Recently I have been struggling between staying focused to learn coding and building with AI to get projects on my portfolio faster. But as a person who loves to learn from the ground up, I have decided to stay with the former. However I also want to keep up with the industry standard to stay relevant.
So here is my approach to balancing both:
Learn the fundamentals (without AI):
Fundamental is key. Focusing on the fundamentals at this early stage would help me understand what is important and why. For example:
- How the web works
- The concepts of the clients, server and APIs.
- Why every HTML tags and attributes are used
- Why using semantic elements over divs improves accessibility
- Why CSS is relevant and different ways to implement it
- Why frameworks and libraries?
- How frameworks build upon their vanilla counterparts.
- How to figure and debug my codes
- Knowing a good code from a bad one.
- And generally improving my problem-solving skills
Generating codes with AI without understanding these fundamentals would be building a house on a shaky ground, which would eventually collapse.
Enhance my learning with AI Chats:
Once I have mastered the fundamentals, adding AI to my learning toolbox enhances my learning experience. In earlier coding days, one would have to run to platforms like stackoverflow, reddit etc. to find a similar problem and an approach to solving it. Or be extremely good at googling and asking questions in general. These skills are still very relevant. But AI just makes things easier.
An AI chat is that senior dev just a prompt away. It responds really fast, saves time and improves learning.
What I wouldn’t do in this phase though:
Copying AI responses directly into my code without understanding them.
Best way to approach this:
- Ask AI to explain every line of code and why: This will help me understand why every code decision is made.
- Type the codes out myself into my project: This will get me familiar with the code and help solidify my learning.
Use AI to automate concepts I already understand:
The goal of AI is to speed up my workflow right? Recently I explored using AI Agent directly in my code (using Github copilot), to automate my tailwind design and style tokens. The AI did a great job importing tailwind and google fonts. Created the root variables. But did not get the variables in the @theme directory right.
I knew it wasn’t correct and could fix the errors myself because this is a process I’ve had to code manually for several times.
During this project:
- I learnt to feed context to the agent.
- I learnt to review before accepting the code generated by the agent.
- I learnt to fix the bad codes myself.
This experience even though I had to go back and forth with my prompt, gave me the confidence to want to explore Agents further.
Explore Context-Driven Prompting With AI Agents:
This is the area I wish to explore next. In my previous project, I had to give the agent access to specific files (like index.css) for context, alongside a series of prompts. But typing too many prompts into the agent at once can overwhelm it.
In context driven prompt, I will have to create a dedicated file (.md), where I write my project constraint and standards for the Agent to follow. This would provide a persistent, and structured way to configure the agent compared to just prompting into the chat. And it will be easy to track with Git.
A context file can be a universal markdown file like AGENTS.md or an agent-specific file like CLAUDE.md.
Explore Spec-Driven Development With AI-Agent
This is the stage where I get to fully delegate my end-to-end tasks to the Agent. Here, I’ll have to write a list of files with full features that are executable to the Agent. It contains the product requirements, business logic, technical requirements, acceptance criteria etc. Basically what the Agent has to build and how to go about building it.
At this level, I think one has to be considered a senior dev because you’ll have to know exactly what technologies, requirements and criteria you’re giving to the agent.
I guess this approach does it for me. Now I have something to follow through for every project I work on, knowing what level I have to work without or with AI progressively.
I hope this helps someone too. And If you’re already comfortably using AI-agents in your workflow, please share what approach works best for you!
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