TODAY’S THOUGHTS ☠️

Hey friend 👋,

Is your company using “true” AI agents to deliver meaningful work?

Probably not.

And you’re not alone in this. The tech world has been on an obsession with telling us that AI agents will revolutionise the world of work.

First it was the AI-first movement with delegating everything to AI and sacking humans, which didn’t work, and we never spoke of AI-first again.

The humans were rehired and then came the next wave of proclaiming that the AI jobpocalypse was coming in 18 months for all white collar jobs. Again, it didn’t happen.

The next phase was agentic AI everywhere supporting the humans doing the work. It has happened in some areas but most certainly not to the biblical scale the AI companies have been telling us these past two years. Nor has the billions of dollars in value been seen as of yet.

I see a lot of “AI Agent” solutions bouncing around on social for L&D, yet experience has shown me very little of that within company walls.

So, why haven’t AI agents rewired work and what’s really going on inside L&D teams with AI Agents today?

That’s what we’ll be exploring today.

Get your tea or beverage of choice ready 🍵.

We've got lots to discuss!

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THE BIG THOUGHT 👀

Open up your social media app of choice and you’ll be met with endless posts by tech bros proclaiming how AI agents run their business, makes them millions and they’ll show you how by commenting on their post.

Organisations aren’t much better.

I see constant mentions from CEO’s on “Our agentic” strategy and “how we’re deploying AI agents across the enterprise to do blah, blah, blah”. Almost all of this is ‘performative theatre’ and so far from the reality of what’s happening inside organisations.

I’ve been inside so many organisations from startups, scale-ups to large fortune 500 names you all know. None of them are doing much if anything with AI agents, and they’re certainly not making millions.

So, that begs the question - what are people inside companies doing with AI?

And the no BS answer is…not as much as you think.

Ok, let’s take a step back and contextualise the dream of humans working with AI agents to produce good work.

Microsoft positioned the concept of AI agent + human team structures back in 2025.

They proposed that frontier firms would have teams of humans leading AI agents. This would look like the below:

I think some L&D teams are at phase 2 today but mass adoption isn’t quite here yet.

95% of people don’t know what AI agents are or even what they can use them for.

But this is not a tech problem, it’s a positioning and usability one. AI agents only become useful if you understand ‘how you do work today’, and many of us don’t. The gateway to AI agents becoming useful is being able to map out your current workflows (fyi, a workflow is a step by step breakdown of how you complete a task).

Mapping workflows is not an easy task.

It takes time, deep thinking and the capability to capture that in a simple format. Which is why most people don’t do it.

For AI agents to become truly useful at work and in learning, they need to answer these questions:

From my own experience inside organisations, what holds most people back from utilising AI beyond general chat can be categorised as the following:

Again, this isn’t a tech problem.

Agentic AI is here right now but if its applications and outcomes remain undefined, then it won’t be used. Much like anything we have in life.

I’m not the only one calling this out, either.

Analysts, AI bros desperate for people to buy their products and Chief AI officers inside organisations are saying it too.

Here’s a few snippets I’ve picked up over the past month.

In relation the the image above, NYU Stern’s Chief AI Architect, Conor Grennan, shared some good commentary on this, and analysed the comments from the post to give use 7 reasons why the majority of us aren’t using AI agents.

I’ve placed them below to save you clicking through more links:

The final paragraph is one to pay most attention to.

Many of us are using AI agents without knowing it, and that’s a good thing. We see this inside the LMS and LXP too, a lot of stuff is being baked in. The same goes for any of the leading LLMs in Claude, ChatGPT and Gemini.

Most of the newer features in these models are agentic, they’re just not calling them out as agents.

The simple answer riffs on what I shared before, focus on:

Of course, simple is not easy.

At the heart of all of this transformation are people, and we are pretty fickle beings.

You can have all the fancy AI tools you want but without the people onboard to adopt, enable and drive value, you’re f**ked.

This point was also raised by IBM’s Chief HR Officer, Nickle LaMoreaux, in a much more professional manner then mine:

I’m not going to leave you hanging with no help on this, here’s a few pieces from my library to get you started.

The rest I will leave to your exploration.

Ok, friend.

This week the message is simple: Everything is not as it seems with AI in the real world.

You’re not behind because the data overwhelmingly points to the fact you’re early. Especially if you know what an AI agent is already (go you!).

We know this to be true as I type these words:

Shocking revelations, I know.

Oh, and one more thing. I couldn’t help but chuckle when I saw the image below on a recent doom-scrolling session. It’s more accurate than most people know.

See you next time, human.

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👀 ICYMI (In case you missed it!)

VIDEO THOUGHTS 💾

No matter where you work, what your industry or your skills, you need to know the conditions for your success at work.

I learned this the hard way as an L&D operator.

No one cared about my products and work unless it met the conditions for success in that organisation. In this video, I use my role as an example to showcase the 3 conditions for success that every business runs on.

Master these to do great work.

Enjoy 😊.

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