00Jev wiki

Jev Wiki — Master Index

TL;DR 81 content pages (plus this index and the log) about Jev, TypeSafe AI's System One model. Snapshot of upstream sources: 2026-09-17. Model: jev-1.13.0; typesafe-sdk 0.6.0; @typesafe-ai/sdk 0.6.0. New here? Read Playbook for LLM agents building with Jev first, then HTTP API: POST /v1/systemone and GET /v1/models or the SDK reference, then Jev 1.13 jaggedness: known failure modes.

This file is generated from page frontmatter by node scripts/build.mjs; edit the pages, not this list. Maintenance log: Activity log.

Guides (6)

Page	Summary	~Tokens	Updated	Conf.
Playbook for LLM agents building with Jev	Seven-step playbook for an agent told 'use Jev for X': decide, decompose, shape state, write questions, call, consume, handle errors, test.	7.0k	2026-09-20	high
Choosing between Choice, Score, Noul	Decision table mapping question shape to Choice, Score or Noul, the anti-patterns for each, and how to decompose a complex judgment into several primitives.	3.4k	2026-09-17	high
Quickstart: first call in HTTP, Python, JS	Get a key at console.typesafe.ai, export TYPESAFE_API_KEY, and make your first POST /v1/systemone call in curl, Python, or TypeScript.	3.6k	2026-09-17	high
Smart home assistant demo walkthrough	TypeSafe's smart home demo: one speculative fan-out per utterance routes device commands, while an LLM handles compound splitting and conversational fallback.	2.3k	2026-09-17	medium
Testing and evaluating a Jev workflow	Measure accuracy, calibration, repeatability, latency and cost on your own labelled set; pick thresholds from confidence buckets; regression-test jaggedness.	3.9k	2026-09-20	high
Writing instructions and criteria that Jev reads correctly	How to phrase instructions and criteria for each question type, with before/after rewrites for literal reading, negation, numbers and dates, plus an edge-case testing loop.	4.6k	2026-09-17	high

Ideas (community) (5)

Page	Summary	~Tokens	Updated	Conf.
Community repos: what people built and how they use Jev	42 third-party repos from Jev launch week, grouped by domain, each with the state it sends, the question types it asks, and the official page it maps to.	4.5k	2026-09-20	medium
Consult guide: could Jev help this project?	Procedure for an agent asked 'here is my project, could Jev help?': what to read (10-15k tokens), how to find and filter decisions, and the shortlist format to return.	1.9k	2026-09-20	medium
Field reports: independent evaluations, critiques, open replicas	What independent testers measured in Jev's first week: strong repeatability and cost on bounded classification, weak standalone browser/spatial control, and a wave of open replicas.	3.5k	2026-09-20	medium
Ideas section overview	One-screen map of the community-tier ideas section: which of its four pages to open for which question, and how far to trust them.	0.5k	2026-09-20	medium
Decision patterns from the community (with fit verdicts)	25 decision patterns people published for Jev in its first week, each with a state/ask/code shape, a strong/workable/poor fit verdict, and links to the official pages.	5.2k	2026-09-20	medium

Concepts (13)

Page	Summary	~Tokens	Updated	Conf.
Structured instructions, options, levels, criteria	instructions, Choice option descriptions, Score levels and Noul true/false all accept JSON: string, object, array or null (EntryType).	3.4k	2026-09-17	high
Choice questions	Choice picks one option from a fixed set: send type/instructions/criteria, get back choice, probabilities over every option, and confidence.	4.6k	2026-09-17	high
Confidence vs probability	confidence is a 0-1 statistic derived from an answer's probabilities distribution; Choice and Score carry it, Noul does not.	2.3k	2026-09-17	high
How to build software with System One	Build a normal software workflow and insert System One only where AI is needed: narrow typed questions, composed in code.	6.3k	2026-09-17	high
Jev 1.13 jaggedness: known failure modes	Nine documented failure modes of jev-1.13 — literal reading, math, dates, indirection, big states, adversarial text, contradictions, invariants, generation — with the mitigation for each.	3.3k	2026-09-17	high
AI primer: why calibrated decision models	Why TypeSafe post-trains with RLCD for calibrated decisions instead of RLHF/RLVR for generated text.	1.7k	2026-09-17	high
Noul (yes/no) questions	Noul asks one yes/no question and returns a single number, the probability that the answer is yes; criteria are optional true/false clarifications.	2.3k	2026-09-17	high
Primitives: Choice, Score, Noul	The three Jev question types (Choice, Score, Noul), the typed answers they return, how to pick one, and how to batch many questions in one request.	3.0k	2026-09-17	high
Score questions	Score rates a state against an ordered array of described levels and returns a probability-weighted position, the legend, per-level probabilities, and confidence.	5.1k	2026-09-17	high
State: what you send Jev	State is the content Jev evaluates: a string, JSON object, or array of text, shared by every question in one request.	1.7k	2026-09-17	high
System One Models	System One models make fast, typed, calibrated decisions software can consume directly; Jev is TypeSafe's first one.	2.8k	2026-09-17	high
Use-case map by industry	Scannable map of where Jev fits: five capability categories, eighteen industry/function areas, and ten decision shapes.	3.1k	2026-09-20	high
Workflow evals: how TypeSafe measures Jev	TypeSafe's four workflow evals: same harness for every model, reference labels from GPT-6 Astra + Claude Fable 5.1, source of 193.6x/444.6x.	4.0k	2026-09-17	high

