---
title: "Decision models — AI hype score and trend · Above the Fog"
canonical_url: https://abovethefog.app/topics/decision_models
as_of: 2026-09-27
updated: 2026-09-28T22:02:40Z
---

# Decision models (💡 Concepts)

[Home](https://abovethefog.app/index.md) › [Topics](https://abovethefog.app/topics.md) › Decision models

Decision models is 🧊 Cooling on Above the Fog’s AI hype radar: a hype score of 26 out of 100 on Sep 27, 2026, 19 points lower than 7 days before. Its current hype episode, running since Sep 17, peaked at 58 on Sep 21; the score is now at or below 60% of that peak.

'System One' decision models: instead of generating text, they return typed, calibrated decisions (a category launched by Jev).

First seen on Podcasts (Apple + niche RSS) · Sep 16 — the first monitored source to go above normal for it in the run-up to this hype episode.

Why this stage: still hot but down to 45% of its peak (58 on Sep 21).

- **Stage:** 🧊 Cooling — past its peak, or just left the hype
- **Hype score:** 26 / 100 · −19.7 in 1 day · −19.4 in 7 days
- **In hype since:** not in hype now
- **Peak, 30 days:** 58.3 on Sep 21, 2026
- **Category:** 💡 Concepts
- **Sources above normal:** 2 of 23 scoring it (2 independent families)
- **Stories in 7 days:** 248
- **Share of voice:** 0.5% of the radar’s attention in 7 days

## Where the attention comes from

“Normal” is the median of the source’s previous 14 normal days for this topic. A source is above normal when its value is at least 30% over that level and stands out from its usual day-to-day variation (z ≥ 2); the share is the part of the hype score that source explains. “× normal” is left blank when the normal level is 0.

| Source | Metric | Latest | Normal | × normal | Above normal | Share of score |
|---|---|---:|---:|---:|---|---:|
| Reddit | posts | 10 | 0 | — | yes | 52% |
| HN: front-page time (ClickHouse) | frontpage hours | 15.1 | 0 | — | yes | 46% |
| DEV Community (dev.to) | items | 2 | 0 | — | no | 2.9% |
| Lobste.rs | items | 1 | 0 | — | no | 0% |
| Luma (SF AI events) | events | 1 (Sep 26) | 0 | — | no | 0% |
| Bluesky | trending | 0 (Sep 26) | 0 | — | no | 0% |
| Cerebral Valley (AI events) | events | 0 (Sep 26) | 0 | — | no | 0% |
| Developer forums (Cursor, OpenAI, Hugging Face) | items | 0 | 0 | — | no | 0% |

## Stories behind it

1. [Jev isn't new tech. Its marketing targets people who think AI started with LLMs.](https://www.reddit.com/r/LocalLLaMA/comments/1woe70t/) — Reddit (r/LocalLLaMA) · Sep 23 · score 756 · 280 comments
2. [Ollaya – Ollama for open-source, Jev-style decision models](https://news.ycombinator.com/item?id=49848269) — Hacker News (ollaya.dev) · Sep 25 · score 609 · 145 comments
3. [ollaya-dev/ollaya: Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.](https://github.com/ollaya-dev/ollaya) — GitHub (ollaya-dev) · Sep 23 · score 862
4. [Ollaya – Ollama for open-source, Jev-style decision models](https://news.ycombinator.com/item?id=49848269) — HN: front-page time (ClickHouse) (ollaya.dev) · Sep 25 · score 568 · 137 comments
5. [Your Agent Thinks Too Much 🤖🍗 \| Crazy Thursday @ SF Tech Week](https://luma.com/seamate-tdd8) — Luma (SF AI events) (SEAMATE) · score 81
6. [Jev: System One models for Prod, not God — with Diogo Almeida, CEO, TypeSafe AI](https://www.latent.space/p/jev) — AI newsletters (RSS) (Latent Space) · Sep 21 · score 49 · 5 comments
7. [Jev 101: How I'm Using It Today in My Apps](https://dev.to/erikch/jev-doesnt-write-text-it-returns-probabilities-5gno) — DEV Community (dev.to) (#ai) · Sep 22 · score 30 · 3 comments
8. [Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failures](https://huggingface.co/papers/2609.29429) — Hugging Face Daily Papers (hf-papers) · Sep 25 · score 10 · 2 comments
9. [How to Solve Hallucination \(with RLCD\)](https://lobste.rs/s/kolgwk/how_solve_hallucination_with_rlcd) — Lobste.rs (#vibecoding) · Sep 28 · score 8 · 1 comment
10. [Jev AI: What It Is, How It Works, Use Cases, Benefits, Limitations and Jev vs LLMs Meta Title: Jev AI Explained: What Is Jev, How It Works & Use Cases Meta Description: Learn what Jev AI is, how Type…](https://www.urbanmind.net/display/f7dd981d-7b586284-31ba8c499c1a462f) — Mastodon (fediverse) (www.urbanmind.net) · Sep 24 · score 6 · 0 comments
11. [The Agentic Loop is OUTDATED](https://www.reddit.com/r/ClaudeCode/comments/1wp9nga/) — Reddit (r/ClaudeCode) · Sep 24 · score 353 · 153 comments
12. [Running a Jev-Style Decision Model on One TPU v6e: What Fits, What It Costs, and What Changes From a GPU](https://dev.to/gde/running-a-jev-style-decision-model-on-one-tpu-v6e-what-fits-what-it-costs-and-what-changes-from-1j0g) — DEV Community (dev.to) (#gemma) · Sep 24 · score 9 · 0 comments

