From 3 Months to 3 Days: How AI Transformed My Development Process

From 3 Months to 3 Days: How AI Transformed My Development Process

We all know by now, AI is a revolution that will defiantly change the game for the tech industry, not only, but for sure will make a huge impact on Software Developers, Testers and DevOps professional fields.

I read this and watched Mark saying in an interview “AI will be doing the work of mid-level engineers this year”?

https://www.forbes.com/sites/quickerbettertech/2025/01/26/business-tech-news-zuckerberg-says-ai-will-replace-mid-level-engineers-soon/

That triggered my curiosity to dig deep, spend the time to learn, research and evaluate if his statement was just to show that Meta is part of the game or this is really a true possibility.

I decided to take the weekend and spend the time to define, plan, build, integrate and deploy a full blown, production ready information system with 3rd party integrations and a MongoDB backend.

I decided to relay only on AI to create all of it (frontend & backend).

Even though I have the skills to build it myself from start to finish, the rule was – AI will do everything, I am not touching a line of code.

These are my thoughts after completing the exercise and demonstrating the system to real potential users.

First, YES, it is possible! Wait, its not over yet.. let me show you how.

I used VSCode and Github co-pilot with 3 AI Models (Gemini 2.0, Claude 3.5 and MS Co-pilot). I evaluated and compared all of their code results and during the exercise made adjustments for when to use each.

The results were astounding! What would typically take me around 3 months, I accomplished in just 3 days.

Main takeaways:

  1. Coding: Seamless experience, At first, not very smooth and results were slightly off but this was mainly me learning how to provide a better prompt. I fine-tuned my prompts and learned exactly how to ask to get the best results and then things started to fly.
  2. Troubleshooting: Any error I received, AI quickly identified and resolved, saving countless hours of debugging and providing additional information in case I want to learn more about the issue
  3. Testing: Automated testing ensured robust and reliable integrations, with minimal manual intervention.
  4. Deployment: All the scripts and instructions on how to deploy, this is were I stopped and did a few things manually.

At this point I would say, it is almost there but REALLY close.

You don’t necessarily need to know everything about the technology you are using to develop what you want, but you need to understand software so that the system will be architected correctly, optimized and will be easy to navigate.

For me this experience has truly showcased the power of AI in accelerating development timelines and enhancing productivity, it allowed me to keep my focus on the “what” and let AI do the rest saving me a LOT of time coding trivial stuff.

There is more to unpack but I tried to provide some basic insights.

I am a better professional now, I learned a lot from this exercise.

Let me know what you think, comment or message if you want us to get more into it.

I would love to learn more,? this is defiantly going to be a field that I will be spending more time on.

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Avi Mualem

Principal infrastructure engineer

1 个月

the way you used to makes you feel it more than what it is.. yes its great to get small POC fast. system with client and backend which will show some tables and store some documents.. now lets see things as they are: assume you are a developer in a software company which exists 5 years and has good reputation and cant tolerate major bugs or severe prod issues.. plus it has large amount of code in its code base. try to implement a feature there with LLM. what you will see is that it helps you to write some function and save you some time which is cool. but thing is it doesnt come close to have the proper domain knowledge, the context of the feature, the company guidelines (yes even if you have a nice RAG solution over the LLM its not enough), the in house deployment pipeline and more. senior developer was never about only writing code. it was 30% writing code and 70 understanding how to model complex, doing design and communicating with product teams. try to work in the same manner you launched the POC, in a real life software company, you will see the difference trust me. what you did has a really little context and constraint. its cool, but there is not a single senior developer that works 10 times faster from using LLMs.

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