Reference (18)

Page	Summary	~Tokens	Updated	Conf.
The typesafe-ai agent skill and Claude Code plugin	Install, update, and invoke the typesafe-ai agent skill (Claude Code plugin typesafe 0.5.7, MIT), plus a faithful digest of the guidance SKILL.md gives agents.	5.0k	2026-09-20	high
TYPESAFE_* environment variables across SDKs	Exactly four TYPESAFE_* environment variables are read by the SDKs: API_KEY, BASE_URL, DEFAULT_MODEL, LOG_LEVEL — both SDKs read all four.	2.8k	2026-09-17	high
HTTP API: POST /v1/systemone and GET /v1/models	Complete wire contract for POST https://api.typesafe.ai/v1/systemone and GET /v1/models: auth, request body, question and answer shapes, usage, errors.	5.0k	2026-09-17	high
JavaScript/TypeScript SDK: install, client, choice/score/noul	@typesafe-ai/sdk 0.6.0: install, TypeSafeClient config and defaults, systemOne(), choice/score/noul builders, APIPromise, models.list(), logging.	6.9k	2026-09-17	high
JavaScript SDK changelog	@typesafe-ai/sdk releases: 0.5.7 initial public release, 0.6.0 (2026-09-15) makes Score.criteria an ordered sequence — the one breaking change.	1.8k	2026-09-17	high
JavaScript SDK error classes, RetryPolicy, RequestOptions	Error hierarchy of @typesafe-ai/sdk 0.6.0, status-to-class mapping, RetryPolicy defaults (2 retries, 500ms/5s backoff, 0.25 jitter) and RequestOptions.	5.2k	2026-09-17	high
JavaScript SDK interfaces and type aliases	Every interface, type alias and exported variable in @typesafe-ai/sdk 0.6.0, with per-property type/required/default tables and generics examples.	6.0k	2026-09-17	high
Legal: MCA, DPA, privacy, data retention	Developer-facing summary of TypeSafe's MCA, DPA, and Privacy Policy: no training on Input, telemetry carve-out, retention, sub-processors, acceptable use, no uptime SLA.	5.1k	2026-09-17	high
Migrating from /preview/evaluation to /v1/systemone	Every delta between the preview evaluation endpoint and the stable v1 API, with before/after examples, plus the typesafe-client to typesafe-sdk rename table.	3.7k	2026-09-17	high
Models, aliases, pricing, rate limits, context	Jev 1.13 model ID, aliases, $42/Btok pricing with free output tokens, 250k tok/s and 1,200 rpm limits, 64k/32k context rule, and text-only input.	2.7k	2026-09-17	high
OpenAPI component schemas	Every component schema in TypeSafe's OpenAPI 3.1.0 document (info version 0.2.0): properties, types, requiredness, constraints, and examples.	4.8k	2026-09-17	high
Python SDK: install, clients, system_one()	typesafe-sdk 0.6.0: install, TypeSafeClient/AsyncTypeSafeClient constructor params, system_one() kwargs, models resource, env vars, logging, and the full export list.	5.7k	2026-09-17	high
Python SDK changelog	typesafe-sdk release history: 0.0.1a0 placeholder, 0.5.7 initial public release (2026-09-14), 0.6.0 (2026-09-15) with the Score.criteria breaking change.	1.8k	2026-09-17	high
Python SDK question types (Noul, Choice, Score)	Every field of Noul, Choice and Score in typesafe-sdk 0.6.0, their TypedDict equivalents, JSONContent typing, client-side validation, and the 0.6.0 Score.criteria breaking change.	3.1k	2026-09-17	high
Python SDK responses, answers, usage, models	SystemOneResponse fields and the .nouls/.choices/.scores views, every answer attribute, Usage, request_id and raw_http_response, plus ListModelsResponse and ModelMetadata.	3.4k	2026-09-17	high
Python SDK retries, exceptions, constants	RetryPolicy fields and defaults, which statuses and exceptions are retried, backoff and Retry-After handling, the full exception hierarchy with attributes, timeouts, and public constants.	4.7k	2026-09-17	high
HTTP status codes, rate limits, retry semantics	One table mapping every HTTP status to its meaning, Python exception, JS error class, retryability, and the recommended client action.	3.6k	2026-09-17	high
system-one-adapter: LLM-backed drop-in for TypeSafeClient	system-one-adapter answers typesafe_sdk questions with an OpenAI or Anthropic LLM instead of Jev, so you can compare cost, speed, and intelligence on the same code.	5.0k	2026-09-17	high

