Ready to join the next edition?
17. March 2027
Copenhagen
Building Your Professional ‘Spidey Sense’ in the Age of AI
Jomar Reyes
I knew about Simo Ahava long before I really knew Simo.
For years, working around the web analytics industry, I would hear people refer to something Simo had written or said. He was one of those people whose name kept coming up in conversations: “Simo says…” or “Have you seen what Simo wrote about this?”
Today, Simo is co-founder of Simmer, the technical marketing training company he founded with Mari Ahava, where teaching and helping people develop their technical capabilities have become a major focus of his work.
I have to admit, I wasn’t one of the people religiously following his blog. My brain has always tended towards the strategic rather than the deeply technical, and Simo’s work could get pretty technical. But I could see how strongly his thinking resonated with the people around me.
I eventually got to know him when he came to Copenhagen. He spoke at Web Analytics Wednesday Copenhagen many years ago and ran a couple of masterclasses with us, all before BLC itself was created. Over the years I’d also bump into him at Superweek, where we’d usually manage a quick chat and a bit of a laugh.
What has always struck me is the contrast between Simo’s standing in the industry and the person you actually meet. He has built an enormous following and become one of the most influential voices in analytics, yet I’ve always found him incredibly approachable. He’s always been happy to answer my questions, including the ones coming from my considerably more strategic brain, and has retained a humility that I think is part of why people connect with him.
What makes Simo stand out, though, isn’t simply the depth of his technical knowledge. It’s his ability to turn that knowledge into understanding for other people.
He can take something deeply technical and reveal why it matters, connecting the technical people in the room with those thinking more strategically or operationally. It’s a quality I’ve seen both in his talks and when watching him teach.
Webcast Epsiode: See the full episode of the AnalyticsDev.net webcast featuring Simo Ahava, hosted by Gunnar Griese, Steen Rasmussen and Jomar Reyes.
Join future live AnalyticsDev.net Webcasts and register here
Bringing Simo back into the conversation
So it was great to have Simo join us again, this time as the first guest on the new AnalyticsDev.net Webcast, which I hosted alongside Steen Rasmussen and Gunnar Griese.
The webcast also gave us a chance to look ahead. Simo will be returning to Copenhagen as the keynote speaker at the second AnalyticsDev.net event, continuing a relationship with this community that stretches back many years.
In some ways it felt like things had come full circle. Our relationship with Simo goes back to Web Analytics Wednesday and those early masterclasses in Copenhagen. Now we were sitting down again, years later, with an analytics industry being reshaped by AI and asking some pretty fundamental questions about what happens next.
What skills will still matter?
What happens when AI can generate the code that previously took years of learning to write?
Are we becoming better professionals because answers are easier to find, or are we in danger of skipping the experiences that taught us how to recognise whether those answers are any good?
And what should the next generation of analytics professionals actually be learning?
These are big questions, and Simo is particularly interesting to ask. He’s spent years working at the technical edge of analytics, but he’s also increasingly focused on education and training.
Rather than simply asking what AI can do, our conversation with Simo, Steen and Gunnar increasingly became about what humans still need to know.
And that’s when Simo mentioned his “Spidey sense.”
Developing your professional Spidey sense
Simo was talking about something that happens after you’ve spent years actually doing the work.
You develop an instinct.
When you see something that doesn’t quite look right, there’s a little signal in the back of your head. You might not immediately know what’s wrong. You might not even be able to articulate why you’re suspicious.
But something is telling you:
Hang on. Look at that again.
Simo described it during the webcast like this:
“If you don’t have that expertise and how your brain is wired, you lose the tingle in the back of your head that, ‘Hey, something is wrong here.’”
That really resonated with me.
I’ve said something similar to younger people in our industry for years: you develop instinct over time.
It comes through experience, both positive and negative. The projects that worked and the ones that didn’t. The decisions you got right and the ones you wish you’d made differently. The assumptions that turned out to be wrong. The difficult conversations. The mistakes. The unexpected successes.
All of that gradually creates a library of signals in your head.
