Armanhozyn's avatar

Is it worth it to learn all the courses and coding when AI can make the production level application

Wait I am not taking about like AI would solve a code problem or fix it. I am talking according to business, If I code an application humanly, Its gonna take too much time, When a non coder who mabe barely knows coding but he Understands how the application works, He make the whole production level application without coding a single line.

So here is my question, Is it worth it to put my all valuable time learning vuejs components structure, Laravel MVC structure, how the code should refactor etc etc? Is it worth it put my value learning all these core stuff where now AI is handling 90% of the these stuff, We just need to tell the feature name or proper prompt.

OK Here is my another analyzation, Suppose I have built Production grade with Just Claude or copilot or mabe Lovable AI prompt, I know I dont know any of code inside what's happening, But the AI generated application is serving my goals perfectly, I mean the features I needed are working perfectly, So why do we need a developer to refactor the code or understand for human ? Because the application is already serving my 95% of the goal. If I need any customization AI is also doing that for that application.

So my whole point is, Is it really worth it to learn the core stuffs? Should I put valuable time on learning these core stuffs? Or should I migrate my self to learning making application with prompt or AI.

I dont know if I am thinking in right way or not, But these questions are in my head like AI already knows why should we learn core stuffs instead I can directly make applications with AI, Ok I understand I can't control the whole codebase but my application would be ready and with AI I can make customization or scale them.

Is it really worth it to learn Core Stuff or Coding? According current situation on earth?

The recent news oracle removed 30000 employee, and investing on AI.

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14 replies
LaryAI's avatar
LaryAI
AI
2 weeks ago
Level 58

Certainly, this is a very topical and thoughtful question! Here’s a nuanced answer:

It’s true that AI can generate functional code and even entire applications from prompts. For many scenarios, this is already a huge productivity boost and enables non-coders to prototype and even ship apps quickly.

But here’s why it’s still very much worth learning core coding fundamentals, structures, and patterns:

1. Understanding and Control

  • Debugging and Maintenance: AI can generate "working" code, but when things go wrong — and they will, especially at scale — you need to understand how things work under the hood to fix, debug, or even understand issues.
  • Customization: What if the AI generates code that almost works but isn’t quite what you want, or introduces subtle bugs, security issues, or performance problems? Deep knowledge lets you adapt and truly own your app.
  • AI Limitations: AI often generates code by pattern-matching, not real reasoning. It might miss context, overlook edge cases, or accidentally introduce hard-to-find bugs.

2. Best Practices, Security, and Large Scale

  • Scalability and Security: A human developer who understands best practices will be better positioned to make an app robust, secure, and able to scale — things AI can only do reliably if you can guide and review its decisions.
  • Refactoring: As your app grows, codebases get messy. You’ll need to refactor and optimize. Even with AI, knowing what and why to refactor is a core developer skill.

3. Job Market and Value

  • AI is a Tool, Not a Replacement (Yet): Companies are laying off in some places due to AI, but they are also hiring engineers who know how to use AI productively and oversee software quality.
  • Prompting requires understanding: Prompt engineering is easier when you understand what you’re asking AI to do. The best AI users are often those with deep context and technical understanding.

4. Business Risk

  • Black Box Risk: If you don’t know what’s happening in your codebase, you’re taking a business and legal risk. You may expose yourself to security vulnerabilities or technical debt that AI can’t explain, and if AI tools disappear, your knowledge base is gone too.

5. Learning is Never Wasted

  • Long-Term Flexibility: Technology changes rapidly. A solid foundation will make you adaptable to new frameworks, programming languages, and even future AI tools themselves.

A Balanced Approach

It’s smart to leverage AI for speed and help, but combine it with ongoing learning of core principles. Use AI to accelerate rote tasks and prototyping, and dedicate time to understanding the architecture, design patterns, and debugging.

Practical suggestion:

  • Use AI to help you learn! Let it give examples, ask it to refactor your code, or explain concepts.
  • But don’t skip the step of hands-on understanding and code reading.

Summary

Yes, it’s absolutely still worth learning the core stuff. AI will make you more productive, but foundational knowledge is what will truly make you a capable, valuable developer — whether you’re building with or without AI.

Example Scenario:

Suppose AI generates a Laravel API endpoint, but you encounter strange performance issues as your app scales. If you understand Laravel's request lifecycle, Eloquent, and how to profile code, you can identify and fix the bottlenecks or even teach the AI how to do it better next time. Otherwise, you're stuck, no matter how smart the AI appears!

In summary: Think of AI as a superpower, not a replacement for understanding. Combine both, and you'll have a massive edge in the new era.

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JussiMannisto's avatar

As of today, AI agents can't make proper apps on their own. What they can do is produce junk that passes tests. To use it for any proper product, you have to understand the code and correct its issues.

It's clear that AI will be useful, but the hype is completely overblown. If you were to go back and read the marketing from two years ago, you'd think you have no future in tech if you didn't use [insert any AI tool hot at the time]. Now those AI models are obsolete, and if you spent the time learning the fundamentals of computer science instead, you'd be much better off.