Patterns (5)

Page	Summary	~Tokens	Updated	Conf.
Composite scoring	Break a ranking judgment into independent Score dimensions, normalize each to 0–1, and combine them with weights your code owns and can retune.	2.1k	2026-09-17	high
Confidence-gated routing	Treat confidence as a second decision axis: one floor below which nothing is automated, then a per-action threshold sized to the consequences of being wrong.	2.2k	2026-09-17	high
Speculative fan-out	Put every question your decision tree could need into one call, including speculative ones, and let code discard the irrelevant answers.	2.2k	2026-09-17	high
Intent routing	Classify the request with one cheap Jev call, then invoke the cheapest adequate handler: deterministic code, a specialist LLM, or a human.	2.6k	2026-09-17	high
Patterns overview	Catalog of TypeSafe's four architectural patterns — fan-out, confidence routing, composite scoring, intent routing — and when to reach for each.	1.8k	2026-09-17	high

Cookbooks (19)

Page	Summary	~Tokens	Updated	Conf.
Cookbook: Structure recovery (autoformat)	Rebuild Markdown from de-formatted plain text in two requests: Nouls stitch hard-wrapped lines, then Choices classify each block; code renders every character from the input.	4.5k	2026-09-17	high
Cookbook: Autoresearch feature discovery	An LLM proposes Jev questions, Jev answers them per row to build numeric columns, CatBoost trains and reports back: 38 questions after five rounds reach 1.77 held-out RMSE on wine scores.	4.7k	2026-09-17	high
Cookbook: Double-checking citations	One Choice question decides whether a quote's surrounding section supports, contradicts, or says nothing about an LLM's claim; a string match catches fabricated quotes first.	2.8k	2026-09-17	high
Cookbook: Classification using confidence	Classify SEC filings into 75 SIC industry groups with one Choice; when confidence < 0.9, report the broader division instead — 40% correct becomes 70%, at no extra call.	2.9k	2026-09-17	high
Cookbook: Classifying RAG passages	Four Noul questions per retrieved query-passage pair, routed by ordered thresholds, decide what reaches the generator as evidence, as conflict, or not at all.	3.6k	2026-09-17	high
Cookbook: Self-consistency — choices	Runs an 8-Choice moderation rubric 15 times across Jev and six LLM conditions; a 0.60 top-probability floor lifts Jev's decision agreement from 90.8% to 99.2% at 74.2% automation.	4.3k	2026-09-17	high
Cookbook: Self-consistency — nouls	Runs a 14-Noul claims rubric 15 times against Jev and six LLM conditions; Jev's mean probability std dev is 0.0102 at 111ms per call, and an uncertain band routes 0.30-0.70 to a human.	3.7k	2026-09-17	high
Cookbook: Date extraction	Seven Choice questions read a date's parts off a document in one call; code does all the calendar math and gates on the weakest part's confidence.	3.9k	2026-09-17	high
Cookbook: Knowledge graph entity alignment	One three-level Score decides merge / curate / leave-unlinked for 450 candidate entity pairs, with three Nouls riding along to tell the curator which field disagrees.	3.0k	2026-09-17	high
Cookbook: Function calling	Map typed Python functions to Jev Choice/Noul questions so a natural-language command becomes a validated call with a per-argument confidence.	2.9k	2026-09-17	high
Cookbook: Hierarchical classification	Walk a deep taxonomy to a leaf by asking one Choice per sibling set, and keep K paths alive with a geometric-mean beam search instead of a greedy walk.	2.9k	2026-09-17	high
Cookbook: Guardrails for LLMs	Screen every LLM input and output with one Jev request: four hazard Nouls plus a severity Score, then route pass / review / block / support on thresholds you own.	3.1k	2026-09-17	high
Cookbooks overview	Catalog of all 18 TypeSafe cookbooks — goal, primitives and domain each — plus how a cookbook is structured and why the published pip line does not work.	3.4k	2026-09-17	high
Cookbook: Parallel questions	Batching 13 questions about one 54k-character document into a single Jev call was 12.2x cheaper and 10.0x faster than 13 single-question calls, with identical answers.	3.1k	2026-09-17	high
Cookbook: Pre-parsed value extraction	A recall-tuned regex finds candidate spans, a Jev Choice over those exact spans picks the one the question asks for, and code copies it verbatim and normalizes it.	2.7k	2026-09-17	high
Cookbook: Re-ranking	BM25 builds a 30-candidate shortlist per CLERC query, then one Noul per query-candidate pair re-sorts it: top-1 rises 5% to 18%, top-10 38% to 62% for $0.0645.	2.6k	2026-09-17	high
Cookbook: SDE cascade	Extract with a cheap model, verify every field with a battery of Jev Nouls framed so true means wrong, and escalate to a reasoning model only when a flag fires.	4.0k	2026-09-17	high
Cookbook: Line-by-line search	Tag a document's lines with ids, rank them with one Choice over those ids, and pair it with a Noul that says whether the document answers the query at all.	2.4k	2026-09-17	high
Cookbook: Skill suggestion	Two Jev requests per agent turn — rank 182 skills then re-read the top three — cut wrong skill loads from 16.8% to 7.3% and needless loads from 9.8% to 4.0%.	3.8k	2026-09-17	high

