Jev is a new “System One” AI model released by TypeSafe AI. It is designed for fast, structured decision-making rather than human-facing text generation. Instead of outputting words, it returns structured signals such as scores, probabilities, codes, or decisions for software to act on. What is Jev? How Jev works How it differs from RLHF-based […]
Read More →Picture a warehouse stocked with every power tool ever made. Now picture the lights off, no labels, and no inventory list. That’s roughly where AI assistants are today. Modern AI clients like Claude, ChatGPT, Copilot, and Gemini aren’t limited to what the model knows anymore. They can plug into external tools, MCP servers, APIs, Skills, […]
Read More →Based on “5 things every AI engineer should know about agent sandboxes” by Ryan Ismert and Alan Blount of Google Cloud Tech (September 2026). Table of Contents Imagine hiring a brilliant intern who works at lightning speed, never sleeps, and occasionally does something completely unpredictable. Now imagine giving that intern the keys to your entire […]
Read More →The Wiggle Framework is an evaluation method introduced in Meta’s research paper, “Jagged Judges: Epistemic Stability Under Perturbation.” It is designed to test how easily large language model (LLM) judges abandon their original verdicts when challenged. Why this matters Traditional LLM evaluation often measures a judge’s accuracy once against a fixed gold-standard dataset. That tells us how […]
Read More →Imagine hiring a brilliant assistant, handing them a 200-page manual, and asking a question. They read all 200 pages, answer, and then promptly forget everything. Next question? They read all 200 pages again. And you pay them by the page. That’s roughly how large language models (LLMs) work by default. Prompt caching is the fix. […]
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