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Replacing my OS process scheduler with an LLM

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HN · launched Dec 30, 2025 · 77 upvotes (top 14%) · 0 views

Niche: experimental and embedded operating systems · 142 launches, 6 in the last 7 days ▼ -60% · Explore this niche →

Category and tags

  • Horizontal
  • Dev tools
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Partial Writing a toy user-space scheduler or eBPF/sched_ext experiment that calls an LLM can be assisted by AI, but integrating with kernel scheduling interfaces requires deep systems knowledge.

What it would actually take: A real implementation uses Linux 6.12+ sched_ext (extensible BPF scheduler) to intercept task dispatching in the kernel. The BPF hook communicates through shared ring buffers to a user-space daemon that batches process metadata, prompts an LLM via local inference runtime (like llama.cpp), and writes back scheduling decisions with strict real-time deadline fallbacks.

Discussion

20 comments analyzed.

Competitors mentioned: Task Manager (Windows), macOS Shortcuts app with LLM integration, Framework Desktop systems, Mac Studio

Concerns raised: Replacement of OS scheduler with LLM would be painfully slow, Deterministic systems have more value than autonomous LLM loops in OS-level functions, LSP servers consuming excessive RAM (2GB+) makes some tools unusable, Utility of LLMs questionable versus simpler solutions like Kindle with Wikipedia in resource-constrained scenarios

Feature requests: Roulette mode to randomly kill processes, Focus Mode that kills processes like Steam or Civilization VI on launch, Strict productivity coach mode with roasting capabilities, Process Defense Attorney agent to log process arguments, LLM-powered Clippy-like character that screenshots and comments on user behavior

Competitors

Other products that read as similar to this one : 484 launches clear the similarity bar, closest 8 shown.

Attention rank: #45 of 485 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 61 days after the earliest competitor.

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