Syntheses (4)

Page	Summary	~Tokens	Updated	Conf.
FAQ for agents and developers	Forty answers about Jev — what it is, the API, the SDKs, design, confidence, limits and pricing, company and legal — each linked to the page carrying the detail.	4.9k	2026-09-17	high
Glossary	Sixty-nine Jev, TypeSafe, API, SDK and evaluation terms defined in one or two sentences, alphabetical, each linked to the page with the full contract.	4.7k	2026-09-17	high
Jev vs LLM JSON mode / structured outputs	What Jev gives you that an LLM in JSON mode does not (and vice versa), a row-by-row comparison, when to pick each, how to combine them, and how to benchmark the pair honestly.	4.3k	2026-09-17	medium
Versions and timeline (models, SDKs, API, company)	Every datable fact in the wiki on one axis: company, model versions, API, both SDKs, the plugin and adapter, legal documents, repo commits, and where the dates disagree.	4.0k	2026-09-17	medium

Entities (11)

Page	Summary	~Tokens	Updated	Conf.
Blog: Lies, Damned Lies, and Benchmarks	2026-09-11 post against benchmaxxing, ending in TypeSafe's commitment to publish no standard benchmark table and to retire dated eval snapshots.	1.7k	2026-09-17	high
Blog: The Bitterest Lesson	2026-09-10 post arguing the ML priority order is doing the right task > data > compute > algorithms, using InstructGPT vs GPT-3 as the proof.	1.4k	2026-09-17	high
Blog: Introducing System One Models & Jev (2026-09-15)	Digest of TypeSafe's launch post: System One vs LLM comparison table, price/speed claims, the evidence section, and the caveats the post states itself.	2.6k	2026-09-17	high
Blog: AI: too good to be true, too bad to be useful (2026-06-19)	Stub: the body of this 2026-06-19 TypeSafe post was not captured (JS-rendered); only title, date, category, and the homepage teaser are known.	0.7k	2026-09-17	low
typesafe-ai GitHub organisation and repos	The github.com/typesafe-ai org: two SDKs, the agent skill marketplace, the System One adapter, plus infra repos and two forks.	2.3k	2026-09-20	high
Jev (model)	Jev is TypeSafe's first System One model: text in, typed decisions with calibrated probabilities out, $0.042/MTok input, 64k context, 70-500 ms.	1.6k	2026-09-17	high
Manifesto: Composable AI — Build Prod, Not God	TypeSafe's manifesto argues the bottleneck is composability, not intelligence, and lays out a three-step plan to make AI a dependable software primitive.	1.7k	2026-09-17	high
Press and third-party coverage	Outlet-by-outlet digest of Jev's launch coverage (2026-09-15/16), separating TypeSafe's claims from each outlet's own assertions and caveats.	3.5k	2026-09-17	medium
Founders and team	TypeSafe AI's three founders (Diogo Almeida CEO, Sasha Sheng COO, Erik Gafni CTO), the team's stated culture and values, and the SDK maintainers.	1.5k	2026-09-17	high
TypeSafe AI (company)	TypeSafe AI, Inc. is a San Francisco frontier AI lab that left stealth on 2026-09-15 with $40M led by DCVC and Jev, its first System One model.	2.5k	2026-09-17	high
console.typesafe.ai (console + playground)	console.typesafe.ai is TypeSafe's Web Interface: log in with Google or an email code, try Jev in the Playground, and mint API keys.	1.1k	2026-09-17	medium

