Don't Sweat the AI Agent Hype - here's what you actually need to know for L&D

Author

Ross Stevenson
June 3rd, 2025

📨 Subscribe | 🤖 AI Training | 🚀 Courses

 TODAY’S THOUGHTS ☠️

Hey there 👋,

We’re 6 months into 2025, and I feel like I’ve hardly done a thing.

I’m hoping I’m not alone in that thought.

We’re navigating so much innovation at hyperspeed, I’m not surprised if we can’t cling to the concept of time. A big topic of the past 6 months, on my feeds anyway, has been AI Agents.

I shudder even typing that word as it’s almost become cringeworthy.

There’s a lot of misinformation swirling around about this topic.

So today, we’re unpacking what L&D teams actually need to know about AI Agents to make you a little wiser about the hype you see everywhere.

Get your tea or beverage of choice ready, 🍵.

We've got lots to discuss!

P.S. Your app might clip this edition due to size, if so, read the full edition in all its glory in your browser.

 IN THIS DROP 📔

  • What you actually need to know about AI agents

  • Your guide to deciphering the snake oil to make smart decisions

  • Don’t sleep on the importance of digital intelligence for L&D teams

🙋‍♀️ Want to reach over 5,000 L&D pros? Become a Newsletter sponsor in 2025

 THE BIG THOUGHT 👀

Don't Sweat the AI Agent Hype - here's what you actually need to know for L&D

What social feeds currently look like

Agent this, agent that — is literally all I see on LinkedIn these days.

Granted, it’s a total echo chamber of people mostly shouting that back at each other, but by God, it’s giving me a headache.

The hype, mostly driven by AI companies, is becoming laughable.

Don’t get me wrong, AI agents will be very useful and there’ll be some great applications in L&D, yet you’d think a sort of world peace is about to emerge by the way the ‘influencers’ talk on social.

So, this is my PSA (public service announcement) to you to say: “Don’t get worried about all the talk.”

I know it feels like you’re missing out on some great party, but you’re really not.

Almost 90% of what you see paraded online is not a true agent solution. Not in the technical context, anyway.

Much like marketing teams decided to use the word “AI” everywhere post-2022, they’re doing the same thing by labelling everything an Agent.

Unfortunately, this has created a fractured understanding of what an agent is, and the definitions are always changing.

Not only this, but many are trying to run before they can walk.

I work with sooo many teams and companies that hardly know how to use a basic AI assistant to even 50% of its potential. Adding agents into that mix is a recipe for both confusion and mistakes.

A lot of people need to slow down…

Pause… take a breath and find your centre (or whatever meditation teachers say).

Without this moment of pause, it’s incredibly hard for you to truly know what’s going to help you and what you don’t need to know.

And too many of us aren’t aware of all the options we already have today.

Agents are cool, but the current noise is lying to you about a lot of things.

So, let’s bring some clarity to all of this ↓

How I’m feeling…

Assistants vs Agents: What’s the difference?

Two terms you might hear techies mention with AI products are ‘AI assistants’ and ‘AI agents’.

Here’s the difference in clear, simple terms.

Let’s start with what we know – AI assistants like ChatGPT.

These are tools that help us with tasks through conversation. They can write, analyse, explain, and give suggestions based on what we ask.

AI agents take this a step further.

Instead of just helping through conversation, agents can actually complete tasks on their own. They follow instructions, use different tools, and make basic decisions to get things done.

The key difference is simple:

  • AI assistants help you with tasks

  • AI agents complete tasks for you

Both are valuable, but they serve different purposes. An assistant works with you through conversation, while an agent works independently based on your instructions.

Use this info to impress the boss at your next meeting.

I’m not going to leave you with just this, though.

As I’m a tech nerd, I’ve filmed a quick video (see below) to show how agents work with examples from Google and Salesforce – enjoy.

What can AI agents do?

A lot, but maybe not as much as the local tech bros are promising.

Imagine having a personal assistant who not only follows your instructions but also takes the initiative to resolve problems independently.

AI agents are like that, except they exist in the digital world.

At their core, they’re designed to observe their environment, make decisions, and take actions using the tools available to them.

Unlike traditional software that waits for you to give it a command, like LLMs, AI agents can think ahead, figure out what needs to be done, and act.

Sometimes without needing constant human input.

Think of them as a self-driving car.

Instead of waiting for a person to steer, brake, or accelerate, the car analyses traffic, makes decisions, and moves safely toward its destination.

AI agents work similarly but in a digital space, whether it’s automating workflows, analysing data, or even assisting with creative tasks.

The magic of AI agents lies in their autonomy and problem-solving abilities.

Even if you don’t give them step by step instructions, they can work out the best way forward to achieve a set goal.

They do this by following set rules and past experiences to decide the best way to complete a task. This makes them incredibly useful for businesses, customer support, research, and even personal productivity.

→ Get an example of this type of AI agent solution with this scenario I built to support common onboarding challenges between HR and Tech teams.

The many faces of AI agents

There was a time when an AI agent meant one thing.

Now, we’ve hit peak confusion thanks to marketing teams the world over.

Each one wants to tell you they’re “agentic”, and each wants you to use their AI agent. But…is it really an AI agent? And if it is, is it the right one for you?

Let’s unpack the types of AI agents, or what social media wants to tell you are AI agents in the market today:

Now, the reality of what you see online is 95% in the automation and AI workflow buckets.

I know every 22-year-old with a YouTube channel wants to tell you otherwise, but “true” AI agent solutions, right now, are rare. Even rarer are agents doing valuable work within organisations.

