Laravel AI Preflight Checker with Jev Probability Scores | Mohamed Said [ ![Mohamed Said](https://cdn.msaied.com/01KT78WE565VEMM3PSNQAAB0MH.png) Mohamed Said Laravel Backend Engineer ](https://www.msaied.com) [ Home ](https://www.msaied.com) [ Projects ](https://www.msaied.com/projects) [ Articles ](https://www.msaied.com/articles) [ Certificates ](https://www.msaied.com/certificates) [ Contact ](https://www.msaied.com#contact-section) [ ](https://github.com/EG-Mohamed) [ Home ](https://www.msaied.com) [ Projects ](https://www.msaied.com/projects) [ Articles ](https://www.msaied.com/articles) [ Certificates ](https://www.msaied.com/certificates) [ Contact ](https://www.msaied.com#contact-section) [ home ](https://www.msaied.com) [ articles ](https://www.msaied.com/articles) Decide with Jev: Build a Laravel AI Content Preflight Checker That Returns a Probability On this page 1. [ What Is "Decide with Jev"? ](#what-is-quotdecide-with-jevquot) 2. [ Why a Probability Score Instead of Text? ](#why-a-probability-score-instead-of-text) 3. [ Setting Up the Project ](#setting-up-the-project) 4. [ The Four Test Drafts ](#the-four-test-drafts) 5. [ First Results in Tinkerwell ](#first-results-in-tinkerwell) 6. [ What Comes Next ](#what-comes-next) 7. [ Key Takeaways ](#key-takeaways) ![Decide with Jev: Build a Laravel AI Content Preflight Checker That Returns a Probability](https://cdn.msaied.com/701/916a0dd2b427c6335395d6d2684524ab.png) [ Laravel ](https://www.msaied.com/articles?category=laravel) [ AI ](https://www.msaied.com/articles?category=ai) #Laravel AI #Jev #TypeSafe #AI SDK #content automation #PHP AI Decide with Jev: Build a Laravel AI Content Preflight Checker That Returns a Probability ========================================================================================== 25 Sep 2026 4 min read ![Mohamed Said](https://cdn.msaied.com/01M22N44A70A5MC2S599JP0MPH.webp) Mohamed Said Table of contents 1. [ 01 What Is "Decide with Jev"? ](#what-is-quotdecide-with-jevquot) 2. [ 02 Why a Probability Score Instead of Text? ](#why-a-probability-score-instead-of-text) 3. [ 03 Setting Up the Project ](#setting-up-the-project) 4. [ 04 The Four Test Drafts ](#the-four-test-drafts) 5. [ 05 First Results in Tinkerwell ](#first-results-in-tinkerwell) 6. [ 06 What Comes Next ](#what-comes-next) 7. [ 07 Key Takeaways ](#key-takeaways) What Is "Decide with Jev"? -------------------------- [Decide with Jev](https://laravel-news.com/decide-with-jev-laravel-ai-that-answers-with-a-probability) is a new mini course on Laravel News by Harris Raftopoulos. The goal is to build a **content preflight checker** — an app that compares a written draft against its brief and tells you how well the two align, before the draft ever reaches an editor. The analogy is deliberate: pilots run a preflight checklist before takeoff. This app runs the same kind of check on content. Why a Probability Score Instead of Text? ---------------------------------------- Most AI models you interact with return a paragraph. Jev, an AI model from a company called TypeSafe, returns a **number between 0 and 1** — the probability that the answer to your yes/no question is "yes." That distinction matters in PHP: - A paragraph is hard to act on programmatically. - A number is easy to route through business logic. A score of `0.96` means the draft almost certainly satisfies the brief. A score of `0.02` means it almost certainly does not. Anything in the middle can be flagged for human review. PHP can enforce thresholds on a float; it cannot reliably parse intent from a sentence. > **Important caveat:** The number is the model's confidence in "yes" — it is not proof the answer is correct. Setting Up the Project ---------------------- Episode 1 covers installation and first contact with the API. ```bash # Install the Laravel AI SDK (stable branch now includes this feature) composer require laravel/ai ``` Add your TypeSafe API key to `.env`: ```env TYPESAFE_API_KEY=your-key-here ``` Jev runs on TypeSafe's servers, so there is nothing extra to install locally. > **Note:** The video was recorded against the `1.x` dev branch of the Laravel AI SDK because the Jev feature had not yet merged. It has since landed on the main branch, so a standard `composer require` is all you need. The Four Test Drafts -------------------- To have something meaningful to score, Harris wrote four short drafts for a single brief: *show a Laravel developer how to add a `GET /hello` route and verify it in the browser.* | Draft | Description | |---|---| | 1 | Complete — covers every step the brief requires | | 2 | Mentions routes but provides no actionable steps | | 3 | Mixed — some opinion and product news, only one instruction | | 4 | Adversarial — instructs the model to ignore the brief | Draft 4 is reserved for a later episode where prompt-injection resistance is tested. First Results in Tinkerwell --------------------------- With the SDK configured, Harris queries Jev directly from Tinkerwell: ```php use Laravel\AI\Facades\AI; $score = AI::jev()->decide( question: 'Does this draft fulfill the brief?', context: $brief . '\n\n' . $draft ); // Draft 1 (complete) → 0.96 // Draft 2 (thin) → 0.02 ``` The gap between `0.96` and `0.02` is exactly what you want from a classifier: a clear signal at both ends of the scale. What Comes Next --------------- Episode 2 expands the single question into three parallel checks: 1. Does the draft fulfill the brief? 2. What type of content is it? 3. How clear are the instructional steps? Running multiple Jev queries gives you a richer signal without asking the model to produce prose you then have to parse. Key Takeaways ------------- - **Jev returns a probability**, not text — making it directly usable in PHP conditionals and routing logic. - **The Laravel AI SDK** (stable branch) now supports Jev out of the box; no dev branch required. - **A content preflight checker** is a practical, low-risk way to introduce AI into an editorial workflow without removing human oversight. - **Probability ≠ truth** — treat the score as a signal, not a verdict. - The project source is available at [github.com/harris21/decide-with-jev](https://github.com/harris21/decide-with-jev). --- *Source: [Decide with Jev: Laravel AI That Answers with a Probability — Laravel News](https://laravel-news.com/decide-with-jev-laravel-ai-that-answers-with-a-probability)* Found this useful? [ ](https://twitter.com/intent/tweet?url=https%3A%2F%2Fwww.msaied.com%2Farticles%2Fdecide-with-jev-build-a-laravel-ai-content-preflight-checker-that-returns-a-probability&text=Decide+with+Jev%3A+Build+a+Laravel+AI+Content+Preflight+Checker+That+Returns+a+Probability) [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.msaied.com%2Farticles%2Fdecide-with-jev-build-a-laravel-ai-content-preflight-checker-that-returns-a-probability) Frequently Asked Questions ---------------------------- 3 questions Q01 What makes Jev different from a standard chat AI model in a Laravel app? Instead of returning a text response, Jev returns a probability score between 0 and 1 representing how likely the answer to a yes/no question is "yes". This makes the output directly usable in PHP conditionals without any text parsing. Q02 Do I need a special branch of the Laravel AI SDK to use Jev? No. The tutorial was originally recorded against a 1.x dev branch, but the Jev feature has since been merged into the main branch. A standard `composer require laravel/ai` install is sufficient. Q03 Can a high Jev probability score be treated as a definitive answer? No. The score reflects the model's confidence that the answer is "yes" — it is not proof the answer is correct. The course recommends routing borderline scores to a human reviewer rather than acting on them automatically. 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