Tags

acceptable-use: Legal: MCA, DPA, privacy, data retention
adapter: system-one-adapter: LLM-backed drop-in for TypeSafeClient
advanced: Structured instructions, options, levels, criteria
agent: Playbook for LLM agents building with Jev
agent-skill: The typesafe-ai agent skill and Claude Code plugin
agents: Cookbook: Skill suggestion
answers: Primitives: Choice, Score, Noul, Python SDK responses, answers, usage, models
anthropic: system-one-adapter: LLM-backed drop-in for TypeSafeClient
api-key: Quickstart: first call in HTTP, Python, JS
api-keys: console.typesafe.ai (console + playground)
architecture: How to build software with System One, System One Models, Patterns overview
autoformat: Cookbook: Structure recovery (autoformat)
autoresearch: Cookbook: Autoresearch feature discovery
batching: Cookbook: Parallel questions
beam-search: Cookbook: Hierarchical classification
benchmarking: system-one-adapter: LLM-backed drop-in for TypeSafeClient
benchmarks: Workflow evals: how TypeSafe measures Jev, Blog: Lies, Damned Lies, and Benchmarks, Field reports: independent evaluations, critiques, open replicas
blog: Blog: Lies, Damned Lies, and Benchmarks, Blog: The Bitterest Lesson, Blog: Introducing System One Models & Jev (2026-09-15), Blog: AI: too good to be true, too bad to be useful (2026-06-19)
bm25: Cookbook: Re-ranking
breaking-changes: Migrating from /preview/evaluation to /v1/systemone
calibration: Confidence vs probability, AI primer: why calibrated decision models, System One Models, Testing and evaluating a Jev workflow
cascade: Cookbook: SDE cascade
catalog: Cookbooks overview
catboost: Cookbook: Autoresearch feature discovery
changelog: JavaScript SDK changelog, Python SDK changelog
checklist: Playbook for LLM agents building with Jev
choice: Choice questions, Primitives: Choice, Score, Noul, Cookbook: Structure recovery (autoformat), Cookbook: Double-checking citations, Cookbook: Classification using confidence, Cookbook: Self-consistency — choices, Cookbook: Date extraction, Cookbook: Function calling, Cookbook: Hierarchical classification, Cookbook: Pre-parsed value extraction, Cookbook: Line-by-line search, Cookbook: Skill suggestion, Choosing between Choice, Score, Noul, Python SDK question types (Noul, Choice, Score)
citation-check: Cookbook: Double-checking citations
claims: Workflow evals: how TypeSafe measures Jev, Blog: Introducing System One Models & Jev (2026-09-15), Press and third-party coverage, TypeSafe AI (company), FAQ for agents and developers
classification: Choice questions, Cookbook: Classification using confidence, Cookbook: Hierarchical classification, Intent routing
claude-code: The typesafe-ai agent skill and Claude Code plugin
client: JavaScript/TypeScript SDK: install, client, choice/score/noul, Python SDK: install, clients, system_one()
community: Community repos: what people built and how they use Jev, Ideas section overview, Decision patterns from the community (with fit verdicts)
company: TypeSafe AI (company)
comparison: Jev vs LLM JSON mode / structured outputs
composable-ai: Manifesto: Composable AI — Build Prod, Not God
composition: How to build software with System One, Composite scoring
confidence: Choice questions, Confidence vs probability, Score questions, Cookbook: Double-checking citations, Cookbook: Classification using confidence, Cookbook: Date extraction, Confidence-gated routing
configuration: TYPESAFE_* environment variables across SDKs
consistency: Cookbook: Self-consistency — choices, Cookbook: Self-consistency — nouls, Testing and evaluating a Jev workflow
console: console.typesafe.ai (console + playground)
constants: Python SDK retries, exceptions, constants
consult: Consult guide: could Jev help this project?
context: State: what you send Jev
context-length: Models, aliases, pricing, rate limits, context
cookbook: Cookbook: Structure recovery (autoformat), Cookbook: Autoresearch feature discovery, Cookbook: Double-checking citations, Cookbook: Classification using confidence, Cookbook: Classifying RAG passages, Cookbook: Self-consistency — choices, Cookbook: Self-consistency — nouls, Cookbook: Date extraction, Cookbook: Knowledge graph entity alignment, Cookbook: Function calling, Cookbook: Hierarchical classification, Cookbook: Guardrails for LLMs, Cookbooks overview, Cookbook: Parallel questions, Cookbook: Pre-parsed value extraction, Cookbook: Re-ranking, Cookbook: SDE cascade, Cookbook: Line-by-line search, Cookbook: Skill suggestion
