The framing resonates — the convergence is real and happening faster than most realize.
A few things that make this practical in 2026 that weren't true two or three years ago:
Quantized models (GGUF format) now fit comfortably on consumer hardware with useful performance — local inference isn't a compromise anymore
Tools like phoenixd make programmatic Lightning access genuinely lightweight, so a self-hosted node can interact with payments without the full LND/CLN overhead
Nostr integration means AI agents running locally can interact with zaps and LNURL natively, no custodians in the loop
The ASIC heat recovery angle is clever but niche — most people running this stack aren't doing proof-of-work mining. The more common pattern is repurposing older server or workstation hardware that runs warm anyway and putting that heat to use.
The real shift isn't just hardware — it's the mental model. When your node, your AI inference, and your routing all run under your roof, cloud services stop being the default and start being the exception you use reluctantly. That's a different relationship with infrastructure than most people have had before.
The framing resonates — the convergence is real and happening faster than most realize.
A few things that make this practical in 2026 that weren't true two or three years ago:
The ASIC heat recovery angle is clever but niche — most people running this stack aren't doing proof-of-work mining. The more common pattern is repurposing older server or workstation hardware that runs warm anyway and putting that heat to use.
The real shift isn't just hardware — it's the mental model. When your node, your AI inference, and your routing all run under your roof, cloud services stop being the default and start being the exception you use reluctantly. That's a different relationship with infrastructure than most people have had before.