Foster a culture of psychological safety:
↳  Have frank round table discussions around AI. 
↳  Do this with smaller teams and ensure everyone is included.
↳  Managers should ensure that fears can be expressed and addressed.
↳  Leaders must lead by example. 

3/ Support your middle management:
↳  Have a "all hands" meeting with company leadership and explain "why" and "how" you are implementing AI.
↳  Communicate early and often with your middle managers.
↳  Give them the resources and time they need to communicate with their team.
↳  Technology transformation thrives or dies in the middle.
    
4/ Teach AI literacy and AI limitations:
↳  Not everyone is technical.
↳  Provide basic instruction on AI across work areas.
↳  This creates a basis for everyone to learn.
↳  Explain that AI is not perfect and show the opportunities and limitations of the technology.

5/ Show how AI will help support administrative and boring tasks:
↳  Provide training on AI tools and show how AI can support boring and administrative tasks.
↳  Show how this allows employees to focus on higher level and more purposeful tasks.
↳  Build AI into real workflows and provide training.
↳  Illustrate the number of new jobs that AI will create (AI ethics, AI governance, etc.) and provide training in these areas. 

6/ Invest in increased soft skills:
↳  There is a lot AI does well, but a lot AI does not do well.
↳  Make investments in training all staff in these areas.
↳  For example: customer service, team leadership, AI ethics, emotional intelligence, etc.


Trust me.

This is the elephant in the room.

Your employees won't tell you this.
But I just did.

Now the question is:
What are you going to do about it?

How are you going to address this in your organization?

Share below.

♻️ Share with someone in your network who needs to see this.
➕ Follow me, Ashley Nicholson, for more tech insights.

The most dangerous man in technology isn't Elon Musk.
It's a 28-year-old kid:
And Zuckerberg just gave him 15 BILLION DOLLARS to build a "superintelligence lab" for Meta. 

His name is Alexandr Wang.
And while we were all looking at the visible geniuses....
He controlled the invisible power.

He didn't start a social network.
He didn't sell electric vehicles.
He didn't build rockets. 

Wang did something infinitely more strategic:
He created the infrastructure on which all of AI would learn from.

His business: Scale AI.
Clients: OpenAI, Microsoft, Amazon, and Meta.

And his advantage?

↳ Seeing the models before anyone.
↳ Collecting the best data.
↳ Knowing what was coming.... before anyone suspected anything.

Because every time a business wants to train AI, it will likely go through him.

And now, Meta wants all this power on their side.
They didn't just get Wang.
They bought access to this corner of the market. 

And here's the craziest thing:
Wang didn't want to be famous.
He didn't scream on social media.
He didn't want visibility. 

He simply constructed something so essential....
The rest didn't have another choice but to rely on him.

While others compete for attention,
He constructed a system that changed the game.

This was the strategy.

It was playing the game from the top.

And seeing things others didn't see.


What do you think of this development?

Share your take.



♻️ Share this with someone who needs to see it. 
➕ Follow me, Ashley Nicholson, for more tech insights.

AI is forcing universities to rethink everything.
And many people are already embracing the change:

At last week's GovAI conference, a group of us discussed what skills will be crucial for the "new university."

This topic kept coming up in so many of the sessions.

Here are the 5 essential areas that came up in the discussion:

1/ Philosophy, epistemology, ethics, and critical thinking are no longer optional:
↳ These courses should be required early, maybe even middle school.
↳ They will be the new language or mathematics.
↳ Essential across all fields.
↳ Students need frameworks to evaluate truth and navigate AI-generated information.

2/ Systems thinking:
↳ Every person in every field will likely do their job at a higher level.
↳ This will require systems thinking and focusing on scaling.
↳ Understanding interconnections becomes critical when AI handles the details.

3/ Soft skills and emotional intelligence:
↳ Human connection will be the differentiator.
↳ Communication, empathy, and collaboration can't be automated.
↳ Negotiation, getting buy-in, asserting power, and managing change can't be taught or executed by AI.
↳ Leadership skills will become more essential.

4/ AI history and training:
↳ Understanding how we got here helps predict where we're going.
↳ Hands-on experience with AI tools should be standard across curricula.
↳ Students need to know both the capabilities and limitations of AI.

5/ Deep expertise in one area:
↳ Ability to be a subject matter expert and analyze large model outputs.
↳ Being well-versed in using field-specific small models.
↳ Depth matters more than breadth when AI provides broad knowledge on demand.

The universities that adapt to this framework will produce graduates who thrive.

The ones that don't will produce graduates who get replaced.

What do you think of this list?

What skills do you think the graduates of tomorrow need to thrive in the age of AI?

Share below.


♻️ Share with someone in your network who needs to see this.
➕ Follow me, Ashley Nicholson, for more tech insights.

taplio

The Battle

Jay Mount

Ashley Nicholson

Followers

Posts

Engagements

Likes

Performance ScoreAshley Nicholson's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Jay Mount

Ashley Nicholson

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Ashley Nicholson's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreAshley Nicholson's LinkedIn Performance