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Builds: data, content, business, games and devices

[ community tier ][ updated 2026-09-23 ][ confidence medium ][ jev-1.13.0 ]#ideas · builds · community · data · games

TL;DR What people shipped with Jev outside agent loops, one row per build: what Jev decides, reported numbers, pattern ID, link. Every number is one builder's own run; re-measure on your data (Testing and evaluating a Jev workflow). Agent and browser builds: Builds: agents, coding tools, browser and interface. Price checks use $0.042/Mtok input, output free (verified, Models, aliases, pricing, rate limits, context).

Build (builder) Jev decides Reported numbers Pattern Source
likethisgame.com recs (Mehmet Aras) Noul per candidate "would a fan of X like Y?", 20 candidates per request; top 30 of 600 go to an LLM that writes the recs; code down-weights popular games Batched vs one-by-one rankings Spearman 0.884; 600 candidates = 30 requests, ~2 s, $0.007; 243 pages $2.02 total, $1.59 of it Jev. Filtering after generation failed (strict cut removed 150 of 216 recs); ranking before won blind comparisons 11-9 (10 ties). Jev's effect not yet separated from better candidates (author). Via OpenRouter's decisions endpoint (unverified, not in TypeSafe docs) Patterns: judging, search, documents, real-time and markets P17 dev.to
jevsearch (@kylemclaren) Reranks React site-search results none in the capture Patterns: judging, search, documents, real-time and markets P17 post
tocsin (Ateeq) Log lines masked and templated in code; one request per new template: pageable, detail Nouls, severity Score 0-3, area Choice, against a plain-English paging policy. Code: attention = pageable × (1 − detail), verdicts cached 22.8M lines → 11,812 templates → 13,080 calls, $0.64, 6 m 23 s (every line would be $1,120); p50 ~370 ms. BGL (tuned on) F1 0.860; Thunderbird held out F1 0.000: its dominant alert pattern scored 0.65 and went to ticket. Offline keyword fallback Patterns: judging, search, documents, real-time and markets P18 repo
HN categoriser (@sabrinaesaquino) 24,000 Hacker News posts into 12 categories "about 2 minutes"; via the Venice API beta (gateway unverified) Patterns: judging, search, documents, real-time and markets P18 post
Image sorter (@fayazara) OCR text first, then Jev picks a category ~900 images in 40 s Patterns: judging, search, documents, real-time and markets P18 post
Nitpicky (@richard_meng_01, roe-ai) AI-image detector judging faces, fingers, text, poses region by region none. Jev is text-only (verified), so a vision step must describe regions first; how is not stated Patterns: judging, search, documents, real-time and markets P16 post
jev-reviewer (Ahmad Sofi-Mahmudi) Systematic-review extraction: pass 1 Choice "which line answers q?" (+ none) per 2-3 pages; pass 2 Noul per candidate line, keep ≥ 0.5; code copies the verbatim quote. "Not found" is an answer 712-line sample study: 18-question template, 27 requests, 4.6 s, $0.0101; 12,000-char chunks = same answers as 7,000 with a third fewer requests. Author: spot checks, not validation Patterns: judging, search, documents, real-time and markets P26 repo
Proq plan sets (@hari_trinay) Sheet type per construction-plan sheet 26 sheets in 2.9 s for $0.0052; matched GPT-4.1 and GPT-6 Astra on 100% of sheets; "17–21x cheaper and 5x faster" than their pipeline Patterns: judging, search, documents, real-time and markets P26 post
Langfuse trace judge (Annabell Schäfer, Langfuse) One request per agent run: needs_review Noul, severity Score, failure_mode Choice; score written back to the trace. Now a built-in Langfuse evaluator Cites Good Start Labs: 6,003 rubric checks, 91.5% agreement with Fable 5.1 at $160 per million graded answers vs $33,000. Noul has no confidence (verified, Noul (yes/no) questions); warns Jev cannot abstain, so add an escape option Patterns: judging, search, documents, real-time and markets P15 blog

Content and marketing

Build (builder) Jev decides Reported numbers Pattern Source
Every writing checks (Mike Taylor; Dan Shipper) 21 yes/no AI-tell questions per article (Noul, inferred); 11 experiments (context finding, reply grading, triage) 37 docs × 21 = 777 judgments in < 0.7 s, ~¼ cent; 1,709 judgments < 1 cent. Shipper: 4 checks × 12 passages, Jev 0.35 s median vs 8.83 s Fable 5.1, ~580x cheaper, caught 6 of 7 planted defects (Fable 7 of 7). Idea: a linter an agent runs after each paragraph Patterns: marketing, sales, GTM, content, support and ops P30 Every, @danshipper
Slop detectors (@kraayenJon; @jozef_gherman) One question per AI-slop tell on a page or text (type not stated) Kraayenbrink: 35 tells, 243 ms, $0.00015. Gherman: ~10,000 words in ~2 s Patterns: marketing, sales, GTM, content, support and ops P30 kraayenJon, jevdetector
SuperX post scorer (@robj3d3) 61 questions per draft; loop: draft, score, revise until the score stops rising ~1 s, $0.0004 per post; fitted on 9,481 posts from 207 creators; picks the viral post "2 in 3 times" (no baseline stated) Patterns: marketing, sales, GTM, content, support and ops P21 post
maxfusion ad teardown (Ori Silver, via @aresotik) Funnel stage and creative style per ad in a brand's ad library 1,891 ads in 19 s for $0.12 Patterns: marketing, sales, GTM, content, support and ops P21 post

