Beyond the Hype: A Friendly and Sceptic User’s Guide to ChatGPT (v1.5)

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Intro, or “Why like this!?” 

This guide is a labour of love for humans, not technology. It was born from my frustration with current writing about ChatGPT in general, and practical advice on LinkedIn in particular. And honestly — from a feeling of urgency, as I fear the bad advice will take hold and create bad business outputs, damaging careers and adoption rates for AI.  

Currently, the debate about ChatGPT’s usefulness (and the usefulness of language model chatbots in general) is dominated by the question “Is it a search killer?”. I believe this question comes from a spin that Big Tech propagates because it’s good for the share price. You can find my full view on that here.  But when this spin spreads into the practical discussion, framing our perceptions of how this tool may change our industry (by which I mean marketing, strategy, brand, media, creative, design, advertising, content, digital), the result is a blurry vision of what ChatGPT can do.  

This ‘blurry vision’ framing usually results in three kinds of ‘advice’:

  1. Don’t believe the hype
    “Look at the mistakes it makes, LOL; it’s not even as good as Google; there’s no serious use-case here. It’s a toy.” 
  2. This changes everything (superficially)
    “ChatGPT can do everything. Not only has research changed forever, and we no longer need to use search engines, but look at this brilliant [insert dull and superficial result] to [a crucial, nuanced and deep business/marketing/creative task].” 
  3. Moar content! Zero effort! 

“Here’s a listicle about how to use ChatGPT to create the most boring spammy articles and posts the world has ever seen.”

None of these are helpful,  or give meaningful guidance about how to use these new tools in our daily working life. Rather, they lead you down a garden path, at the end of which there’s a fork in the road and a signpost that reads, “this way to arid desert” or “this way to cloud-cuckoo-land”. 

Read the full guide here.

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Get/to/bye-bye strategy: how to fix advertising’s favourite framework

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smiling man with a tie, holding a hammer in his right hand and making a thumbs up gesture with his other hand. the thumb is bandaged.

This is the story of how a simple and ubiquitous framework threatens to break advertising.

There are many tools and frameworks across strategy, marketing, and advertising.

Have you ever noticed which ones tend to be the most popular?

Is it the smartest ones? The clearest ones? The most effective? The most validated by research?

Of course not!

The most popular ones are those which are easiest to explain and learn, and most importantly — easiest to sell. Internally to teams, and externally to clients.

Unfortunately, even simple frameworks are often not as simple as people think.

When misused – which I see happening more and more often — GTB cultivates bad work, promotes non-strategies, mismanages creative teams, and sets them and their clients up for failure. 

What’s the framework, and where does it come from?

 If you’re reading this post, you’re probably already familiar with the formula, which can usually be found lurking somewhere in creative brief documents. Some even use it instead of a brief, but more often it sits in the section summarising the creative strategy.

 There are various nuanced takes on it, but here’s the rough outline:

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Taming Marketing Babylon

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Prompt: the tower of babel made of neon marketing ephemera against a stormy sky (MJ5)

It’s often said that the very things that initially attract you to someone are the things that eventually begin to grate on your nerves. This old saying perfectly captures my relationship with the marketing industry.

Early days, I fell in love with Marketing’s creative, “whatever works” approach. A magpie-like mentality to pick and choose the best concepts and strategies for success from our own as well as other disciplines. Yet, over time, I have become increasingly frustrated with the neverending onslaught of synonymous, mutated, and spliced frameworks, models, labels, jargon, and “stuff”. It’s bloody exhausting.

The tragedy of this situation is that the genuine ideas, original concepts, research and science that underpin our profession are buried beneath this barely held-together tower of shiny marketing trinkets. This dearth of context and historical understanding has led me to call my blog “Marketing Babylon”. Way back in 2006, when I was still a fresh-faced agency-side rookie.

The paradox of marketing is that the creative freedom we love is both our saviour and our tormentor. It’s what makes our industry innovative and adaptable, but it also spawns a convoluted mess that leaves most marketers befuddled and, frankly, less effective. And in a classic “it’s always the children who suffer”, it also stunts the growth of our junior team members, even those with some formal training. 

