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Strands Harness

Hacker News Top · 9h ago Cached

Introducing Strands harness, a new open-source agent harness that delivers frontier performance with 28% lower token cost compared to other harnesses like Claude Code, supporting multiple AI models and easy deployment.

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I open sourced 12M agentic decision examples for training Jev style models

Reddit r/artificial · 9h ago

The author has open-sourced Jev Decisions v1, a dataset of 12 million examples for training AI models on agentic decisions like tool selection and routing, to address data gaps in agent decision-making.

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@omarsar0: Just published a few ideas for using Jev and Pi to build a custom harness. This is the first of the series. Some of the…

X AI KOLs Timeline · 10h ago Cached

The author shares initial ideas for using Jev and Pi to build a custom harness, focusing on gates, routing, and verifiers, with plans for deeper exploration in follow-up posts.

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@omarsar0: https://x.com/omarsar0/status/2102762406204076532

X AI KOLs Following · 10h ago Cached

This article is a tutorial on building a custom AI agent harness using the Pi SDK and Jev, a small decision model for efficient tool call handling and checks in agent loops.

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Do not let your type system reason about aliasing in your programming language

Lobsters Hottest · 10h ago Cached

The article examines the complexities of aliasing in type systems for programming languages, using Futhark's in-place updates as an example, and warns about the design challenges it can introduce.

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I turned Qwen3.8-27B Q2_64 + llama.cpp into a fully TypeSafe AI-compatible Jev-like system. OpenAI API still intact! World’s first Vision-enabled Jev-like model! <10 GB VRAM, 170 ms on an RTX 3090 and ~140 tok/s in chat. 76% vs. 88% Jev-1.13 Acc. on a diverse 22,000-request typed-decision benchmark

Reddit r/LocalLLaMA · 10h ago

Bonsai-Llama-Jev is an open-source, vision-enabled typed-decision inference system that runs locally with low VRAM and high accuracy, outperforming other systems in a diverse benchmark.

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@heyshrutimishra: Competitor tracking is one of those tasks that's easy to skip because it's slow. I tested automating it with Qoder. The…

X AI KOLs Following · 10h ago Cached

A user tests the Qoder AI agent tool to automate competitor tracking, which plans research, runs parallel tasks, and compiles structured reports, while mentioning Qwen3.8-Flash and a promotional credit offer.

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@JenovaAIAgent: Survey Design Consultant is an AI agent that turns research objectives into bias-audited questionnaires you can actuall…

X AI KOLs Following · 11h ago Cached

Survey Design Consultant is an AI agent that converts research objectives into bias-audited questionnaires with item-level audits and validated instrument recommendations for defense-ready surveys.

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@PrajwalTomar_: GitHub: https://github.com/agentrhq/webcmd Works with Claude Code, Codex, Hermes, OpenCode, or any agent that can run t…

X AI KOLs Following · 11h ago Cached

Webcmd is a self-learning browser infrastructure for AI agents that learns website navigational contexts to reduce token spend and improve automation reliability.

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@PrajwalTomar_: Most browser agents are burning your tokens on mistakes they already made. Your browser agent has ZERO memory so every …

X AI KOLs Following · 11h ago Cached

WebCMD provides memory for browser agents like Chrome, saving site paths to avoid repeating mistakes and reducing token waste. It was tested on Reddit and ranked as the most accurate and cheapest per task in BU Bench V1.

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@JenovaAIAgent: Java Coding Assistant is an AI agent that helps you ship production-grade Spring, Jakarta EE, and JVM code — from green…

X AI KOLs Following · 11h ago Cached

Java Coding Assistant is an AI agent that helps developers ship production-grade Java code for Spring, Jakarta EE, and JVM systems, supporting Java 8–21 with features like session memory for consistency.

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@TeksEdge: Someone just made ordinary Qwen behave a LOT more like Jev without training a new model. TOP Jev Clone (according to HF…

X AI KOLs Timeline · 12h ago Cached

A new technique called JEVfire enables existing LLMs like Qwen to behave more like Jev by modifying decision-making processes without retraining, resulting in significantly faster JSON generation and enabling local AI agents to run efficiently on consumer hardware.

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@SamuelZengML: Speech recognition is easy—until you ask it to listen forever. Today we’re open-sourcing Audio8 ASR Infinite: Ultra-low…

X AI KOLs Following · 12h ago Cached

Open-sourcing Audio8 ASR Infinite, a speech recognition tool with ultra-low latency, unlimited audio support, 24/7 transcription, and built-in semantic turn detection, claimed to be new state-of-the-art for streaming ASR.

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GitHub - MatiwosKebede/OpenTrainDNN: OpenTrainDNN: A Browser-Based Real-Time Neural Network Visualizer

Reddit r/artificial · 13h ago Cached

OpenTrainDNN is an open-source, client-side web application that provides real-time visualization of deep neural network training, including backpropagation and weight updates, directly in the browser.

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Z80 REPL

Hacker News Top · 13h ago

A REPL environment for interacting with the Z80 microprocessor, likely used for development or emulation purposes.

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@neural_avb: Simply DSPy code to generate choice-based JEV decision training data from any raw text source Some of the newer models …

X AI KOLs Timeline · 13h ago Cached

This article describes using DSPy code to generate choice-based JEV decision training data from raw text, highlighting the cost-effectiveness with cheap models like gpt-6-luna and deepseek-v4.1-flash.

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Introducing MentalHealthBench

OpenAI Blog · 14h ago Cached

OpenAI introduces MentalHealthBench, an open benchmark for evaluating AI responses in mental health conversations, co-created with over 80 mental health experts to measure safety, context, agency, and guidance.

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@Saccc_c: Friends who are interested can check out the game production process:

X AI KOLs Following · 15h ago Cached

This article shares the workflow for creating a 3D game in Codex using GPT 6-Sol, highlighting the challenges in character modeling and large scene assets.

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A proxy that watches the yes/no and pick-one decisions your app asks an LLM for, then trains a local model to make them for free

Reddit r/artificial · 15h ago

Stuntd is an open-source local proxy that records LLM decision calls, trains a lightweight model to handle them locally, reducing costs while maintaining high agreement with the teacher model.

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@akshay_pachaar: Redis built a cache that cuts LLM costs by 70%! Production LLM apps often receive different versions of the same questi…

X AI KOLs Timeline · 16h ago Cached

Redis LangCache is a semantic caching tool that reduces LLM costs by up to 70% by storing and reusing similar question-response pairs, making AI applications faster and more cost-effective.

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