cost: Cookbook: Parallel questions, Speculative fan-out
coverage: Press and third-party coverage
criteria: Structured instructions, options, levels, criteria, Writing instructions and criteria that Jev reads correctly
critiques: Field reports: independent evaluations, critiques, open replicas
culture: Founders and team
curl: Quickstart: first call in HTTP, Python, JS
data-retention: Legal: MCA, DPA, privacy, data retention
date-extraction: Cookbook: Date extraction
dates: Versions and timeline (models, SDKs, API, company)
decision: Choosing between Choice, Score, Noul
decision-guide: Jev vs LLM JSON mode / structured outputs
decision-mapping: Consult guide: could Jev help this project?
decision-table: Playbook for LLM agents building with Jev
decomposition: How to build software with System One
deduplication: Cookbook: Knowledge graph entity alignment
definitions: Glossary
demo: Smart home assistant demo walkthrough
design: How to build software with System One
dispatch: Cookbook: Function calling
dpa: Legal: MCA, DPA, privacy, data retention
entity-alignment: Cookbook: Knowledge graph entity alignment
environment-variables: TYPESAFE_* environment variables across SDKs
errors: HTTP API: POST /v1/systemone and GET /v1/models, JavaScript SDK error classes, RetryPolicy, RequestOptions, Python SDK retries, exceptions, constants, HTTP status codes, rate limits, retry semantics
evals: Workflow evals: how TypeSafe measures Jev, Blog: Lies, Damned Lies, and Benchmarks, Blog: Introducing System One Models & Jev (2026-09-15), Press and third-party coverage
evaluation: Cookbook: Self-consistency — nouls, Testing and evaluating a Jev workflow
evaluations: Field reports: independent evaluations, critiques, open replicas
examples: Community repos: what people built and how they use Jev
exceptions: HTTP status codes, rate limits, retry semantics
extraction: Cookbook: Pre-parsed value extraction, Cookbook: SDE cascade
failure-modes: Jev 1.13 jaggedness: known failure modes
fan-out: Cookbook: Parallel questions, Smart home assistant demo walkthrough, Speculative fan-out, Patterns overview
faq: FAQ for agents and developers
feature-engineering: Cookbook: Autoresearch feature discovery
field-reports: Field reports: independent evaluations, critiques, open replicas
fit-verdicts: Decision patterns from the community (with fit verdicts)
founders: Founders and team
function-calling: Cookbook: Function calling
funding: TypeSafe AI (company)
github: typesafe-ai GitHub organisation and repos
glossary: Glossary
guardrails: Cookbook: Guardrails for LLMs
guide: Choosing between Choice, Score, Noul, Writing instructions and criteria that Jev reads correctly
hiring: Founders and team
http-api: HTTP API: POST /v1/systemone and GET /v1/models, Migrating from /preview/evaluation to /v1/systemone, OpenAPI component schemas, HTTP status codes, rate limits, retry semantics
ideas: Consult guide: could Jev help this project?, Ideas section overview, Decision patterns from the community (with fit verdicts)
ideation: Use-case map by industry
index: Cookbooks overview, Jev Wiki — Master Index, Glossary
industry: Use-case map by industry
input: State: what you send Jev
install: Python SDK: install, clients, system_one()
installation: The typesafe-ai agent skill and Claude Code plugin
instructgpt: Blog: The Bitterest Lesson
instructions: Structured instructions, options, levels, criteria, Writing instructions and criteria that Jev reads correctly
integration: Playbook for LLM agents building with Jev
integrations: Community repos: what people built and how they use Jev
intent: Intent routing
jaggedness: Jev 1.13 jaggedness: known failure modes, Writing instructions and criteria that Jev reads correctly
javascript: Quickstart: first call in HTTP, Python, JS, JavaScript SDK changelog, JavaScript SDK error classes, RetryPolicy, RequestOptions, JavaScript SDK interfaces and type aliases, JavaScript/TypeScript SDK: install, client, choice/score/noul
javascript-sdk: TYPESAFE_* environment variables across SDKs
jev: System One Models, Blog: Introducing System One Models & Jev (2026-09-15), Jev (model), Models, aliases, pricing, rate limits, context
jev-1-13: Jev 1.13 jaggedness: known failure modes
json: State: what you send Jev
