Posting peluncuran Jev
Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
Yang terbaik dari Jev: proyek nyata, panduan praktis, dan ide dari seluruh internet.
Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
Pengumuman peluncuran resmi TypeSafe memperkenalkan laboratorium dan mengarahkan pengembang ke Jev. Termasuk film peluncuran Diogo Almeida dan pengantar asli.
TypeSafe mengumumkan akses publik ke Jev tanpa daftar tunggu. Konsol resmi adalah titik awal untuk mencoba keputusan bertipe dalam aplikasi Anda sendiri.
TypeSafe menyoroti pendekatan Jev untuk output bertipe: aplikasi menyediakan state dan pertanyaan, lalu bertindak berdasarkan probabilitas, pilihan, atau skor. Pengumuman terkait juga mencakup integrasi API Venice.
Start with the Launch Post. Explore four official signals.
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AI-assisted summaries and translations. Check original sources for context and performance claims.
Agens Jev yang sangat cepat untuk penggunaan browser: Jev memilih operasi dan elemen DOM dalam satu permintaan; LLM kecil hanya menulis teks saat pengetikan diperlukan.
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Plugin Claude Code yang mengganti ringkasan kompaksi dengan keputusan Jev: setiap panggilan alat dan hasilnya dinilai dalam satu permintaan cepat, yang kedaluwarsa dihapus atau dipotong, semua yang disimpan tetap dalam bentuk asli.
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A skill for writing and improving programs that call Jev, TypeSafe's System One model.
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A Jev powered LinkedIn recruiting agent. Watch it browse relevant profiles, save links, and review evidence against your hiring brief.
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Testing Jev as a search reranker shows limited improvement over vector retrieval, with mixed results depending on evaluation methods.
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A YouTube guide explaining Jev's functionality, including browser use, classification, and code review without an LLM.

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A developer project for agent-native routing that selects models based on task complexity.
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Go CLI and single-binary MCP server exposing TypeSafe judgments to Claude Desktop, Claude Code, and Codex.
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One grounded Jev/Playwright core: typed SDK, persistent CLI, and MCP server with native browser operations and deterministic assertions.
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Ultra-fast model routing using Jev for agent-based systems.
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A community post describing 500 real-time agents operating in a 3D environment with notable performance metrics.
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A prose linter that sniffs out AI writing tells. Zero dependencies, countable rules plus one judgment model.
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Jev controls both hands and fingers to play piano in real-time based on visual input.
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Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.
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Standalone Android agent for Mobilerun where Jev makes every decision, with a live React studio and an Uber demo.
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Explains Jev's role in automating decision-making processes and enabling new business models through efficient task sorting and classification.
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An agent using headless Chromium to quickly navigate the web, demonstrated by browsing Wikipedia links efficiently.
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An experiment using Jev to interpret voice commands and trigger tool actions before the user finishes speaking.
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A developer project using Jev for plain-language MCP tool calls without an LLM.
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OCR layar, klasifikasikan tindakan berikutnya dengan TypeSafe, lalu klik. macOS.
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A developer project providing a local MCP server for running pre-made Jev question packs.
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A moderation system for Mastra agents that processes inputs in a single file.
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Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell.
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A guide explaining how to integrate Jev with Pydantic AI agents for type-safe operations.
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A community post describes a plugin that manages agent context by analyzing and pruning unnecessary data, available in Spanish.
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Jev was integrated with Claude Code to address context compaction challenges in agent workflows, showing promising results.
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A developer project where Jev assists in browsing by selecting actions, with an LLM planning and citing sources.
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Typed, confidence-aware agent skill routing with TypeSafe Jev.
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Write Cucumber tests with just the .feature file. No step definitions — Jev (TypeSafe AI) resolves each Gherkin step and Playwright runs it.
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A system using Jev to interact with computer interfaces without screenshots, relying on local CoreML models and OCR.
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Daf-jev: composable Python toolkit for TypeSafe's Jev (System One) decision API — question builders, confidence gates, evaluator, calibration, CLI, MCP server, agent skill.
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A Chrome extension enabling agents to browse and interact with websites, utilizing Jev for decision-making.
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A social media feed optimized using user bookmarks and Jev's analysis.
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A community post testing Jev's performance in a browser environment, noting limitations after five actions.
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Jev achieved 100% task success on the WebMCP benchmark with significantly lower model costs compared to other systems, using a combination of tool selection and argument generation.
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A GitHub project converting agent skills into Oxlint plugins that involve Jev.
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Systematic software development framework for AI coding agents upgraded with TypeSafe Jev System One typed decisions.
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A log analysis tool that groups 22.8M lines into patterns and uses Jev to review key patterns.
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A community experiment using Jev as a plugin in Claude to reduce unnecessary tool calls, cutting token count from 1M to 86K.
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A community post suggests Jev accelerates computer use, claiming 100x faster processing than standard LLMs.
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Control a real browser by voice. Jev (TypeSafe System One) decides intent + target in ~300 ms per spoken word; Playwright acts — often before you finish the sentence.
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Jev-Tool-Runner is a GitHub project where Jev selects developer tools and Codex generates code based on those selections.
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Test report using Jev to check each agent action first: most attacks caught, almost no false blocks.
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AgentRun leverages Jev for creating self-sufficient agent workflows.
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A plugin using Jev's scoring capability to remove unnecessary terminal garbage and redundant logs, improving agent performance.
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Jev analyzes outreach messages to identify signals that lead to booked demos, improving campaign performance.
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Reduces SEO and GEO fix costs by 90% through faster data analysis and automation.
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Agent Skill: send closed coding-agent judgments to TypeSafe Jev.
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A community post discussing Jev's use in enforcing coding rules that linters cannot handle.
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Reduces context usage by 30-55% through Jev-based compaction for OMP agents.
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A community post providing a tutorial on Jev, including demos for browser control and AI memory.
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A YouTube guide explores using Jev within an agentic coding loop, focusing on cost efficiency for development tasks.