And when I say ‘agents’, I mean actual ‘agents’, not workflows.

I’m not being harsh. I think AI workflows and automations are very useful, just don’t call them “Agents”.

Before we move on, let’s talk about Model Context Protocol aka MCP, in the first image.

Unless you’re a backend developer or some super nerd (like yours truly), you might never engage with MCP. Nonetheless, let’s take this as a learning moment to once again impress at your next team meeting.

Model Context Protocol Explained

To understand MCP, we need to understand the limitations of Large Language Models (LLMs) on their own, with the challenges developers face when trying to make them useful.

Maybe this will make you feel a bit of empathy for your local tech team.

LLMs are good at tasks like writing text, answering questions based on their training data, or generating code snippets.

However, they can’t do anything meaningful in the real world on their own, such as sending an email, interacting with a calendar, or performing a specific task on your behalf.

So, we need to connect them to different tools and services.

We can do this through APIs…however, this relies on APIs being made available for applications to connect and constantly needing to be monitored. One API with an LLM is easy, but connecting multiple tools to LLMs through APIs is difficult.

Now, MCP helps solve this problem by acting as a universal translator to simplify these connections.

Think of it as a layer between the LLM and all the different tools and services it might need to interact with. Instead of the LLM having to learn and manage every single service (through an API), MCP translates the different "languages" of all those services into a unified language for the LLM.

Now, either you got that, or I confused the s**t out of you.

If the latter, check out this vid, which should resolve that.

To Agent or not to Agent, that is the question

Every tool has its time and place.

I say that too often. Much like LLMs, and AI in general, Agents aren’t the answer to everything. Knowing when (and when not) to call upon the powers of an AI agent is a skill in itself.

My best advice is actually stolen from an engineer at Anthropic (creator of Claude).

Barry Zheng (Applied AI team at Anthropic) gave what I class as a legendary answer to the growing trend of people trying to apply agents to every problem, even when simpler systems would suffice.

“Don’t go after a fly with a Bazooka”

Barry Zheng (Applied AI team at Anthropic)

Magnificent!

I see this so much these days with a lot of tech.

So many tasks can be done in a few minutes by a human, but we'll spend hours trying to get AI to do it. Surely, that's counterintuitive to the goal?

Barry also shared this useful slide from one of his live talks (if you’re reading this, Barry, I’m not stalking you - promise!).

And to echo what Quentin Villard shared on LinkedIn, here’s a quick framework to figure out the best tool for the job:

  • If a task requires interacting with external services or your digital environment and is not set up as a workflow or agent, you need to do it yourself. Use a degree of common sense here. If the task is simple or you enjoy it, use that supercomputer in your head, aka the brain.

  • Choose an AI workflow for repeatable, rule-based tasks where you want predictable automation.

  • Choose an AI agent for tasks where you have a goal and want the AI to dynamically figure out the steps, acting as a flexible assistant.

Final thoughts

Ok, this one has gone on for far too long.

I feel if I go any further, this will morph into “middle-aged man rages against youth over AI agent definitions”, so I will close here for now.

Of course, there’s much to say about agents.

I’m sure you’re hearing lots of people give their two cents. The purpose of today’s edition is to make you a bit wiser in those discussions. I’ve always been big on not believing everything you think and read. I hope that doesn’t make me sound like a conspiracy theory nut!

This space will continue to grow faster than my cups of tea can brew, but that doesn’t mean you need to be flying at the same speed.

Deep and meaningful understanding requires a moment or two to breathe.

Agents are here, they’re useful, and it will only become easier to access them in shared marketplaces. As always, absorb what is useful, discard what is not and add what is uniquely your own.

I didn’t say that, Bruce Lee did, fyi.

That’s it from me today.

If you’ve got questions on agents and uses in L&D, shoot me a message by hitting ‘reply’ to this email.

→ If you’ve found this helpful, please consider sharing it wherever you hang out online, tag me in and share your thoughts.

Till next time, you stay classy, learning friend!

PS… If you’re enjoying the newsletter, will you take 4 seconds to forward this edition to a friend? It goes a long way in helping me grow the newsletter (and cut through our industry BS with actionable insights).

And one more thing, I’d love your input on how to make the newsletter even more useful for you!

So please leave a comment with:

  1. Ideas you’d like covered in future editions

  2. Your biggest takeaway from this edition

I read & reply to every single one of them!

 👀 ICYMI (In case you missed it!)

  1. Why Digital Intelligence is the critical missing skill in the L&D toolbox. It’s hard to operate in the world without a bit of tech savviness. I still see this missing from a lot of the L&D skills that are paraded in frameworks. That needs to change.

  2. How to evaluate the actual worth of AI agents in your work. Since we’re on the topic, why not go a little deeper with some counterpoints to the current “AI agents are God” narrative?

  3. Even the smart folks at BCG want you to recognise the AI hype. They share the view that agents will be useful, but are thoroughly overhyped right now.

 VIDEO THOUGHTS 💾

How To Build Powerful Case Studies with AI

Want an interesting -30 minute AI experiment in L&D for the week?

I got you covered!

I shot this video before NotebookLM became mainstream with its audio overview features. So, look at this as an alternative and an opportunity to try something different.

🙋‍♀️ Want to reach over 5,000 L&D pros? Become a Newsletter sponsor in 2025

P.S. Wanna build your L&D advantage?

Here’s a few ways I can help:

Reply

or to participate.