ITDogtics - Blog

Building AI Code Generation Tools from Scratch in Python 3: A Journey from Zero to Everything (Stage Report) After diving deep in our first three parts, this post is a bit different. It's not a typical progress update, but a moment to pause, reflect on the journey so far, and tackle some big questions that have come up – especially about the limits of AI in software development. Where We Left Off: The Roadblocks In our last discussion, we identified some key challenges our AI tool faced: Missing Design Assets: It couldn't create necessary visual elements (like image folders). Backend Blindspots: Setting up databases or connecting to external services was beyond its scope. The User Acceptance Puzzle: What the AI generated often didn't quite match what a user really wanted or expected. Ignoring Runtime Reality: The process couldn't detect if the generated code would actually run without errors. Honestly, finding straightforward ways to solve these purely with ou...

Building AI Code Generation Tools from Scratch in Python 3: A Journey from Zero to Everything (Part 3) Welcome back! If you missed the previous parts, you can find them here: Part 1 : Covered the basic workflow, fundamental code generation, directory creation, file generation, and folder automation. Part 2 : Addressed the limitations of the prompts and Large Language Models (LLMs) used in Part 1. In this installment, we'll focus on the compilation pipeline. Disclaimer: I won't be sharing the complete project code directly. My goal is to encourage discussion and collaboration. For Beginners: Use this as a guide to build your own project and join the conversation. I'm happy to help with any learning challenges. For Experienced Developers: Please share your insights and discuss potential improvements. Recap In Part 1, we established the foundation for the compilation phase. This phase is crucial for identifying syntax errors, warnings, and coding inconsistencies. Our...

Building AI Code Generation Tools from Scratch in Python 3: A Journey from Zero to Everything (Part 2) If you missed Part 1, you can find it here: link . In our previous discussion, we covered the basic workflow, fundamental code generation, directory creation, file generation, and folder automation. Disclaimer: I won't be sharing the complete project code directly. Instead, I want to foster discussion and collaboration. For Beginners: Use this as a guide to build your own project and join the conversation. I'm happy to help with any learning challenges you encounter. For Experienced Developers: Please share your insights and discuss potential improvements. Our journey doesn't end here. In this part, we'll delve into some of the challenges we've faced in previous part. Challenges: Token exhaustion: Large files exceeding token limits. Code skipping: The LLM omitting parts of the implementation. Inconsistent code generation: Function naming inconsistencies acr...

Building AI Code Generation Tools from Scratch in Python 3: A Journey from Zero to Everything (Part 1) Can we create AI code generation tools in Python 3 from the ground up? This is an open-ended question, and I don't claim to have all the answers. I welcome discussion and idea exchange, as I'm always open to learning. This exploration also reveals how I built the ITDOGTICS application for first prototype in just three days. While I believe there are limitations to current AI technology, I'll address those in a future blog post where I'll delve into how AI works and why it has become so prominent. If you're familiar with basic AI concepts, feel free to skip the introduction to  Scope of this Blog Post . This blog post assumes you have a basic understanding of Python 3. If you don't, it might be challenging to follow along. Disclaimer: I won't provide the complete project code, as I encourage discussion and collaboration. For beginners: Use this as a refer...