Simo just gave me a much better name for it.
Your professional Spidey sense.
Steen immediately picked up on the same idea from another direction.
He described it rather more colourfully as our “bullshit detector.”
His concern was that if we increasingly learn through AI-generated answers without building the underlying expertise ourselves, that detector becomes weaker.
“Their bullshit detector, their spider sense becomes so much weaker.”
It’s a funny line, but there’s a serious point underneath it.
If everything sounds plausible, how do you know what isn’t?
But what happens to Spidey sense when AI has the answer?
This is where our webcast conversation really got me thinking.
We’re increasingly treating AI as our assistant, our sparring partner and even our digital twin. And I think that’s a good thing. We should use it, nurture it and allow it to support us in becoming better at what we do.
But we shouldn’t outsource our Spidey sense to it.
In fact, I think AI could help us develop and sharpen it.
Our instinct might tell us something isn’t right. AI can help us investigate why. It can test an assumption, find another perspective, introduce evidence we hadn’t considered or challenge us when our instinct is leading us in the wrong direction.
Because our instincts aren’t right 100% of the time either.
Spidey sense is a signal. The interpretation of that signal is what matters.
And that’s where we humans need to remain firmly involved.
Perhaps the opportunity isn’t to choose between human instinct and artificial intelligence at all.
It’s to become better at combining the two.
The fundamentals don’t disappear just because the tools get better
One of Simo’s strongest observations during our conversation was:
“What will never change is the need to have those foundational skills and that critical thinking.”
For me, this is where the discussion becomes much bigger than analytics.
The tools we use are changing incredibly quickly. Tasks that once required specialist knowledge can now be completed, or at least attempted, with a well-written prompt.
Simo made the point very directly when talking about coding:
“You don’t have to learn to code to generate code, right? You just have to be able to prompt it well.”
That’s an extraordinary opportunity.
But there’s an important distinction between being able to produce something and understanding why it works.
Gunnar reinforced this during our conversation. His point was that as AI makes answers more accessible, we actually need greater discipline in how we approach those answers.
That’s an important distinction.
The value of expertise isn’t necessarily that the expert can produce an answer faster anymore. AI might win that race.
The value is understanding the foundations well enough to evaluate the answer.
Simo summed up the relationship between AI and those foundations simply:
“We need a foundational basis for AI to actually flourish there.”
If you’re working in analytics, those foundations might include data collection, tagging, browsers, JavaScript and measurement.
For a strategist, they might be markets, customers and competitive dynamics.
For a marketer, consumer behaviour, positioning and measurement.
For a leader, people, organisations and commercial fundamentals.
AI changes the execution layer much faster than it changes the foundations underneath it.
It’s to become better at combining the two.
Don’t skip the difficult bit
This was another part of Simo’s argument that stayed with me.
“Doing it manually is what builds your muscle memory. It’s what rewires your brain in a certain way to understand that concept better.”
There is an interesting tension here.
Most technology is designed to remove friction. We want things to be faster, simpler and easier.
AI takes this to another level because it can remove not just repetitive work, but some of the thinking that previously went into completing that work.
That’s fantastic when the friction is pointless.
But what if some of the friction was actually learning?
Steen raised this during our discussion by contrasting being digitally comfortable with genuinely understanding the technology underneath what we’re using.
We can become incredibly capable operators while still being technically naive.
Everything works beautifully, until it doesn’t.
That’s when the difference between operating something and understanding it becomes apparent.
Think about the first time you had to solve a genuinely difficult professional problem.
You probably weren’t very efficient.
You tried things that didn’t work. You asked people questions. You went down the wrong path. You came back. Eventually you understood something you hadn’t understood before.
The answer mattered.
But so did the journey towards it.
That experience becomes another small piece of your professional Spidey sense.
So I’m certainly not suggesting we deliberately make our work inefficient.
Instead, perhaps we need to become more conscious about distinguishing between friction we should automate and friction we need in order to learn.
From masterclasses to Simmer: teaching people how to think
This also made me think back to watching Simo teach.
