Jev by @typesafeai is now on OpenRouter, in beta. Jev is a System One model. Instead of generating text, it takes your app's state plus a typed question and returns a typed decision with a probability attached. There is no JSON prompting, parsing layer, and nothing to validate Show more
Core Concepts
AI-powered software
The architecture TypeSafe recommends: code owns the workflow and the model appears only where programmable common sense is needed.
- Category
- Core Concepts
- Also known as
- —
- Related terms
- 4
- Directory entries
- 2
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
The how-to-build guide contrasts three architectures: traditional software, LLM agents that choose their own next step, and AI-powered software where code handles deterministic work and keeps control flow. In the third, each AI task is atomic and constrained.
The summary is blunt: build a normal software workflow and insert System One only where AI is needed. Control flow, rules, and side effects stay in code; the model handles narrow judgments over unstructured input.
Tagsarchitecture
Related terms
Definitions that connect to this one.
Agent loopA control pattern where the model chooses its next step repeatedly; TypeSafe's guidance is to prefer a code-owned workflow instead.Core ConceptsTyped decisionA model output that conforms to a software type your code expects, rather than free-form text that has to be parsed.Core ConceptsMachine-to-machine automationAutomation where software calls AI directly, expected to be roughly 99% of large-scale AI interactions versus 1% human-facing.Core ConceptsDecompositionBreaking a broad judgment into one question per factor, then combining the answers with weights and rules you control in code.Core Concepts
From the directory
Design AI-powered software by keeping code in control and giving System One narrow, structured decisions to make.
Practices & PatternsDocs#official#patterns#architecture
Official
TypeSafe's case for machine-native composable AI: intelligence as a dependable primitive that software branches on, rather than an assistant that keeps humans in the loop.
Sites & GuidesArticle#official#article#architecture
Official
From the community
Posts from builders shipping with Jev right now.
Jev lands on OpenRouter
700 leads scored for $0.09
JEV is INSANE. We gave it 700 high-intent leads and personalised outreach messages. In 40 seconds, it predicted how each message would perform, assigned a confidence score and detected lead-message mismatches. All for just $0.09. JEV can also score leads, analyse buying Show more
Beating Gemini Flash Lite on an eval
Ran @typesafeai's Jev against an existing classifier eval that previously used Gemini 2.5 Flash Lite. It won both on quality (saturated the eval) and speed (6x)
Browser Use Ultrafast, powered by Jev
Breaking: Browser Use + Jev = Ultrafast ⚡ Findings flights took 7s and cost only $0.0039 🤯 > new action space every step > DOM state space > small LLM fallback to type (this video is at 1x speed btw) Built a tiny open source browser agent. try it below ↓
A really smart switch statement
hype-free explanation of jev: jev does not replace gpt / claude jev is just a *really* smart switch statement like if 2016 ml classifiers got 2026 levels of intelligence it's a new* type of tool that will make a lot of workloads insanely fast, cheap, and accurate * = and by Show more
@CompleteSkeptic
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x
When a designer gets Jev
when a designer gets access to Jev