Show HN: A local-first AI agent for the desktop, no Electron, any LLM endpoint
Hey folks. Most all the apps I see for agent harnesses are typescript based, and involve either electron or some form of IPC to function as a desktop app. In the age of LLM's, I thought it would be cool to build out a prototype of what a modern desktop application would like for this, without using any web code, since I can have agents pretty aggressively work on the cross-platform compatibility on my behalf. After about a week, I ended up with a harness that feels pretty good! Feel free to try
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points · 2 votes
2026-11-15 16:37:15.509Z
cumulative since publication
Research analysis
Project record
Repository: Scronkfinkle/byob. Source account: Hey folks. Most all the apps I see for agent harnesses are typescript based, and involve either electron or some form of IPC to function as a desktop app. In the age of LLM's, I thought it would be cool to build out a prototype of what a modern desktop application would like for this, without using any web code, since I can have agents pretty aggressively work on the cross-platform compatibility on my behalf. After about a week, I ended up with a harness that feels pretty good! Feel free to try
Observed adoption & comparisons
Source votes: 2 votes (Nov 15, 2026 UTC; cumulative since publication) Recent records to compare: “Show HN: profiler-md converts performance profiles to Markdown” (Hacker News, Nov 15, 2026); “Show HN: db-branch – database branches in seconds for AI agents and CI, via ZFS” (Hacker News, Nov 15, 2026). Shared themes are navigation hints; they have not been verified as the same need or independent corroboration.
Adoption decision
Evaluate it against the tool or manual workflow it would replace. The stored record supports discovery; it does not yet establish reliability, lower operating cost or commercial adoption.
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Next test
Choose one real task and a current alternative. Record the commit, environment, input, output, elapsed time and failure behavior; retain the result before recommending adoption.