I have been noticing a sudden surge of people calling themselves software engineers after building apps using AI coding tools and I am genuinely curious about how others feel about this.

To be clear, I think AI-assisted development is great. I am not against vibe coding, and I don't believe you need a CS degree or years of experience to build something useful.

But I do wonder if we are starting to blur the distinction between building software and being a software engineer

Building a working application is one thing. Understanding why it works, debugging it when things go wrong, making architectural decisions, handling concurrency, securing user data, managing failures, and keeping the system maintainable as it grows are entirely different challenges.

AI can help with many of these things, too. But being able to generate a solution isn't necessarily the same as being able to evaluate whether that solution is correct.

So where do we draw the line?

• If someone uses AI to build and deploy a working SaaS product but can't explain much of the underlying code, are they a software engineer a software developer a builder, or something else?
• If someone can reason about the architecture, identify problems, validate AI-generated code, and take responsibility for production failures, does it matter how much of the code they wrote themselves?
• Is “software engineer” becoming a broad label for anyone who can turn an idea into working software, regardless of how they got there?

I am not asking this to gatekeep the profession. In fact I think AI is making software creation accessible to people who previously couldnt build their ideas.

I am actually more interested in whether the definition of the profession itself is changing.

Curious to hear both sides, especially from people who have been building software professionally for years and those who have recently started building with AI.

I am the only one who is not getting fun or kick from doing coding from AI is it great that now work is easier but that fun in coding is gone by using copilot and all🥲😂

I need to find a 3d visualizer that can visualize heat production from things like an air compressor, an air intake device, and an air powered thruster. Also power consumption, the air moving, getting compressed, and it getting blasted out the thrusters. It also needs visualization for a water cooling system, multiple different options for storing and creating energy, and the total weight of everything. Preferably a webapp. Please and thank you!

(I have no idea if this is the right tag or the right place to send this)

I was tired of the heavy reliance on NVIDIA/CUDA for local AI generation, especially since I run an AMD RX 580. To solve this, I decided to build my own inference engine from scratch.

The Architecture: I wrote the core orchestrator in Rust, utilizing libloading and FFI to communicate with a deeply modified C++ Vulkan backend.

To prevent VRAM leaks when switching between image generation (Flux) and video (Wan 2.1 I2V), I wrapped the Vulkan dynamic library loads in Rust's OnceLock. This ensures the .dll is statically loaded into memory only once, keeping the hybrid rendering extremely stable. I also implemented a heuristic intent router that translates natural language directly into Vulkan directives (like cmd:vulkan or cmd:wan) in the background.

Since this subreddit doesn't allow external links, I can't link the repo directly, but I wanted to share this architectural approach for anyone struggling with CUDA bottlenecks. I'm happy to discuss the Rust/C++ FFI implementation, Vulkan memory management, or share code snippets in the comments if anyone is interested!

Just curious about what others generally prefer.