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What to ask in a job interview when they say “So do you have any questions?”

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There comes the point in most job interviews when the interviewer asks, “Do you have any questions?” 🤔
There’s plenty of content on how to answer questions in an interview, but not much about how to ask them.

Here are some of my go-to favourites, specifically for creative agencies:

🚪 Tell me the story of the last time you fired a client. How long ago was it? What happened?

I’m not saying agencies should fire clients left and right. The point is many of my challenging experiences in agencies were due to the combination of difficult clients and weak leadership with poor boundaries or little regard for the team’s mental health. It often required me to step in and protect the team at a personal cost. The answer can be quite telling.

🌱 What’s the background of senior people? Did they grow within the business? How quickly?

This question is great for understanding diversity and potential career paths.

🏆 Tell me the story of a project/campaign you are particularly proud of. Followed by:
More briefly, what are some past projects that are typical of what I’ll be working on?

These questions can reveal a lot about values, culture, and working style. Pay attention to: How long ago was it? What do they choose to mention/spend more time on? Where’s their passion (if it’s there at all)? Who gets the credit? How does the story reflect ways of working and client relationships?

• What’s your social media policy?

This little question can help you identify red flags around control and micromanagement.

💻 What are your remote work platforms/tools?

This gives you an idea of the company’s agility and overall relationship with technology. Are they still using outdated systems? Have they adopted tools like Slack, or do projects still happen on endless “CC everyone” email chains? Do they think about AI?

💸 Towards the end, don’t just negotiate your starting salary. Ask – What is the typical policy/rate for raises, and how long after starting the job does it usually happen? What about for over-performance?

With most agencies, getting a raise can be like pulling teeth, especially the first one. Compensation should be more straightforward, and the culture surrounding it can reveal a lot. Growing, successful organizations tend to be competitive and honest. Even if the answer isn’t your ideal, it provides a guideline for future negotiations.

🤩 Don’t fall for the one nice room. Ask to have a walk around the studio.

Observe the entire work environment as it reflects the business’s health and the team’s priorities. Also, what’s the vibe? Do people seem happy? Relaxed? Stressed? Are there rushed individuals or playful teams?

What are your favourite questions to ask? 🧐

AI and creative development: Rocket fuel for human creativity?

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Rocket fuel for human creativity? 🚀💡
Hear me out…

I have spent most of my career leading teams in the quest for breakthrough solutions (and searching for them myself). The typical process combines two approaches: quality-dominated development of “new stuff” and quantity-dominated curation of “existing stuff”.

1. Quantity dominated: curating numerous references to existing stuff in the hope of discovering inspiration or direction. Mood boards and best-practice research both work that way. This approach is cheaper, faster, and less demanding. However, this approach might not result in the desired breakthrough due to its dependence on previously explored concepts.

2. Quality dominated: developing fewer bespoke things that have not existed before. Think of a quality storyboard/draft/wireframe or even good scamps. It is slower and requires creation and iteration, mindfully mining opportunity spaces. It’s quite resource-intensive (time, money, energy, attention, people) to reach even a rudimentary prototype.  

Typically, you start in quantity mode and progress to quality, then alternate between the two. 🔄

Enter a third, hybrid mode of strategic creative development, which has an interesting “serendipity acceleration” effect. This the agile-adaptive approach that AI unlocks. It mixes our original ideas with a vast field of references (wider than any human can hold in their head). 
It can start at either end and can rapidly move to the other:

– Quality to quantity: You develop a significant bespoke seed and feed it to an LLM, trained on existing references, to rapidly generate new results for you to iterate. 💡➡️🌐
– Quantity to quality: you use prompts to generate a large number of starting points which, in the absence of bespoke seeds, gravitate more towards the existing references, but take a “quantity is quality” approach and select the best of those to develop and craft further. 🌐➡️💡

Note how the typical shift between divergence and convergence thinking, crucial to success, becomes faster and more cost-effective.