When he delivered those early masterclasses with us, what stood out wasn’t simply the amount he knew. It was his ability to explain technical concepts so that people could understand the thinking underneath them.
You see the same quality when he speaks.
And you could hear it throughout our webcast conversation.
That’s why what Simo and Mari have subsequently built with Simmer feels particularly relevant.
Simmer is focused on technical marketing education and on bridging the divide between technical and non-technical practitioners. At its heart is an idea I recognise from knowing Simo: curiosity, practical learning and sharing knowledge.
There’s something particularly important about that in the AI era.
If information itself is becoming abundant, perhaps the role of the teacher changes too.
The value isn’t simply transferring information from somebody who knows something to somebody who doesn’t.
AI can already do a lot of that.
The value is helping someone understand, ask better questions, connect ideas and eventually develop enough experience to challenge the answer they’re being given.
In other words, helping them build their own Spidey sense.
It’s also one of the reasons I’m particularly looking forward to having Simo keynote the second AnalyticsDev.net event. His ability to connect deep technical knowledge with learning and understanding is exactly the kind of conversation we want Analytics Dev to create.
AI needs your expertise too
There’s another side to this that I think we sometimes overlook.
We talk a lot about what AI can teach us.
But the relationship works both ways.
The more context we give our AI tools about our work, objectives, preferences and thinking, the more useful they become as partners.
I’ve certainly seen that in my own use of AI.
But if we’re going to nurture an AI assistant, or even something approaching a digital twin, we need something valuable to bring to that relationship ourselves.
Our experiences matter.
Our judgement matters.
Our understanding of people and context matters.
Our mistakes matter.
Our Spidey sense matters.
Otherwise there is a danger that we’re simply asking one machine-generated answer to lead us towards the next.
The interesting opportunity is to create a loop where human experience improves how we use AI, while AI helps us examine and challenge our human experience.
My instinct says one thing.
My AI says another.
Why?
That’s potentially a very valuable conversation to have.
Your Spidey sense can be wrong
And this is important.
Experience doesn’t make us infallible.
Sometimes what feels like professional instinct is actually habit. Or bias. Or an assumption based on a world that has already changed.
Our Spidey sense might be sending us a useful signal, but we can still interpret that signal incorrectly.
This is one of the areas where I think AI can be a genuinely powerful sparring partner.
Ask it to challenge your assumption.
Ask what evidence would prove you wrong.
Ask it to argue the opposite position.
Give it the data and ask whether your interpretation is supported.
Use it to find the blind spots in your thinking.
That’s a much more interesting relationship with AI than simply asking it to give you an answer.
Don’t just ask AI to agree with your Spidey sense. Ask it to test it.
Data isn’t the answer either
Interestingly, the same argument appeared later in our webcast when we moved from AI into the role of analytics itself.
Simo said:
“The data itself isn’t the answer, like a number isn’t the answer. It’s what you do with that number.”
Again, the parallel with AI struck me.
For years we’ve sometimes behaved as though having more data would automatically result in better decisions.
Now there’s a danger of assuming having more AI-generated answers will automatically make us smarter.
Neither is necessarily true.
Steen pushed this further when he talked about how organisations actually use data:
“Data has become a negotiable. So it’s not a fact, it’s negotiable.”
We can collect enormous amounts of information and still interpret it according to our existing assumptions, politics or preferred narrative.
Simo described analytics as an organisational discipline, something concerned with how information flows through an organisation rather than simply producing numbers.
Gunnar added an important warning here too: if conversational AI makes information travel through organisations faster, poor foundations and incorrect assumptions can travel faster with it.
That’s another reason our professional Spidey sense matters.
AI doesn’t only accelerate good thinking. It can accelerate bad thinking too.
Don’t just ask AI to agree with your Spidey sense. Ask it to test it.
How do we build professional Spidey sense now?
This leaves us with an important question, particularly for people earlier in their careers.
If AI increasingly handles the basic tasks through which previous generations gained experience, how does the next generation develop that same instinct?
I don’t think the answer is avoiding AI.
