From e6beb61e623742f57970596724bb55cebd175327 Mon Sep 17 00:00:00 2001 From: Experimenting With Computers <1908752+makefunstuff@users.noreply.github.com> Date: Sun, 20 Sep 2026 19:01:17 +0300 Subject: [PATCH] Clarify demo, classifier, and cost section copy --- site/index.html | 42 ++++++++++++++++++++++-------------------- 1 file changed, 22 insertions(+), 20 deletions(-) diff --git a/site/index.html b/site/index.html index bf6b643..e0e3b0c 100644 --- a/site/index.html +++ b/site/index.html @@ -103,16 +103,17 @@

Steer code with rules, not with token maxxing.

Demo

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Finding and fixing AI-slop commentary

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Silent action loop across OpenCode, Neovim, and VS Code: paste an AI-slop comment, get a finding, apply the fix.

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Same no-ai-slop hit in three clients

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OpenCode writes a matching comment and gets the diagnostic. Neovim shows it as virtual text. VS Code clears it with a code action. Silent, ~32s.

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OpenCode → Neovim → VS Code · ~32s · no voiceover
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OpenCode → Neovim → VS Code · ordinary LSP diagnostic
@@ -169,28 +170,29 @@

Findings on the line: same surfaces your client already has

Model shape

Classifier, not chat

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Chat reviews emit prose about the whole file. Jev answers one rule question about one candidate line: a typed value and a confidence p.

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prose · whole file · every turn

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chat review · reject

Here are several thoughts about this file… consider error handling on line 412, also naming, also whether the module boundary is right, also…

- Jev rule answer - typed · one line + Jev decide + one line · one rule
{
   "value": "fail",
   "p": 0.91
 }
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typed value · one line · clears rule floor
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publish only if p ≥ floor (e.g. 0.8)
@@ -231,8 +233,8 @@

The loop

Economics

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Why local / cheap models work here

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Rules carry conventions; the model answers about one candidate line. No matching pattern → no model call.

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One line costs less than a whole-file chat

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Patterns decide which lines run the model. No match → no call. A match asks about that line only, so a small/local decide model is enough.

@@ -246,27 +248,27 @@

Why local / cheap models work here

- rules pass - chat review (same file) + jev rules pass + whole-file chat review server.rs ~2.6k lines - ~5.3k in / 345 out · 2 findings · ~$0.00022 - ~30.5k in / 9 out · 0 findings · ~$0.00306 + 2 findings · ~$0.00022
~5.3k in / 345 out + 0 findings · ~$0.00306
~30.5k in / 9 out 30 Rust docs - ~$0.0034 · 20 calls + ~$0.0034 · 20 decide calls —
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decide jev-1.13 vs chat review gemini-2.5-flash-lite. PoC: accuracy from steering, not token maxxing.

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jev-1.13 decide vs gemini-2.5-flash-lite chat on the same file. Measured in this repo.

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Accuracy from steering, not from burning tokens.

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Cheaper because most lines never call the model.