Almost Timely News: 🗞️ What's In An AI Workshop? (2025-05-04)

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May 04, 2025

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What's On My Mind: What's In An AI Workshop Anyway?

Happy Star Wars Day, fellow nerds.

I’m wrapping up five weeks of travel - San Diego, Wilmington, Miami, Chicago, and DC (I have a week break before Toronto and then two weeks until Phoenix) - and while the spring conference season has been a breakneck pace, it’s been incredibly enjoyable.

I just wrapped up my twice-yearly 2 day AI bootcamp with the Society for Marketing Professional Services (SMPS), the professional society for architecture, engineering, and construction (AEC) professionals. I’ve been doing these workshops for a couple of years now, and they’re so enjoyable because we get to dive deep into things I normally don’t have time to do more than gloss over in a keynote.

What’s always stunning to me is how fast AI changes. I refresh my training materials before each event, and this time around - even though it hasn’t been all that long in calendar time - I had to toss almost 50% of my materials because AI has changed so much.

I’ve been around for almost five decades now. In that time, I have never, ever seen a technology accelerate as fast as generative AI has in the last 3 years. The first inkling I had of generative AI was in 2021, when Eleuther.ai released its GPT-J-6B model. It was the first model I tried that generated coherent text that didn’t look like someone tripped and fell with a Scrabble tileset. In just four years, we’ve gone from bare coherence to reasoning models that can build deployable software in the browser and write entire, decent quality novels in one shot.

Change in AI is constantly accelerating, which is why a bootcamp can be useful, a way to get people up to speed with at least the basics. Now, I can't cram a workshop into a newsletter, but I can give you a sense of what I cover as an example of what you might want to look for in AI workshops.

Let’s take a tour of the workshop in brief, with the understanding that a 12 hour workshop isn’t going to fit in a newsletter.

Part 1: Workshop Prep

One of the main takeaways from the previous workshops I’d done is that a significant minority of participants really wanted to use the generative AI tools on the exercises, but they either didn’t have access to, or weren’t permitted to use their own company data with generative AI tools. Many of the exercises use data sources like Google Analytics, CRM data, competitive data, etc. As part of the prompt structures, and without that data, the prompts don’t work as well.

So the major change for the 2025 workshop is that I have a huge amount of synthetic data included with the workshop - a fictional company, its competitors, RFP examples, clients, RFP responses, competitive analysis, Google Analytics data, call center transcripts, email exchanges - basically, everything you would want in a comprehensive marketing analysis but you might not have, or it might take you far too much time to gather before or during a workshop.

The reception to this change was night and day. Far more people participated in the exercises than in past workshops; by my rough guesswork, about 2/3 of the room was actively participating, whereas in past workshops it was half or less. And more people came up to me during breaks to say thank you for including all the materials.

In conversation with some attendees at meals, one of them remarked how excited they were to get all this stuff, because they could go back to the office on Monday and show their manager how much stuff they got, tangible evidence and things they could bring back to share with their teams.

I’ve been including “stuff” in my keynotes all year, and with this workshop, it was even more valuable. So, more stuff it is. Attendees even get the synthetic, generated hold music from the workshop to keep as well.

Part 2: The Workshop

The two day workshop is structured based on the topics in my standard one hour keynote, expanded greatly and with dozens of exercises for people to actually try. Here’s the general layout:

Introduction and Basics

We talk through the major impacts of AI from recent studies; I cover some of Professor Ethan Mollick’s lab results along with a handful of other very recent research to set the table about why AI is important. There’s a strong undercurrent on social media of people claiming that AI has no impact, that it’s a fad, that the technology doesn’t work.

Nothing could be further from the truth. In fact, AI is becoming so alarmingly powerful that last year, I retired the old saw that “AI won’t take your job but someone using AI will”. That’s mostly untrue now. Can AI do your entire job the way you do it? No. Can it consume so many of your tasks that your position could be consolidated and eliminated? Yes. AI models like OpenAI o3, Google Gemini 2.5, and the upcoming DeepSeek R2 are so incredibly smart (properly prompted) that there are few tasks they can’t make serious contributions to.

Check out this ad I made for a fictional AEC firm in 38 minutes as an example of how fast AI is evolving:

After that, we look at the landscape, digging into the major classes of models and giving attendees the current short list of what to use. Spoiler: unless you have a specific, narrow use case, use a reasoning model of some kind. And local models are the only guaranteed private AI - and today’s local models like Qwen-3-30B-3AB (you can tell a marketer did not name that) are absolutely incredible.

We then cover how language models work, and dig into prompt frameworks like the Trust Insights RACE 2.0 Framework, CASINO Deep Research Prompt, and a Prompt Optimization Meta-Prompt that makes just about anything better. The Prompt Optimization Meta-Prompt is one of the AI Trinity of “special sauce” techniques that makes AI better, along with Knowledge Blocks and Prompt Libraries.

