Walid Ladeb

smart programmable routing with jev as a brain!

Introducing Jev @typesafeai powered people-search Just $0.0089/lead, No more $600 subscriptions, Try it at treg.to/people-search - 85% cheaper than Clay - #1 on people search bench accuracy - Plugin to any agent to find anyone Fully open source, 0% markup Git Repo below 👇

Jev as a judge for LLM evals! JevEval uses Jev as the judge for custom LLM evals instead of relying on another generative LLM for every evaluation. The idea is pretty simple. You define the exact decisions you want the evaluator to make, Jev evaluates each one and returns probabilities, and DeepEval uses those results to calculate the final score. For example, with an AI agent you can evaluate the trace itself, checking whether the agent selected the right tools, followed the expected sequence of actions, and actually completed the task. Jev handles those semantic judgments, while the scoring logic stays outside the model. That is the main difference from a normal LLM-as-a-judge setup. With a generative judge, the model often has to interpret the rubric, reason about the response, and generate the evaluation itself. With JevEval, you define the decision structure upfront. You can also assign different weights to different checks or use `strict_mode` when every requirement needs to pass. So if one part of the agent workflow matters more than another, you can reflect that directly in the scoring logic instead of leaving the entire evaluation to the judge model. Key capabilities: - Evaluate agent outputs and traces with Jev - Define custom checks as bounded decisions - Use yes/no, score, and closed-choice questions - Weight different checks or require all of them to pass - Evaluate both single-turn outputs and multi-turn conversations This is where Jev makes a lot of sense for evals. If you already know what needs to be checked, you can define those decisions upfront, let Jev handle the semantic judgment, and keep the final scoring deterministic. I’ve shared the DeepEval post in the comments.

introducing muse wonder our new frontier model. state-of-the-art at personal agents and professional agents. our largest and most capable model yet—rivals the big bois

Replacing LLM calls with deterministic code is a no brainer and also results in better code that better matches what users want

say it with me: a jev in every home

We're excited to introduce OrcaCyber Zero 1.5 — our latest frontier cybersecurity model, built to discover critical vulnerabilities, investigate complex attack paths, and validate real-world exploitability. Updated weights. New benchmark results: • 95.8% — CVE-Bench (23/24 evaluable tasks) • 100% — Cybench (39/39, unrestricted) • 93.9% — HumanEval+ Its predecessor, OrcaCyber Zero 1.0, has already helped protect some of the world's largest software companies, governments, blockchain networks, and cybersecurity firms from real-world threats. It also powered our autonomous OrcaCyber harness, which achieved 98%+ pass@1 on CyberGym, ranking among the top 3 globally. What's different about OrcaCyber Zero 1.5? 🔹 Find what others miss. Designed to uncover previously unknown vulnerabilities, including RCE, sandbox escapes, authentication bypasses, privilege escalation, and complex attack chains. 🔹 Go beyond detection. Reasons through attack paths, challenges its own hypotheses, and prioritizes vulnerabilities with demonstrable exploitability and real-world impact. 🔹 Built for autonomous security agents. 1M-token context window, native tool calling, and extended reasoning to investigate large codebases and complex attack surfaces. The goal isn't more vulnerability reports. It's more real vulnerabilities discovered, validated, and fixed before attackers exploit them. Available now exclusively on OrcaRouter: orcarouter.ai/models/orca/or…

Dear Prime Minister Ambani, Please accept my humble apologies for not realizing that you are the real boss of India. Naturally, you would prefer to maintain your monopolistic exploitation of the great people of India, but would you nonetheless consider allowing Starlink to compete? There are many areas of India, as there are in all countries, with no Internet access, which denies children the opportunity for education and for small businesses the opportunity to sell their goods to a global market. Starlink would change their lives for the better. Thank you 🙏

We’re so excited to announce that we’re leading TypeSafe AI's Series A: "Like @TypeSafeAI, we believe the future of SaaS and software is bright. And AI should make software more powerful, and not just automate the recreation of existing software. This spiritual alignment goes back many years. We’ve long been fans of Diogo, the founder and CEO of TypeSafe, and have resonated strongly with his vision that the true bitter lesson is not necessarily about building a new being, but returning the power to builders by giving them the primitives of intelligence then letting them unleash their imagination. The entire a16z team is excited to partner with TypeSafe. Software continues to eat the world." By @JenniferHli, @sarahdingwang, @martin_casado, @pmarca, and @bhorowitz

launched a model accidentally served trillions of tokens a day 29.4% of the fortune 500 showed up raised a really big series A from @a16z it's been 3 weeks we would like to sleep now