20 Comments
User's avatar
James Presbitero's avatar

That's so cool! Congratulations on putting it out.

Expand full comment
Atman's avatar

Very useful. Thanks for sharing!

It might be useful to add the link to this article in the Google Doc as well since it seems like the doc only mentions it without the actual link

Expand full comment
John Brewton's avatar

All the links are embedded for the docs in multiple places though out the article, did you means in the note too? That’s a good idea. Thanks!

Expand full comment
James's avatar

Your post felt like watching someone build a staircase one careful step at a time.

No rushing, no skipping ahead, just a clear rhythm that helps people grow without burning out.

Through the 5 Voices lens, upskilling lands differently for each person:

Nurturers learn best through encouragement and purpose.

Guardians thrive with repetition and clarity.

Creatives grow when they have room to explore.

Connectors develop through conversation and shared energy.

Pioneers stretch when they’re given challenge and direction.

When leaders understand these patterns, their development plans become far more effective.

Expand full comment
John Brewton's avatar

Appreciate you, James. So glad the post resonated with you. 🤓🙏🏼

Expand full comment
Chris Tottman's avatar

"AI Era Career" 💙

Expand full comment
John Brewton's avatar

Indeed my friend. Appreciate you, Chris.

Expand full comment
Suhrab Khan's avatar

This framework is a masterclass in turning intent into measurable capability, building AI fluency, human skills, and strategic acumen in tandem is exactly how professionals stay relevant in the AI era.

I talk about the latest AI trends and insights. If you’re interested in structured AI upskilling strategies for building long-term career resilience, check out my Substack. I’m sure you’ll find it very relevant and relatable.

Expand full comment
John Brewton's avatar

Appreciate you, Suhrab!

Expand full comment
Chintan Zalani's avatar

The Three Pillars + EPOCH framing gives good structure to what otherwise feels like random AI ‘tool tinkering.' Thanks for sharing!

Expand full comment
John Brewton's avatar

Appreciate this, Chintan happy it brought some order to the work.

Expand full comment
Nazanin Bigdeli's avatar

You have created a amazing workshop!

Expand full comment
John Brewton's avatar

Thanks for reading, Nazanin what part stood out most to you?

Expand full comment
Ryan Yockey's avatar

Wow. This is some serious depth. I can’t wait to dive in on these playbooks.

Expand full comment
John Brewton's avatar

Glad it caught your interest, Ryan what part are you planning to dig into first?

Expand full comment
Ryan Yockey's avatar

Pillar 3 - strategic work with AI as it pertains to the business development will be critical not just for me but my clients as well. I like the daily activities too.

Expand full comment
John Brewton's avatar

You and me both my friend. I’ve spent a lot of time in pillar 3. Hope your year is ending well my friend!

Expand full comment
Passport Inspiration's avatar

It's one thing to understand the technology but it's another to design a career that is specific, applicable, and necessary. That's a winning strategy.

Expand full comment
John Brewton's avatar

You summed it up well, Passport, making it real in your work is what matters.

Expand full comment
Myles Saulibio's avatar

John, the part that got my eyes unglued is the section on how MIT reframed the terrain.

They showed that complementarity is not a soft skill story at all.

It is the capacity to hold and regulate meaning when the system accelerates.

Machines scale pattern work.

Humans guard how those patterns are interpreted, constrained, and applied.

Most people treat this as a talent gap.

I see an operating gap.

Once you place a model in the loop, the work changes shape.

Teams are no longer selecting tools.

They are deciding who controls interpretation when speed rises and context thins.

Your playbook points to this shift even when the language stays practical.

The real upskilling is the ability to stabilize understanding while the model amplifies pace.

Human presence, judgment, and boundary setting still determine whether the system holds together.

Curious how you see this evolving as more operators move from tool learning to meaning management.

Expand full comment