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Feature
Harness Design for Coding Agents: New Approaches to AI Infrastructure
An empirical study reveals key insights into designing effective harnesses for long-running coding agents, highlighting both potential and pitfalls.
Why it mattersAgent infrastructure is evolving with advanced harness designs that promise efficiency but also pose new risks. Developers face challenges in ensuring these systems enhance productivity without compromising security or reliability.
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Each morning: models, tools, research, and conversations distilled from across the web — with why they matter for builders.
Around the Web
Coding Agents Gone Wild
Top Hacker News discussion.
techcrunch
AI Missteps and Guardrails
Top Hacker News discussion.
cnn
Recent Reddit discussion.
r/nocode
Tools
Trending AI model on Hugging Face — sentence-similarity.
🤗huggingface
Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
github | stars 141,917
为 DeepSeek Harness (DSH) 插件生态打造的现代化桌面端解决方案。万物皆「插件」，桌面本身也是「插件」。
github | stars 27,574
Build
In this article, we’re going to look at how this embedding model works in an RAG setup and what makes it such a critical part of the system.
blog.bytebytego
Why generative AI won't create 10x developers
thoughtworks
From specification to production: Building enterprise software with agentic AI
thoughtworks
Research
Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a framework that uses Logit Lens convergence and causal head-level att…
arxiv
Large language model responses are non-deterministic, so failures in LLM agents are hard to reproduce: a failure depends on inference that is not bitwise reproducible, on tools that read changing state, and on a multi-s…
arxiv
Frontier AI models are rapidly gaining the ability to exploit vulnerabilities in complex pieces of software. The risk is not theoretical, as evidenced by recent sandbox escapes performed by frontier models at OpenAI and…
arxiv
Playbooks
What is Jev? Learn how TypeSafe AI’s System One model makes fast, structured decisions, where it fits in the agent loop, and how to use Jev with LangChain
langchain
Harness design is key to performance at the frontier of agentic coding. Here's how we pushed Claude further in frontend design and long-running autonomous software engineering.
anthropic
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hamel
News
Migrate a multi-model healthcare AI agent from self-managed Amazon ECS with AWS Fargate to Amazon Bedrock AgentCore runtime, preserving triple-model orchestration and vector-enhanced knowledge retrieval while reducing i…
aws.amazon
Deploy production-ready Hugging Face models on Amazon SageMaker AI using six open-source agent skills. Point a coding agent at a model and get back a real-time endpoint with the right serving container, autoscaling, Ama…
aws.amazon
Understanding agent orchestration economics, model capability thresholds, token burn rates, and structural failure modes.
yegge