AINewsnow

System 1 vs. System 2 in AI Engineering: Replacing Ambiguous LLM Judges with Calibrated Semantic Sensors (Jev) in Pure Go

In AI-assisted software engineering pipelines, there is a clear boundary between what compilers can verify and what requires semantic understanding. For everything syntactic and structural — formatting ( gofmt ), static analysis ( go vet ), race-condition testing ( go test -race ), and vulnerabilit…

Read the full story at DEV Community — AI ↗

Timeline · 1 report

  1. 2026-11-06 13:01 · DEV Community — AI
    System 1 vs. System 2 in AI Engineering: Replacing Ambiguous LLM Judges with Calibrated Semantic Sensors (Jev) in Pure Go

More stories

  1. How to Cut Claude Opus API Cost With Jev: 4x on Easy Data, 1.8x on Hard — DEV Community — Machine Learning
  2. A Jev that can ask Opus for help gives Opus accuracy at 4x lower cost — Hacker News Front Page
  3. 🚦 Auto-routing Claude models with Jev prompt classification — DEV Community — AI
  4. I tested four decision models against five small LLMs on 6,662 decisions. The strongest model changed by task, and the full harness and raw calls are public. https://pournasserian.com/writing/decision-models-vs-small-llms-2026 — DEV Community — Machine Learning
  5. Jev Creator Diogo Almeida Discusses Decision Models and Benchmark Fatigue on Podcast — Unsupervised Learning (Redpoint)
  6. [AINews] Behind Latent Space: Kill My SaaS, Jev & AI in 2026 | AIEi Shanghai — Latent Space
  7. AutoTrust Labs Releases JEV-27B Decision Model Scoring Options in One Token — AlphaSignal
  8. Election backlash against data centers rattles AI stocks and expansion plans — TechCrunch AI

Get the daily brief of stories like this at 6:30 every morning →