The shipwithjev press · 151 posts · page 3 of 4
Blog.
What the builds in the catalog add up to. Every post goes through the same gate: every number is as reported by its author.
- Questions 31
- Builds & people 30
- Recipes 23
- Comparisons 18
- Guardrails 9
- Evals & judging 8
- Triage & routing 8
- Cost 7
- Classification 6
- Calibration 5
- Monitoring 4
- Essays 2
- FIG. 72Questions
What Is TypeLLM? The Open-Source Answer to Typed Decisions
TypeLLM brings Jev's typed-decision interface to self-hosted open models: closed questions, structured answers, your infrastructure. When it beats hosted.
Sep 30, 2026Read →
- FIG. 71Questions
What Is jev-tree? Recursion Past the 255-Choice Cap
jev-tree is the community library that turns giant answer sets into staged Jev questions, past the ~255-choice cap. How it works and when you need it.
Sep 30, 2026Read →
- FIG. 70Questions
What Is jev-harness? The TypeScript Ecosystem's Workbench
jev-harness is the community TypeScript client for Jev: typed questions, batching, and Node/edge ergonomics. What it's for and how it fits your stack.
Sep 30, 2026Read →
- FIG. 69Questions
What Is awesome-jev? The Ecosystem's Front Door on GitHub
awesome-jev is the community-curated GitHub list of Jev tools, SDKs, and resources. What lives there, how it differs from this directory, why both exist.
Sep 30, 2026Read →
- FIG. 68Questions
What Is Ask Jev? The Chrome Extension That Puts Verdicts on Every Page
Ask Jev is a Chrome extension exposing Jev's Choice API on any webpage: highlight, ask, get probabilities. What it does and why it's a perfect demo.
Sep 30, 2026Read →
- FIG. 67Questions
What Does "Jev" Stand For? The Name, the Confusion, the Namesakes
What "Jev" means, what TypeSafe has and hasn't said about the name, and the disambiguation the internet needs: the model, the YouTuber, the vaccine.
Sep 30, 2026Read →
- FIG. 66Recipes
Wiring Jev Into Zapier, n8n, and Webhook Automations
How to put Jev verdicts inside no-code and low-code automations: the webhook pattern, where the verdict belongs in a flow, and the gates you still need.
Sep 30, 2026Read →
- FIG. 65Comparisons
Jev vs ChatGPT: You're Comparing a Referee to a Novelist
Jev vs ChatGPT in plain terms: one converses and creates, one issues instant structured verdicts. When each wins, with reported numbers, minus the hype.
Sep 30, 2026Read →
- FIG. 64Cost
Jev Rate Limits: What's Known, and How to Build So They Don't Matter
Jev's rate limits live in TypeSafe's docs and change at launch speed. The architecture that makes any limit survivable: queues, caches, batches, backoff.
Sep 30, 2026Read →
- FIG. 63Builds & people
Jev's Context Window: What Fits in a Question (And What Shouldn't)
How much text fits in a Jev question, why the honest answer is "less than you want, more than you need," and the section-and-aggregate pattern.
Sep 30, 2026Read →
- FIG. 62Calibration
How Accurate Is Jev? What We Can Honestly Say Without Benchmarks
No official Jev benchmarks exist. What reported builds actually show about accuracy, why question design dominates, and how to measure yours in an hour.
Sep 30, 2026Read →
- FIG. 61Questions
Is Jev Safe to Use? The Five Questions That Actually Decide It
Is Jev safe for your data and your product? The five real questions: what leaves your systems, verdict reliability, vendor trust, injection, and stakes.
Sep 30, 2026Read →
- FIG. 60Questions
Is Jev Open Source? No: Here's the Actual Landscape
Jev's weights are not open source. What is open around it (SDKs, tooling), the open-source alternative TypeLLM, and when self-hosting actually pencils out.
Sep 30, 2026Read →
- FIG. 59Questions
Is Jev Free? Pricing, Access, and What Builders Actually Pay
Is Jev free to use? What we know about access and pricing, plus the real costs builders report: workloads from $0.0004 to $0.13. Sources linked.
Sep 30, 2026Read →
- FIG. 58Questions
How to Get Jev Access: The Current Path, Minus the Guesswork
Getting access to Jev in practice: where signup actually lives, what the gateway setup involves per ecosystem reports, and what to do while you wait.
Sep 30, 2026Read →
- FIG. 57Cost
Jev Cost Per Request: The Napkin Math With Real Receipts
What a single Jev request costs in practice, derived from builder-reported workloads, plus the three-number napkin method for budgeting any pipeline.
Sep 30, 2026Read →
- FIG. 56Questions
Does Jev Work in Languages Other Than English? What Reports Show
Can Jev judge non-English text? What ecosystem reports and builds suggest about multilingual verdicts, plus the calibration rule that matters per language.
Sep 30, 2026Read →
- FIG. 55Questions
Does Jev Have an API? Yes: What the Ecosystem Documents
Jev's API as the ecosystem documents it: typesafe-ai/jev via the Vercel AI Gateway, an evaluate surface, choice probabilities, and SDKs in four languages.
Sep 30, 2026Read →
- FIG. 54Questions
Can Jev Write Code? No, and Knowing Why Makes You Better at Using It
Jev cannot write code, essays, or anything else: it's a decision model. What that means, why it's the point, and what developers use it for instead.