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A system enabling rapid agent deployment on digital canvases without relying on slow LLM processes.
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A calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.
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A developer project offering semantic code search for coding agents, benchmarked on SWE-bench Lite.
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A community project enabling hands-free web navigation by having Jev handle browser actions while Claude manages conversation.
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A community project describes an agent system that uses Jev to route requests to appropriate models.
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Agent skill: design judgment-assisted systems with TypeSafe Jev (System One). Maps Choice/Score/Noul onto decision theory, reranking, and routing. Composition algebra, question design, validation gates. MIT.
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An experiment using Jev for real-time model selection in AI agents, collected for the agents shelf.
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Detects low-quality content in real-time as users scroll.
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Per-call GPT model routing for Codex: Jev chooses model and effort, a local Responses proxy keeps the tool loop intact, then independent verification and Router Compass check whether the task still passed.
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Browser extension that reads the YouTube caption track and paints a per-segment sponsor probability on the seek bar before the intro ends, with no crowd database.
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Tutorial covers API setup and building prototypes with Jev and LLMs.

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Browser game: try to beat Jev at spotting a spam message.
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Browser-only playground for Jev (TypeSafe AI's decision model) via Vercel AI Gateway.
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Hand the browser work off: an MCP server where a decision model drives the page for your agent, so a flow costs one tool call instead of a turn per click. Ref-based element tables, code-checked assertions, zero-model macro replay. Speaks CDP to your Chrome.
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Decision layer for coding agents: deterministic rules before any model call, then one Jev request, as a Claude Code PreToolUse hook, an MCP server, a loopback service and a team policy that personal overrides can tighten but not loosen. Ships the 300-call injection kit behind its own numbers.
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Route to the cheapest model in claude code for your task using jev-router.
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Agent-first Haskell DSL for TypeSafe's Jev judgment model: typed packets, inferred types, answers under the same labels.
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Retrieve by relevance, not resemblance: filter an AI assistant's memories with TypeSafe's Jev.
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Jev handles seven SEO and GEO workflows, including competitor page analysis, citation likelihood, and content optimization.
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TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers.
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