## Themes

What its stories of the last 7 days are about: the 253 of them the Jev model kept as about the scene, by theme (a story can carry several themes):

- [Models](https://abovethefog.app/themes/models.md) — 85% of its stories
- [Protocols & infra](https://abovethefog.app/themes/protocols_infra.md) — 18% of its stories
- [Agents](https://abovethefog.app/themes/agents.md) — 16% of its stories
- [Usage & adoption](https://abovethefog.app/themes/usage_adoption.md) — 7.9% of its stories
- [Security & safety](https://abovethefog.app/themes/security_safety.md) — 5.5% of its stories
- [Identity & auth](https://abovethefog.app/themes/identity_auth.md) — 2.4% of its stories

Payment rails its stories name:

- [x402](https://abovethefog.app/themes/x402.md) — 1 story
- [Stablecoins / crypto](https://abovethefog.app/themes/stablecoins_crypto.md) — 1 story

## Related topics

- **Related to:** [TypeSafe AI](https://abovethefog.app/topics/typesafe_ai.md)
- **Mentioned with:** [Qwen](https://abovethefog.app/topics/qwen.md) (38 stories), [Local inference](https://abovethefog.app/topics/local_inference.md) (32 stories), [Open-weight models](https://abovethefog.app/topics/open_weights.md) (19 stories), [LangChain](https://abovethefog.app/topics/langchain.md) (7 stories)

## Hype score, last 30 days

| Day | Hype score | Stage |
|---|---:|---|
| Sep 27, 2026 | 26 | 🧊 Cooling |
| Sep 26, 2026 | 45.7 | 🔥 Hot |
| Sep 25, 2026 | 48.5 | 🔥 Hot |
| Sep 24, 2026 | 42.9 | 🔥 Hot |
| Sep 23, 2026 | 53.2 | 🔥 Hot |
| Sep 22, 2026 | 54.3 | 🚀 Rising |
| Sep 21, 2026 | 58.3 | 🔥 Hot |
| Sep 20, 2026 | 45.4 | 🚀 Rising |
| Sep 19, 2026 | 2 | 💤 Quiet |
| Sep 18, 2026 | 50.9 | 🚀 Rising |
| Sep 17, 2026 | 31.9 | 🚀 Rising |
| Sep 16, 2026 | 23.6 | 💤 Quiet |
| Sep 15, 2026 | 1.1 | 💤 Quiet |
| Sep 14, 2026 | 0 | 💤 Quiet |
| Sep 13, 2026 | 0 | 💤 Quiet |
| Sep 12, 2026 | 0 | 💤 Quiet |
| Sep 11, 2026 | 0 | 💤 Quiet |
| Sep 10, 2026 | 0 | 💤 Quiet |
| Sep 9, 2026 | 0 | 💤 Quiet |
| Sep 8, 2026 | 0 | 💤 Quiet |
| Sep 7, 2026 | 0 | 💤 Quiet |
| Sep 6, 2026 | 0 | 💤 Quiet |
| Sep 5, 2026 | 0 | 💤 Quiet |
| Sep 4, 2026 | 0 | 💤 Quiet |
| Sep 3, 2026 | 0 | 💤 Quiet |
| Sep 2, 2026 | 0 | 💤 Quiet |
| Sep 1, 2026 | 0 | 💤 Quiet |
| Aug 31, 2026 | 0 | 💤 Quiet |
| Aug 30, 2026 | 0 | 💤 Quiet |
| Aug 29, 2026 | 0 | 💤 Quiet |

[Open Decision models in the interactive map →](https://abovethefog.app/#topic=decision_models)

---

Updated Sep 28, 2026, 22:02 UTC · Data: Above the Fog hype radar

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