Knowledge Blocks

Knowledge blocks are a concept I came up with back in 2024. The Trust Insights RAPPEL Framework was an early attempt at addressing the lack of context in most prompts, and for the most part it worked well. But with the advent of tools like Deep Research tools, it was time to evolve past that.

Knowledge blocks are pre-compiled libraries of text that function as jump-starts for any prompt. You drop it in with your prompt, and your prompt is instantly, vastly smarter. You might, for example, have a knowledge block about who your company is and what you do, or how you do your marketing, or a summary of your quarterly results from your analytics dashboards. Whatever the case is, they should be thorough and rich - the average knowledge block for me is between 15-30 pages long of incredibly detailed information.

We spend time talking through the different ways to generate those, especially some fun techniques for unlocking internal information at an organization.

Generative AI Use Cases for Marketers

Similar to the course of the same name, about half of the workshop is spent here. The use cases for generative AI are literally infinite, so we look at the 7 categories of use cases and then bountiful examples and exercises for each.

Extraction: pull data out of other data
Classification: organize and categorize your data
Summarization: turn big data into small data
Rewriting: transform data from one form to another
Synthesis: aggregate small data into big data
Question answering: ask questions of your data
Generation: make new data

One of the key points in the use cases is that the order of these techniques matters; each use case category ladders up to make the next category more effective. That’s why generation is at the end - once you’ve mastered the basics of the first six categories, what and how you generate data with AI becomes vastly better.

Piloting and Governing AI

After half the workshop, folks generally need a break from furious typing, so we spend some time talking through how to set up a pilot task force in an organization, how to identify AI use cases with the Trust Insights TRIPS AI Framework, how to set up an AI council and who should be on it (and who should not), and the Trust Insights 5P Framework for deployment across an organization.

One of the easiest bench tests for whether a task is a candidate for generative AI is the “groan” test. What tasks do you really dislike doing? What tasks make you slump in your chair when you think about doing them? Those are the first tasks you should be decomposing and handing off to generative AI.

The example I usually give is expense reports. I don’t like doing them. But now with a set of prompts and the source data, what took me 2 hours (admittedly, 90 minutes of that was procrastination) now takes 2 minutes, and I don’t dread it nearly as much any more. It’s still not something I’d do for leisure, but it’s no longer something that I outright hate.

The Dark Side

Appropriately named for Star Wars Day, the next section of the workshop digs into the dark side of AI, the things that go wrong, the things that are problematic with it. We cover:

Bias
Security risks
Censorship
Copyright issues, both upstream and downstream
Data privacy
Malicious use cases like deep fakes
Data security and models
Hiring and workforce implications
Sustainability
Limitations of generative AI
Regulation

Data privacy is one that’s straightforward to explain. A general rule of thumb is that, just as with social media, search, and other digital channels, if you’re not paying, you are the product. All those “free” AI tools are not free. You are paying with your data.

Which is a HUGE problem for companies that refuse to have an AI policy AND refuse to provide paid, secure AI tools to their employees. Something like 90% of knowledge workers now use AI in some capacity, whether or not they have approval from their companies. When an employee is using a “free” tool with your confidential data, they’re essentially handing it to a third party.

It’s not enough to have a policy - and if your policy forbids it, good luck with that. Remember all those companies that had “no mobile phone” policies at work? Employees ignored it. They’ll do the same with AI tools, so if you want to get ahead of the data privacy issue, give people tools to use that are safe and secure.

Impacts on Marketing

After an unsettling half hour or so on the dark side, we pivot to AI’s impact on marketing. Recent studies from companies like AHREFS have shown that generative AI overviews in Google Search are eating clicks, with the top search result losing 34% of its traffic on average. (And that means positions 2 and 3 may as well be page 2 results)

More users use generative AI to do tasks formerly done by search engines as well - probably half of the people I talked to have planned vacations and trips entirely in an AI tool like ChatGPT.

We review the Trust Insights Generative AI Optimization toolkit and the ABC of mitigating AI’s impact on your marketing:

Audience: building audience loyalty in non-mediated channels (like this newsletter!)
Brand: building your brand with AI-focused techniques like content generated specifically for AI crawlers and tools
Community: building a loyal community you can reach directly, like Analytics for Marketers, my Slack community

Party Time

After a heavy hour of risks and AI impacts, everyone needs a break and some levity. I demo Eleven Labs, Hume, Veo 2, Sora, Adobe Podcast, and then we get to one of my favorite capstone projects: song construction.

Using a combination of a generative model like ChatGPT or Gemini, I have attendees take a piece of dense text, like an RFP response, and with a specially-designed prompt, turn it into song lyrics. Then attendees put that into a song generation utility like Suno or Riffusion and enjoy hearing their ridiculous song brought to life.

