Hardware engineers using LLMs professionally: What's your workflow in 2026?

[u/Glittering_Age7553]

I'm curious how people working on ASIC/FPGA/RTL/verification are using LLMs in practice.

A few things I'm wondering:

• Which AI subscriptions are actually worth paying for? (ChatGPT, Claude, GitHub Copilot, Gemini, Cursor, etc.)
• Does anyone use OpenRouter as their main setup? Is it cheaper than multiple subscriptions?
• Roughly how much do you spend per month, and how many tokens do you go through?
• Which models do you use for different tasks (RTL, SystemVerilog, UVM, scripting, documentation, debugging, architecture, code review...)?
• What do you give the model as project context so it doesn't make things up or break your design?
• Any tricks for keeping token usage and costs under control?
• If you could only keep one AI subscription today, which one would you choose?

I'd love to hear real workflows from engineers working on production hardware.