The third mode cultivates a dynamic and responsive creative process. It’s like rocket-fuel for serendipity, turbocharging the creative journey and maximizing the chances of finding that elusive ‘Eureka!’ moment. By leveraging human-machine collaboration, this approach accelerates not only serendipitous discoveries but also enables rapid generation, iteration, and refinement of ideas, making it easier for creatives to reach “terminal velocity” in their pursuit of breakthroughs, all while reducing the cost and time required.

It’s already happening, don’t get left out.

Version 1.5 of “The Sceptic’s Guide to ChatGPT” is out.

Reroll to rule with ChatGPT (and the others)

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Will people ever stop using AI wrong? 🤖
Ha!
Discover why you can expect AI to be inaccurate across a broad range of business and marketing subjects.

(I’m not an AI evangelist nor a Luddite.
Nuanced opinions don’t sell on LinkedIn, especially with hyped topics.
But I’m going to keep trying anyway. 🤷‍♂️)

Here’s a simple experiment that shows why it’s risky to treat AI chatbots as founts of knowledge, especially in marketing and business.

I asked gpt4 and Bard a straightforward question posed by a client:
“What are the leading models and frameworks for mapping customer journeys?” 💡

The twist? I generated answers three times for each.

Results?
• High variability in gpt4’s responses, with differing list lengths and items.
• Over-indexing of thought leaders with large publishing volume / PR.
• Influential Nielsen-Norman group framework appeared only once.
• Bard’s anonymized labels made lists nearly useless.
• Both occasionally included loosely related concepts (e.g., AIDA)

Why does this matter? 🤔
On a practical level, result variance indicates if you’re in the AI’s comfort zone or twilight zone and how much fact-checking is needed. High variance? Be cautious!

But there’s a bigger issue. With many flavours and branded versions of customer journey mapping, LLMs struggle to find clear dominant patterns. This issue is common in marketing, strategy, and business concepts.

Let’s not force AI into corners. It’s just not a great desk research tool at this point. Regenerate and iterate for better clarity. 💡

(Version 1.5 of “the sceptic’s guide to ChatGPT” is out)

Language-Based AI: The Photoshop of Knowledge Work

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Adobe stock. Seemed only fair.

All analogies are flawed, but some are useful.

Language-based AI is like Photoshop for the rest of us. 🖥️💃⚡

Hear me out… (less than 2-minute read)

In the world of graphic design, there was a time when only the most skilled designers could create high-quality visuals. It required many years of training and was a time-consuming manual craft.

But then, a tool emerged that changed everything — Photoshop. Suddenly, everyone with a computer could create stunning graphics, and the speed of production increased exponentially. This tool democratised the craft of design, making it accessible to the masses.

Adobe’s Creative Cloud approached 30 million paid subscribers last December. 🤯

However, despite this democratisation, not all designers were suddenly equal, nor will they ever be. Just as it is with many types of skills and tools — equal access doesn’t guarantee equal performance, let alone greatness.

But wait, there’s more to this analogy. 🤓

Photoshop was more than just a tool for making graphics. It also enabled designers to experiment with new techniques (that in the wrong hands scream “photoshop”), create unique styles, and push the boundaries of what was possible in design. And they still use real-world materials and inspiration.

Do designers have to keep up with the evolution of Photoshop? Most of them do. Or you can find your comfort zone and stay there. But unless you’re amazing, it comes at a price. Or you can decide you’re a 100% old-school craft artisan or let someone else import your work into Photoshop. There are implications for that too.

The arrival of AI in knowledge work is like Photoshop for the rest of us. AI is transforming the way knowledge workers operate, automating tasks we didn’t think could be automated, speeding things up exponentially, and providing new possibilities previously impossible.

But like with Photoshop, AI still requires human expertise to use effectively.

You are the designer, not AI.

Education, talent, and hard work still count. Hard work beats talent sometimes, but only up to a degree.

The power of AI lies in the hands of those willing to keep learning and adapting to the technology. But just because you have access to AI tools doesn’t make you a master of your field.

And downloading a pirated copy of Photoshop doesn’t make your nephew a top-tier graphic designer.

But maybe he could help you with that lost dog ad or retouch your dating photos.

Speaking of which, have you tried using it for job applications? It’s a game-changer. 😅

Finally, word processors that can actually process words.

But that’s another analogy…