Age of the Expert Beginner: AI is no match for natural stupidity.

In late 2012, Erik Dietrich published his renowned article How Developers Stop Learning: Rise of the Expert Beginner, part one of a four part series –?more on that later. Erik goes on to talk about technical team members who become stuck in a cycle of non-improvement, thinking they've reached the top of their field.

12 years later I think we're seeing more Expert Beginners than we've ever seen before. However, now these are individuals who – with the help of AI tools – seem competent on the surface but lack the deep experience needed to tackle complex problems. In this article, we'll explore why this phenomenon is becoming more prevalent and what it means for technology leaders today.

The Rise of the Expert Beginner in the Age of AI

AI is shaking things up. It's making it easier for newcomers to appear competent in fields they’ve just entered. Think about it: with tools like ChatGPT and Copilot, anyone can generate code snippets or draft technical documents without fully understanding the underlying principles.

But here's the catch—while these tools provide a shortcut to apparent proficiency, they don't replace the hard-earned wisdom that comes from years of experience. It's like giving a novice carpenter a high-end power tool. Sure, they can make cuts more efficiently, but without knowing how to read blueprints or understand structural integrity, the end result might be a house of cards.

AI Levels the Playing Field—but at What Cost?

In a previous article I discussed how AI is democratising access to knowledge and skills across the board, and while this is overall a good thing, there are potential problems. A recent article from Harvard Business Review discusses how AI tools (generative AI tools specifically) are enabling people to perform tasks they were never trained for. This is both exciting and a bit concerning.

On one hand, we're seeing increased productivity and innovation. On the other, we're facing a surge of individuals who might overestimate their abilities and fool those around them with the results they can deliver with the help of AI – even themselves. They can produce work that looks polished but may have critical flaws beneath the surface or when being adapted to specific use-cases.

You Can't Beat Human Experience, Not Yet

Skills aren't just about knowing what to do; they're about knowing why and when to do it. We already know that LLMs can't reason, not really. This is where human experience will fill the gaps of expertise provided by AI for the foreseeable future.

Traditionally, expertise is gained through a combination of education, practice, and, importantly, learning from failures. AI can assist with the what, but it struggles with the why and when and certainly struggles to adapt to unique edge cases. It doesn't teach you how to troubleshoot a system when things go awry or how to make judgment calls in ambiguous situations. These are nuances that only come with experience.

Consider the field of medicine. A doctor can use AI to help diagnose a patient - often with equivalent or greater accuracy than doctors - but the intuition to spot an outlier in complex cases or to consider a rare condition comes from years of practice and exposure to countless cases.

When AI Empowers—and When It Misleads

For seasoned professionals, AI is a powerful ally. It can handle mundane tasks, crunch data at lightning speed, and even provide insights that might take humans much longer to uncover. This help can't be overestimated and I genuinely believe the future will see competent technologists exceedingly elevated in their craft.

However, for the inexperienced, AI can be a double-edged sword. It provides just enough knowledge to be dangerous –?and apparently competent to other novices. These individuals might not realise the limitations of the tools they're using, leading to overconfidence.

Erik Dietrich pointed out that the "Expert Beginner" often occupies positions of influence without the requisite expertise. In the age of AI, this scenario is becoming more common. It's easier than ever to produce work that gives the illusion of competence.

Spotting the AI-Enabled Expert Beginner

So, how do we identify these Expert Beginners in our consultants, teams, and organisations? Here are some signs to watch out for:

• Superficial Understanding: They can talk the talk but struggle when you dive into the details.
• Over-reliance on AI Tools: They depend heavily on AI outputs and can't perform tasks without them.
• Lack of Problem-Solving Skills: When faced with unique challenges, they don't know how to adapt or defer to AI.
• Dismissive of Experienced Advice: They often ignore input from seasoned professionals, believing they know best.

Being aware of these traits can help leaders mentor these individuals more effectively and prevent potential issues down the line, but mostly the best thing you can do is have a trusted expert in the room to provide candid feedback.

The Road Ahead

Erik Dietrich wrote a follow-up piece titled How Software Groups Rot: Legacy of the Expert Beginner. This is unfortunately what I think we can see now that the Age of the Expert Beginner has properly dawned, thanks to AI.

The gist is simple: if left unchecked, Expert Beginners can lead clients and teams astray, making decisions that have long-term negative impacts. They can roll out solutions that aren't robust, scalable, or serviceable. This isn't just a software development issue; it's relevant to any industry embracing newfound experts over-leveraging AI in the solutions they offer but don't understand.

How Can We Balance Innovation with Wisdom?

As technology leaders, we have a responsibility to ensure that we're not just chasing the latest tools but also fostering true expertise within our teams. AI is here to stay, and its influence will only grow. The challenge for us is how do we properly protect ourselves, our teams, and organisations from illegitimate vendors, externally and internally while still ensuring we get the best AI has to offer.

As Erik stresses in his articles - we should encourage continuous learning and emphasise the importance of experience. AI can augment our abilities, but it shouldn't replace the foundational knowledge that comes from years of practice.

Something to be critically aware of is the Expert Beginner could be you. AI is increasingly insidious in uplifting our perceived competencies. While this article focuses on the rise of Expert Beginners beyond ourselves, it's important to candidly assess how we perceive and project our own skills.

In the end, it's about balance. Embrace the new without discarding the old. By doing so, we can navigate this new landscape effectively, leveraging AI's benefits while avoiding the pitfalls of the Expert Beginner.