json-mode: Jev vs LLM JSON mode / structured outputs
latency: Cookbook: Parallel questions, Speculative fan-out
launch: Blog: Introducing System One Models & Jev (2026-09-15)
legal: console.typesafe.ai (console + playground), Legal: MCA, DPA, privacy, data retention
levels: Score questions
limitations: Jev 1.13 jaggedness: known failure modes
limits: State: what you send Jev, Jev (model)
llm: Jev vs LLM JSON mode / structured outputs
llm-fallback: Smart home assistant demo walkthrough
llm-orchestration: Intent routing
log: Activity log
login: console.typesafe.ai (console + playground)
manifesto: Manifesto: Composable AI — Build Prod, Not God
markdown: Cookbook: Structure recovery (autoformat)
methodology: Workflow evals: how TypeSafe measures Jev, Blog: Lies, Damned Lies, and Benchmarks
migration: Migrating from /preview/evaluation to /v1/systemone
mission: Manifesto: Composable AI — Build Prod, Not God
model: Jev (model)
models: HTTP API: POST /v1/systemone and GET /v1/models, Models, aliases, pricing, rate limits, context, Python SDK responses, answers, usage, models
moderation: Cookbook: Self-consistency — choices
needs-reingestion: Blog: AI: too good to be true, too bad to be useful (2026-06-19)
noul: Noul (yes/no) questions, Primitives: Choice, Score, Noul, Cookbook: Structure recovery (autoformat), Cookbook: Autoresearch feature discovery, Cookbook: Classifying RAG passages, Cookbook: Self-consistency — nouls, Cookbook: Knowledge graph entity alignment, Cookbook: Function calling, Cookbook: Guardrails for LLMs, Cookbook: Pre-parsed value extraction, Cookbook: Re-ranking, Cookbook: SDE cascade, Cookbook: Line-by-line search, Cookbook: Skill suggestion, Choosing between Choice, Score, Noul, Python SDK question types (Noul, Choice, Score)
npm: JavaScript SDK changelog
onboarding: FAQ for agents and developers
open-source: typesafe-ai GitHub organisation and repos
openai: system-one-adapter: LLM-backed drop-in for TypeSafeClient
openapi: OpenAPI component schemas
overview: Ideas section overview
packages: typesafe-ai GitHub organisation and repos
parsing: Cookbook: Date extraction
patterns: Use-case map by industry, Cookbooks overview, Decision patterns from the community (with fit verdicts), Composite scoring, Confidence-gated routing, Speculative fan-out, Intent routing, Patterns overview
playbook: Playbook for LLM agents building with Jev
playground: console.typesafe.ai (console + playground)
plugin: The typesafe-ai agent skill and Claude Code plugin
positioning: Manifesto: Composable AI — Build Prod, Not God
press: Press and third-party coverage
pricing: Jev (model), Models, aliases, pricing, rate limits, context
primitives: Choice questions, Noul (yes/no) questions, Primitives: Choice, Score, Noul, Score questions, Choosing between Choice, Score, Noul
privacy: Legal: MCA, DPA, privacy, data retention
probabilities: Choice questions, Confidence vs probability
probability: Noul (yes/no) questions
products: TypeSafe AI (company)
progressive-disclosure: Cookbook: Skill suggestion
project-assessment: Consult guide: could Jev help this project?
prompt-injection: Cookbook: Classifying RAG passages
prompting: Writing instructions and criteria that Jev reads correctly
provenance: Versions and timeline (models, SDKs, API, company)
python: Quickstart: first call in HTTP, Python, JS, Python SDK changelog, Python SDK question types (Noul, Choice, Score), Python SDK responses, answers, usage, models, Python SDK retries, exceptions, constants, Python SDK: install, clients, system_one(), system-one-adapter: LLM-backed drop-in for TypeSafeClient
python-sdk: TYPESAFE_* environment variables across SDKs, Migrating from /preview/evaluation to /v1/systemone
questions: Primitives: Choice, Score, Noul, Python SDK question types (Noul, Choice, Score), FAQ for agents and developers
quickstart: Quickstart: first call in HTTP, Python, JS
rag: Cookbook: Classifying RAG passages
ranking: Composite scoring
rate-limits: Models, aliases, pricing, rate limits, context, HTTP status codes, rate limits, retry semantics
reference: HTTP API: POST /v1/systemone and GET /v1/models, JavaScript SDK interfaces and type aliases, JavaScript/TypeScript SDK: install, client, choice/score/noul, OpenAPI component schemas, Glossary
regex: Cookbook: Pre-parsed value extraction
releases: Python SDK changelog, Versions and timeline (models, SDKs, API, company)
