The hype around AI is increasing every day. Some people find it interesting and useful, while others do not accept it or fear that it will replace them or take their jobs. But this is more complex and needs more description, because we can categorise people in much more than 2 categories based on their reaction to the AI tools. However, I believe only our mindset causes these differences. Here, I will try to demonstrate how I use AI in my process(which is described in this post), and the correct mindset for using AI that led to this fact: There is nothing wrong with using AI!
Review and remap
Based on the Golden Circle model, we have why, how and what. We can map other words to these titles to better understand the concept. In other words, in each step, these verbs are happening somehow!
‘Why’ to ‘Leading’
In the ‘why’ step, we should find the roots or foundation of the thing we are working on; these findings or these ‘whys’ will lead the next two steps, so by finding ‘whys’, we lead the journey!
‘How’ to ‘Managing’
In this step, we shape the way that will lead us to the goal and the satisfaction of ‘whys’. This is exactly what a manager does. He knows the goal, the resources, and everything that is needed, and he tries to handle what is necessary to reach the destination. So in this step, we are managing!
‘What’ to ‘Execution’
After identifying the problems and the approach we want to use to solve them, it’s time for execution. By execution, I do not mean only doing it based on a written script;; I mean the process that leads to the output.
You are the boss!
I deeply believe that only by using this approach with AI will it be constructive in the long term; You are the boss, and AI is your employee!
As the team lead, you have to know the goal, the plans, and what is going on with every member of your team. Only by having this knowledge can you keep the team alive and achieve targets. Only by this structure can you scale and maintain the products or services.
Let’s get back to the model and add the AI to it.
In the first stage, we must not only lead but also manage AI, because we need these in most of our tasks:
1- Scalability
2- Maintenance
3- Adoption
The management term requires knowledge, so in some cases, you need specific knowledge or at least the mindset. I’m not saying you should know everything about React and CI/CD, but you do need to understand how a programmer thinks and how they manage the steps.
For example, you are a product designer and want to implement your designs for a mobile app. You need to know programming languages, the development process, and everything at an entry-level. If you implement without considering this point, you cannot count on your app in the long term. Of course, you will have a fully functional app with a brilliant look using tools like Cluade Code, but it is exactly like outsourcing it and having no clue what is going on, which will lose your agility and adoption power.
On the other hand, sometimes this is exactly what is needed, for MVPs or something like smoke tests, I can’t ignore this, and I have to mention that.
Consider a design system you created in Figma and want to implement it with React using Claude Code. For a design system, it is undoubtedly crucial to be scalable and adaptable, so we need to know how an experienced React developer works, how he thinks, how he starts, etc. We can obtain this ability by using AI again: ask him and learn in the fastest and best way. As you can see, you have the mindset now without being a developer. It is obvious that knowing how to code helps a lot, but by using AI (with the approach we discussed), we can perform much faster.
Each step can be split!
In each step, we are pursuing a specific goal. In ‘why’, we look for whys and goals; in ‘how’, we figure out the solutions and roadmap; and in ‘what’, we create the output. Why don’t we use the same thing in each step, too?
By splitting, we can keep using AI in each step too, in the optimal mode.
AI is unstoppable!
AI models and tools get better and better by the hour; we cannot ignore this. The only thing I’m sure about is that we can be much stronger with AI, but we must know how to make it work for us!
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