I approve of this, but in your place I'd wait for hardware to become cheaper when the bubble blows over. I have a i9-10900, and bought an M.2 SSD and 64GB of RAM in july for it, and get useful results with Qwen3-30B-A3B (some 4-bit quant from unsloth running on llama.cpp).
It's much slower than an online service (~5-10 t/s), and lower quality, but it still offers me value for my use cases (many small prototypes and tests).
In the mean time, check out LLM service prices on https://artificialanalysis.ai/ Open source ones are cheap! Lower on the homepage there's a Cost Efficiency section with a Cost vs Intelligence chart.
Perhaps JetBrains should reconsider AppCode, since Xcode only got this crappy recently. Apparently they didn't get the market share they had hoped for.
What projects need manual memory management? Those where the hardware costs are comparable to development/maintenance costs. That is much rarer than people think.
RAM is cheap, and few applications really need bespoke allocation. And it's not just a question of skill; even the most disciplined make mistakes. It's one of how much brainpower you want to allocate to... memory allocation.
That is when you realize "free market" means "our buddies at the top can charge whatever they want, and you may not compete". Same with healthcare, telecom, financial services...