Business ops

Build (builder) Jev decides Reported numbers Pattern Source
Fraud email cascade (Hassan, @nutlope) Fraud vs legit; confidence < 0.95 escalates to Kimi K3 100 emails in 1.42 s; 31 escalated; pipeline 96/100 in 16 s for ~$0.07, of which Jev $0.003 Patterns: agent internals, context and coding agents P06, Confidence-gated routing post
Spliit Cloud expenses (Antonio Ivanovski) Expense category from title: local dictionary, then group history, then one engine (LLM or Jev Choice); below AI_CATEGORY_MIN_CONFIDENCE (0.5) no suggestion; uncertain guesses shown as one-tap chips none. README: pin jev-1.13.0 once thresholds are tuned, jev-latest moves (verified, Models, aliases, pricing, rate limits, context); LLM self-reported and Jev confidence are not on one scale, recalibrate when switching Patterns: agent internals, context and coding agents P06, Patterns: browser, computer use, voice and product UI P34 repo
Regex rules → Jev (Ilias Ism, @illyism) Hard-coded rules (vibe-coded regex) replaced in aiseotracker, linkdr, genppt "around 10x faster, 50% cheaper" than regular LLM calls (no method) Patterns: agent internals, context and coding agents P01 post
Backdoor job match (@sarvagya_kul) Fit probability of one candidate for 400 companies; flags mismatches 12 s, $0.0005. At list price that is ~12k input tokens, ~30 per company: only fits very short profiles; treat as approximate Patterns: marketing, sales, GTM, content, support and ops P19 post
Gojiberry outreach mining (@pierreeliottlal) Labels thousands of outreach messages by intent signal; which signals booked demos (the tally is code, inferred) 40 s, < $0.20 Patterns: judging, search, documents, real-time and markets P18, Patterns: marketing, sales, GTM, content, support and ops P20 post

Games, simulation and devices

Build (builder) Jev decides Reported numbers Pattern Source
Dual-arm robot (@Raptor_zip) Middle layer of three: the decision; IK and physics in code ~500 ms per answer, ~0.5 yen per trial Patterns: judging, search, documents, real-time and markets P24 post
RoboJEV (lyk) Franka arm in MuJoCo, structured state not images: Choice of intent, then per-axis negative/zero/positive and gripper open/hold/close; malformed answers execute nothing 100 episodes, 10 seeds each, Jev vs rule baseline: pick-place, push, peg 10/10 both; stack 8/10 vs 10/10; gate obstacle 5/10 vs 8/10. Failures: repeated wrong-direction moves exhausting the budget, one inconsistent answer Patterns: judging, search, documents, real-time and markets P24 repo
JevScape (Skyvern-AI) RuneScape via ~50 coded actions: next_action, a this_tick fix-up, and when to poll next Mean peak XP/min: random 235, Jev 197, Claude Opus 118; Jev total XP 2.1x random; 1,307 decisions, $0.17. Live: 13,402 polls, $2.22, median 0.22 s, ~$0.55/h. Authors: "The catalog carries the game knowledge" Patterns: judging, search, documents, real-time and markets P24 repo

Markets (engineering only, not financial advice)

Build (builder) Jev decides Reported numbers Pattern Source
fedjev-bench (maybern-tripp-smith) Pairwise Choice "more hawkish about inflation" over FOMC press-conference openings, checked against rate actions and FedLock scores Main run ≈ $0.031; gates 1, 3, 4, 6 pass, 2/5/7 reported; 7-criterion extension $1.5329. Text ranking, not a trade signal; buy/sell (Patterns: judging, search, documents, real-time and markets P25) stays poor Patterns: judging, search, documents, real-time and markets P17 repo

Audits to rerun before you build

Audit (author) Finding that changes a design Pattern
jev-evaluation (Will Kelly; 123,805 requests, $12.69) 60 questions on one state: 20x fewer tokens, 8x sooner, identical answers. 60 tickets in one state: 1.000 when each question names its ticket, 0.420 with "Ticket 1". Source text 0.894 vs pre-digested edge list 0.530. A polite "lead already decided" line flipped 147/200 tickets (crude injection 1/200). A 0.8 gate catches 95.5% of missing-fact states, none of fluent nonsense Patterns: judging, search, documents, real-time and markets P15
jev-orderby-bench (yodablocks) Passes on 360 rows (inversion 0.036); fails 4 of 6 gates on hard shopping relevance. 40-row batches fail the ranking gate (0.171) that one row per request passes. Two-decimal probabilities: 53 rows tie at 0.99, so LIMIT 20 is partly arbitrary Patterns: judging, search, documents, real-time and markets P17
jev-acento (Marcos Martinez; 19,200 calls, $0.58) Spanish state costs 3.0-6.4 pp accuracy and doubles ECE on XNLI; Spanish instructions do not help, keep them in English; 17-38% more tokens. Direction matches docs (English primary, verified) Patterns: judging, search, documents, real-time and markets P18
jev-capability-atlas (Zaious) A typo in the correct option drew 0.90 confidence on a wrong answer; strong when the signal is in state, weak when outside knowledge is needed Patterns: judging, search, documents, real-time and markets P16

Conflict: Kelly finds batching safe when questions name their subject; the ORDER BY bench finds 40-row batches break ranking. For ranking products, send one item per request or test both (yodablocks' own jobbyjev does one company per request).

What these builds teach when advising

Sources