The Three Cs: Why Experience Matters More in the Era of AI
We are currently witnessing a shift where the act of writing code is becoming a commodity. We have been moving in this direction for some time - even before the fancy tools we have now, but with a well-structured prompt, a modern AI can generate a functional solution in minutes that would have taken a senior developer days to write just a few years ago.
But there also exists a trap in this newfound speed.
Just because a tool can create a solution quickly does not mean it is the right solution now or for the long term. As the cost of generating code drops to near zero, the value of the human at the keyboard shifts away from syntax and toward three specific pillars. I call these the Three Cs: Compassion, Creativity, and Competence.
And, yes, I came up with that - for better and worse.
Compassion: Solving for the Human, Not the Machine
AI is excellent at optimization, but it is incapable of empathy. It does not understand the frustration of your user navigating a confusing interface or the anxiety of a business owner facing a critical system failure.
Compassion in engineering is the ability to look past the technical requirements and understand the human impact of a project. It is about asking if a solution actually makes someone's life easier or if it just adds another layer of complexity. When we build with compassion, we create tools that people actually want to use. This is something no algorithm can replicate because an algorithm has never felt. Full stop.
Creativity: The Art of the Non-Obvious
An AI model is essentially a high-end pattern matcher - a stochastic parrot. It looks at what has been done before and predicts what should come next. This is useful for boilerplate and standard features, but it is the opposite of true creativity.
Creativity is the ability to connect disparate ideas to find a novel path. In my opinion, good product managers create something "listenable" out of polytonal inputs. It is about strategically breaking the rules rather than following them. In my thirty years of tech, there was never a manual to follow - in the 1990s we were creating Wordpress for teachers before Wordpress existed. The best solutions came from a human (project manager, developer, admin assistant) seeing a problem from a completely different angle and speaking up or taking a calculated risk. AI assists with the "how" of a project, but human creativity is still the only source of the "why."
Competence: The Wisdom to Guide the Tool
This is where decades of experience become a competitive advantage. It is one thing to have an AI generate a script. It is another thing entirely to know how that script will behave when it is integrated into a legacy system with ten thousand users.
Competence today is not about memorizing commands. It is about the ability to recognize when a solution is "too clever" to be stable - whether technically or because of the human processes or politics that exist in a specific environment. It is the ability to guide the AI toward a solution that is maintainable, secure, and scalable. A junior developer with a great AI tool can build a demo in a day. An experienced expert uses that same tool to build a foundation that will still be used and stable in five years.
The New Role of the Expert
We are moving into a phase where the developer acts more like a conductor than a solo performer. The tools provide the notes - often polytonal, but the human provides the tempo, the soul, and the direction (see Richard Bona).
If you are looking for a partner who understands that code is just a means to an end, [let's talk](If you are looking for a partner who understands that code is just a means to an end, let's talk about how we can use these three pillars to build something that truly lasts.