Quite the opposite.
We need to learn how to use it while deliberately continuing to develop ourselves.
Learn the foundations even when AI can perform the task. You don’t necessarily need to become an expert in everything underneath the technology, but you need enough understanding to know what questions to ask.
Do things manually sometimes. Particularly while you’re learning. Understanding what happens underneath the automation makes the automation much more useful.
Get things wrong. Mistakes aren’t simply failures to be eliminated from a perfectly optimised career. They’re part of how judgement develops.
Spend time with people who know more than you. Ask them why they disagree with you. Watch how they approach problems.
Teach what you know. There’s nothing quite like trying to explain something to another person for exposing the gaps in your own understanding.
And, importantly, use AI to challenge you rather than simply reassure you.
That’s how I think we can start using these tools to develop our Spidey sense rather than allowing them to gradually weaken it.
When information is everywhere, people matter more
Towards the end of our webcast, Steen made another observation that connects all of this:
“It’s knowledge sharing, but it’s really about meeting people.”
This came as we were talking about Analytics Dev and why people still travel to technical events when so much information is now available online.
It’s something we’re thinking about a lot at BLC.
Information is no longer scarce.
I can ask an AI almost any professional question and receive an answer within seconds. Tomorrow that answer will probably be better than it is today.
So why attend an event?
Why take a course?
Why join a professional community?
Why sit down with somebody like Simo and have a conversation?
Because learning was never only about transferring information.
It’s about interaction.
It’s having your assumptions challenged. Hearing how someone else solved a problem. Asking the question you didn’t know you needed to ask. Meeting someone whose experiences are completely different from yours.
Gunnar’s perspective on Analytics Dev reinforced this for me.
The foundations still matter, but events and communities also give practitioners a way to benchmark their understanding against other people, to see what’s changing, what others are struggling with and where their own knowledge might need developing.
That’s difficult to replicate through a chatbot alone.
Those human interactions become part of the experiences from which our professional instincts develop.
Perhaps that becomes more important, not less, as AI gets better.
Keep your Spidey sense tingling
Hosting the first AnalyticsDev.net Webcast with Simo, Steen and Gunnar left me thinking that we’re probably asking the wrong question when we ask whether AI will replace expertise.
A more useful question might be:
What kind of expertise becomes valuable when answers are everywhere?
I think Simo gave us part of the answer.
It’s the expertise that lets you recognise when something doesn’t quite add up.
Steen’s “bullshit detector.”
Gunnar’s emphasis on foundations, discipline and learning from other practitioners.
The experience that makes you stop before accepting the obvious answer.
The curiosity to ask another question.
The humility to recognise that your instinct might also be wrong.
And the critical thinking required to decide what to do next.
That’s our professional Spidey sense.
AI should absolutely be part of how we work and learn. It can become an extraordinary assistant, sparring partner and perhaps eventually something resembling a digital twin.
But let’s not allow it to do all our thinking for us.
Instead, let’s use it to challenge our assumptions, accelerate our learning and expose us to perspectives we might otherwise have missed.
And this isn’t the end of the conversation. Simo will join us again as the keynote speaker at the second AnalyticsDev.net event, where we’ll have the opportunity to continue exploring what all of this means for the people actually building, implementing and working with analytics.
Because in a world where getting an answer is becoming incredibly easy, knowing when to question that answer may become one of our most valuable professional skills.
About our guest speaker
Simo Ahava
Simo is Partner and Co-founder at 8-bit-sheep, Co-founder of Simmer, and the author of one of the most widely read and respected blogs in the analytics community. Across more than a decade of writing, teaching, speaking, and consulting, he has helped practitioners make sense of complex topics across Google Tag Manager, Google Analytics, data collection, privacy, tagging, and modern measurement.
About Simmer
Simmer is an online learning platform for technical marketers, co-founded by Simo and Mari Ahava. It offers practical, hands-on courses in areas such as JavaScript, Google Analytics, BigQuery, server-side tagging, data analysis, and browser tracking protections, helping marketers build stronger technical skills at their own pace.