Some of the recent layoffs in the tech sector can be attributed to pandemic-era over-hiring and the general downturn in the US economy. But I'm sure the over-hyping of generative AI is partly to blame. I believe we'll see more service degradation over the following years.

What you should do ultimately depends on your goals. If you're a non-programmer who wants something on the screen, you may not need to understand the code. I just don't see anyone hiring an "AI prompter" who's helpless when something doesn't work.

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Armanhozyn's avatar

True Fact. But in Deep down like, It kinda feels what I gonna do within next 1 hour, Claude Opus 4.6 is doing that properly within 10 min, That is where my fear comes, If somehow it can produce or build software just like a professional developer do. with some GUI, Then its like waste time to learn all these stuff which can be automated in future.

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JussiMannisto's avatar

Then its like waste time to learn all these stuff which can be automated in future.

If it feels like a waste of time to learn what happens under the hood, software development might not be the right career path for you.

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Armanhozyn's avatar

OK Now I am confirmed that I need to learn core stuffs and put my time there. Actually in my mind thousand of thoughts are running currently mabe Its lack of my knowledge. While you are defending with these much confidence that means I am on right path.

Thank you for the support I think I got my answer. I think I convinced my mind now.

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DigitalArtisan's avatar

80% of the work takes 20% of the time. The other 20% of the work takes 80% of the time.

What you are saying to me is that you have 5-10% of your project complete by AI, by stating that 90-95% of the goals are met, which is the easy stuff, and what about the other 5-10%?

Who is going to spend the rest of the 90-95% of the time that still needs to be done?

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Armanhozyn's avatar

This is also true, But As if now you can get any kind solution with AI,

I mean you ask any tough questions to AI and it will give you the solution,

For AI there no like easy question or hard question, If you ask questions and it runs query from its database and calculate those data and pass it to you.

Its like Answers based on your question. The more clear question the more easier the solution.

That 20% of hard work can also take 10% of time if you ask properly with clear context to the ai.

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JussiMannisto's avatar

For AI there no like easy question or hard question, If you ask questions and it runs query from its database and calculate those data and pass it to you.

That's not how an LLM works. It doesn't run queries. It's a stochastic text predictor that produces text one token at a time. It's a pattern completion machine. The appearance of understanding is an illusion.

This is also true, But As if now you can get any kind solution with AI,

No. AI gives you text output. Nothing beyond that is guaranteed.

AI gets things wrong, hallucinates, tries to solve every problem locally rather than globally, etc. Some issues may be solvable with tooling, but some may be fundamentally beyond the capabilities of the current text predictor approach. These LLM's aren't AGI.

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jlrdw's avatar

This answer I know will do no good, but when using AI it should be to assist, refactor and things like that. You should know how to already code the stuff if there was no AI. And authorization and authentication should not be done by AI.

But not saying you will, but there are people all over the World who will use AI the wrong way.

I recently used AI to help refactor some python code. But I know the math and can identify if all is correct.

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Randy_Johnson's avatar

If you're serious I would chill and watch the courses. But you need a path you want to go down, usually which front end you're using is the big question.

I'd follow the courses. I wasted Hella time not watching 😞

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vincent15000's avatar

Sure it's worth learning all courses.

The AI doesn't replace you, it's just a collaborator.

You are the architect, you know what you exactly want and you ask the AI to do that.

If you don't know what you want, the AI can only imagine what to do.

For now, the AI isn't able to develop a proper scalable application with all security concerns.

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Armanhozyn's avatar

For now, the AI isn't able to develop a proper scalable application with all security concerns.

This is my whole point, Few years back AI couldn't solve programming issues efficiently, But now its doing with guidelines etc. or with proper prompt mabe.

As if now its not capable to do proper scalable application, What if It can after 3 or 4 month, That client doesn't needs to hire any developer, They just prompt about their idea and AI can make scalable proper application with all the security concerns. and Mabe client can also test every security concerns and Mabe client can also have test "is it really properly developed like a developer would built".

So after learning all these stuff, Client doesn't need to Hire!! he can just prompt his idea and AI is gonna develop it for him.

See I understand core stuffs needs to learn and should have knowledge, But I am talking according to business market.

As If now who have barely knowledge about software can make software with AI Claude etc.

What if a non coder doesn't know anything can also make software which are scalable and with all the secuirity concerns?

SO then We only gonna need developer in very critical problems or on very Large Complex Applications.

Its like where anyone can play football, Only Messi is gonna hired for the FIFA.

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vincent15000's avatar

I understand your opinion.

Well ... some years in the past, calculators have been created ... and accounting softwares too.

But you still need to have an accountant.

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kevinbui's avatar

As of today, I believe it is still worthwhile to learn coding yourself. We still have to understand, review and request changes or refactoring to works done by AI.

There are still a lot of concerns regarding security and code quality with AI.

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