reliability: Jev 1.13 jaggedness: known failure modes
replicas: Community repos: what people built and how they use Jev, Field reports: independent evaluations, critiques, open replicas
repos: typesafe-ai GitHub organisation and repos, Community repos: what people built and how they use Jev
rerank: Cookbook: Re-ranking
research-philosophy: Blog: The Bitterest Lesson
responses: Python SDK responses, answers, usage, models
retries: JavaScript SDK error classes, RetryPolicy, RequestOptions, Python SDK retries, exceptions, constants, HTTP status codes, rate limits, retry semantics
retrieval: Cookbook: Classifying RAG passages, Cookbook: Re-ranking
rlcd: AI primer: why calibrated decision models, System One Models
rlhf: AI primer: why calibrated decision models, Blog: The Bitterest Lesson, Blog: AI: too good to be true, too bad to be useful (2026-06-19)
rlvr: AI primer: why calibrated decision models
routing: Confidence vs probability, Ideas section overview, Confidence-gated routing, Intent routing, Patterns overview
rubric: Score questions
safety: Cookbook: Guardrails for LLMs, Confidence-gated routing
scaling: Blog: The Bitterest Lesson
schemas: OpenAPI component schemas
score: Primitives: Choice, Score, Noul, Score questions, Cookbook: Autoresearch feature discovery, Cookbook: Knowledge graph entity alignment, Cookbook: Guardrails for LLMs, Choosing between Choice, Score, Noul, Composite scoring, Python SDK question types (Noul, Choice, Score)
scoring: Patterns overview
sdk: typesafe-ai GitHub organisation and repos, JavaScript SDK changelog, JavaScript SDK error classes, RetryPolicy, RequestOptions, JavaScript SDK interfaces and type aliases, JavaScript/TypeScript SDK: install, client, choice/score/noul, Python SDK changelog, Python SDK question types (Noul, Choice, Score), Python SDK responses, answers, usage, models, Python SDK retries, exceptions, constants, Python SDK: install, clients, system_one()
search: Cookbook: Line-by-line search
skills: The typesafe-ai agent skill and Claude Code plugin
smart-home: Smart home assistant demo walkthrough
speculative: Smart home assistant demo walkthrough, Speculative fan-out
state: State: what you send Jev
structure: Structured instructions, options, levels, criteria
structured-outputs: Jev vs LLM JSON mode / structured outputs
stub: Blog: AI: too good to be true, too bad to be useful (2026-06-19)
system-one: System One Models, Jev (model), Python SDK: install, clients, system_one()
systemone: HTTP API: POST /v1/systemone and GET /v1/models
taxonomy: Structured instructions, options, levels, criteria, Cookbook: Classification using confidence, Cookbook: Hierarchical classification
team: Founders and team
terminology: Glossary
testing: Testing and evaluating a Jev workflow
third-party: Press and third-party coverage
thresholds: Confidence vs probability, Noul (yes/no) questions, Cookbook: Line-by-line search, Testing and evaluating a Jev workflow, Confidence-gated routing
timeline: Versions and timeline (models, SDKs, API, company)
timeouts: Python SDK retries, exceptions, constants
token-budget: Consult guide: could Jev help this project?
training: AI primer: why calibrated decision models
troubleshooting: FAQ for agents and developers
trust: Blog: Lies, Damned Lies, and Benchmarks
types: JavaScript SDK interfaces and type aliases
typesafe-ai: TypeSafe AI (company)
typescript: JavaScript SDK error classes, RetryPolicy, RequestOptions, JavaScript SDK interfaces and type aliases, JavaScript/TypeScript SDK: install, client, choice/score/noul
uncertainty: Cookbook: Self-consistency — choices, Cookbook: Self-consistency — nouls
usage: Python SDK responses, answers, usage, models
use-cases: Use-case map by industry, Decision patterns from the community (with fit verdicts)
v1: Migrating from /preview/evaluation to /v1/systemone
validation: OpenAPI component schemas
verification: Cookbook: Double-checking citations, Cookbook: SDE cascade
versions: JavaScript SDK changelog, Python SDK changelog, Versions and timeline (models, SDKs, API, company)
weights: Composite scoring
workflow: How to build software with System One
workflows: Workflow evals: how TypeSafe measures Jev
yes-no: Noul (yes/no) questions

Jev Wiki — an unofficial, agent-maintained knowledge base about TypeSafe AI’s Jev. Built 2026-09-21 · raw markdown · llms.txt