Sep 30, 2026Read →
- FIG. 53Questions
Can Jev Run Locally? No, and Here's the Decision Tree That Follows
Jev is hosted-only: no local weights, no on-device inference. What that means for offline, edge, and privacy cases, and the honest alternatives for each.
Sep 30, 2026Read →
- FIG. 52Questions
Can Jev Replace My Trained Classifier? A Five-Minute Decision
The five-minute answer to replacing a trained ML classifier with Jev: when yes, when absolutely not, and the migration that keeps both honest.
Sep 30, 2026Read →
- FIG. 51Questions
Can Jev Judge Images? Not Directly, and the Workaround Is the Lesson
Jev judges text, not pixels. But the screenshot-free pattern, local extraction feeding text verdicts, handles more image work than you'd expect.
Sep 30, 2026Read →
- FIG. 50Evals & judging
AI Grading: Feedback at the Speed of Homework
AI grading done honestly: rubric verdicts on short answers, instant formative feedback, and the line between grading support and grade automation.
Sep 22, 2026Read →
- FIG. 49Classification
AI Resume Screening: The Use Case That Demands Adult Supervision
Resume screening with judge verdicts: what it does well, where bias law applies, why NYC-style audit rules exist, and the design that keeps hiring human.
Sep 22, 2026Read →
- FIG. 48Cost
Why Decisions Became Free (And What Gets Built Because of It)
The essay version of what 600+ builds are saying: when structured judgment costs nothing, software grows a judging layer everywhere, and the map redraws.
Sep 22, 2026Read →
- FIG. 47Builds & people
Jev for Founders: The Solo Operator's Unfair Advantage Stack
What one person can automate with a verdict machine: inbox, leads, support, content QA, and ops checks, assembled from real builds into a solo stack.
Sep 22, 2026Read →
- FIG. 46Guardrails
Jev Security and Privacy: What Leaves Your Systems, and What Shouldn't
The security questions to ask before wiring a decision model into real data: what leaves, PII minimization, local-perception pattern, and audit posture.
Sep 22, 2026Read →
- FIG. 45Builds & people
Jev in Production: The Ops Guide the Launch Threads Skipped
The unglamorous guide to running a decision model in production: caching, retries, versioning, monitoring, batching, and the failure modes that page you.
Sep 22, 2026Read →
- FIG. 44Triage & routing
AI Invoice Processing: The Back Office Meets the Verdict Machine
Invoice processing as judgments: categorization, PO matching, anomaly flags, and approval routing at verdict prices, with the controls finance requires.
Sep 22, 2026Read →
- FIG. 43Guardrails
AI Spam Detection: Filtering an Adversary, Not a Category
Spam is the one classification problem that fights back. How decision-model filters handle adversarial text, what breaks them, and the layered defense.
Sep 22, 2026Read →
- FIG. 42Comparisons
Fine-Tuning vs Prompting vs Decision Models: Picking Your Adaptation
The three ways to make a model yours: prompting, fine-tuning, and decision-model question design. When each wins, what each costs, and the sequencing.
Sep 22, 2026Read →
- FIG. 41Evals & judging
AI Call QA Scoring: Grading Every Conversation, Not Two Percent
Contact-center QA reviews 1-2% of calls and calls it quality. How judge verdicts on transcripts score every call for compliance, empathy, and outcomes.
Sep 22, 2026Read →
- FIG. 40Triage & routing
Churn Prediction With AI: Reading the Leaving Before the Left
Churn prediction without the data-science project: judging cancellation language, sentiment trajectory, and risk signals in the text customers already send
Sep 22, 2026Read →
- FIG. 39Classification
Document Classification: Sorting the PDF Mountain for Cents
Document classification with decision models: route contracts, invoices, forms, and reports by type, urgency, and risk, chunking realities included.
Sep 22, 2026Read →
- FIG. 38Classification
Entity Resolution: "Are These the Same Thing?" at a Cent a Thousand
Entity resolution is the oldest data problem wearing new prices: record matching, dedup, and identity linking as pairwise judge verdicts, with blocking.
Sep 22, 2026Read →
- FIG. 37Builds & people
The Decision Model Glossary: Every Term This Site Uses, Defined
The working vocabulary of the decision-model era, defined in plain language: verdicts, cascades, confidence gates, judge questions, blocking, grounding.
Sep 22, 2026Read →
- FIG. 36Classification
Intent Classification: The NLU Job That Just Got a New Engine
Intent detection powered chatbots for a decade, badly. How decision models replace trained NLU intent classifiers: no training data, editable taxonomies.
Sep 22, 2026Read →
- FIG. 35Classification
Sentiment Analysis With LLMs: From Vibes Dashboard to Verdicts
Sentiment analysis grew up: decision models judge emotion, intent, and churn signals per message for fractions of a cent. How to avoid the old traps.
Sep 22, 2026Read →
- FIG. 34Guardrails
Prompt Injection Detection: Judging Input Before Your AI Reads It
Prompt injection is the SQL injection of the LLM era. How a cheap judge layer screens untrusted input before your main model reads it, and its limits.
Sep 22, 2026Read →
- FIG. 33Guardrails
LLM Guardrails: The Judge Between Your Model and the Send Button
Guardrails are verdicts on your own AI's outputs before they reach users: policy, grounding, tone, and safety checks cheap enough to check everything.
Sep 22, 2026Read →