This time around, I heard reggae, pop, rap, country, and metal versions of RFPs. And you know what? Most of them sounded pretty decent. Grammy winning? No. But a good laugh? Yes.

Here’s an example of one - I took the closing sponsor speaker from day one, Rachelle Ray from Open Asset, and her talk, transcribed it, then had Gemini render it as a symphonic metal song’s lyrics, then produced it with Suno, then remastered it with Matchering and assembled it in Adobe Premiere. Again, will it win a Grammy? No. But does it leave a lasting impression AND differentiate how her message could be shared? Sure does.

I emphasize in this section, given the capabilities of generative AI, that as marketers and professionals that our work with generative AI in these media should be additive; that is, use it for things you would never have done before. Where possible or necessary though, professionals should still hire other professionals for important content. For example, if you want music you own the copyright to, hire a human musician. The same is true for words, images, interactive, and movies - if you need to hold the copyright, hire a human.

Someone generating a song from an RFP response is in no way going to take work away from a fellow human because we never would have made that work to begin with. But using AI to make your company’s audio branding absolutely not only takes work away from a human, it makes enforcing your copyright on that audio branding impossible in most countries on Earth.

Finishing Up

After the whirlwind tour of generative AI, I spend some time on the career implications of AI. Unsurprisingly, as I said earlier, AI absolutely will start taking jobs. Our job is to stay ahead of it, learn how to use it and direct it, supervise it, and manage it.

We finish off with a look at the near future of AI, where things are going, from new models to new applications to new concepts like agentic AI. I always have a bit of fun designing and building an agent live, on stage, so people can see it at work. For example, at SMPS, we built a proposal evaluator right in n8n on stage in under 5 minutes that evaluates RFPs and scores them as to whether a firm should even bother bidding on it or not.

Then we get into my favorite part of every workshop and talk: the extended Q&A. Attendees are encouraged to ask questions throughout the workshop, but I also strongly encourage them to bring even more questions to the final session, things that we might not have covered in the curriculum, concerns they have, or things that were unclear in the rest of the program.

I love Q&A the most of any part of a talk because it’s where I get to hear the real problems people are facing. I get to think things through with them, demo and build stuff live, and collaboratively solve problems or at least set a strategy for doing so. The questions people ask go into a catalog for me to answer later on in content like this, on the Trust Insights podcast or livestream, on Marketing Over Coffee… you get the idea.

Q&A is also where I feel like I differentiate myself most from my peers and colleagues. Lots of people can give a solid theoretical talk or a talk with canned examples from the stage. Not nearly as many people can pop open an AI tool or coding environment and just build live, solve problems on the spot. One day, when I have a live event of my own (hit reply if you’d pay to attend one), the closing keynote will just be an AMA: you, me, and my laptop.

Part 3: Wrapping Up

So that’s what two days of AI boot camp looks like with me. Everyone walks away with a prompt handbook, the training materials so they can practice again and again when they go back to the office, plus all the presentation assets. I use AI and all my favorite tech tools to produce the video, audio, cleaned transcripts, and summaries for people to take back to the office with them, the pile of stuff they can proudly show off and re-use in the weeks and months to come.

This kind of workshop is a significant investment for a company to put on and for the people who attend it. It takes time, budget, and commitment from attendees to be out of the office for two days, but in some ways, I think it’s a better deal than a conference. Conferences are amazing for getting lots of different viewpoints, for networking, for getting a lay of the land. They’re a vitally important part of professional development.

But a bootcamp is a concentrated dose of learning. One instructor, one focus, and as much information sa you can handle in a massive power-up. Bootcamps and workshops are a chance to put hands on the keyboard and DO, not just hear about ideas that you never get around to trying because real life takes over the moment you set foot in the office. A bootcamp gives you time think, do, and reflect, and it’s my privilege and honor to conduct them for organizations like SMPS and the many other companies that have hired Trust Insights to put on bootcamps.

Ideas are great.
Actions are better.
Experience is the best.

And that’s what a bootcamp delivers for the attendees - it builds realtime, real world experience when it’s done well, and when both instructor and attendees are all-in.

Part 4: Shameless Plugs

If this all sounds good, first a few plugs:

I’m doing a half day workshop at the Marketing Analytics Summit in Phoenix in June.
I’m doing a half day workshop with my favorite co-instructor, Katie Robbert, at the Marketing AI Conference in Cleveland in October.
And I’m doing another two day bootcamp workshop with SMPS in Denver in October.

But I’m also available to do these workshops at your company. When I do workshops for companies, I find them to be even more valuable because now there’s a singular focus - that company’s needs and specific problems. After all the NDAs are signed, I’m often able to prepare training materials tuned on a company’s actual data (or generate synthetic data that’s very close to the real thing - at one corporate workshop, the marketing director lamented that they wished their actual data was as clean as the simulated data), and provide real knowledge blocks for that company.

If that’s of interest to you, hit reply and reach out, or ping me on the contact form.

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