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Explores techniques used in production AI agents to avoid hallucinations when controlling real devices with multiple tools.
This article recommends Thoughtworks Technology Radar, a tech resource updated every six months containing assessments of technologies, tools, platforms, languages, and frameworks, categorized into four rings: Adopt, Trial, Assess, Hold.
OpenAI published a 34-page guide on building AI agents, emphasizing that an agent is essentially a loop: run the model, call a tool, feed back results, repeat until an exit condition. The guide covers tools, guardrails, and starting with a single loop before scaling to multiple agents.
A tweet announcing an open-source UI/UX for building organization-level agent harnesses, allowing users to bring their own model and runtime and integrate with their tools.
Lyto is an AI agent that operates across your browser, tools, and messages, aiming to unify workflows.
An observation that future technologies often start as seemingly trivial toys before evolving into foundational infrastructure for civilization.
User recommends Feishu as the strongest office tool in China and shares how to combine Codex and Feishu for knowledge management, content creation, and topic planning to improve efficiency.
Explores the idea that AI's true impact is not replacing jobs but scaling expertise by removing bottlenecks, citing tools like Perplexity, GitHub Copilot, and Rilla.
Executor, an open-source MCP gateway that connects AI agents to various services, announces its YC S26 batch joining and highlights recent milestones including 2,000 GitHub stars and multiple feature releases.
10 design reference websites to help AI enhance its aesthetic sense for AI-generated content.
A speculative article discussing what tools and infrastructure would be necessary if most people interact with digital services through AI agents instead of directly.
Modal explains the complexities of building performant sandbox systems beyond initial container boot and shares tools for lifecycle management.
This article explains the concept of loop engineering in AI agents, emphasizing that the core loop is trivial but the critical work lies in the harness around the model, including knowing when to stop and preventing context rot.
Bluerails Discovery provides infrastructure for AI agents to find and pay users.
Introduces the combined use ideas of five free and open-source OSINT tools (Blackbird, Maigret, SpiderFoot, theHarvester, Shodan Python), covering scenarios such as people search, company search, device search, and provides practical cases and installation methods.
Introduces multiple web scraping tools, including yt-dlp, FxTwitter, get笔记, etc., for scraping content from different platforms.
Introduces the Awesome LLM Interpretability resource collection, which gathers various interpretability tools, papers, and community resources to help understand the internal workings of large language models.
A curated list of prompt engineering resources including papers, tools, courses, and communities for working with large language models, maintained by PromptSlab.
Bcachefs-Tools 1.38.6 has been released with many performance improvements including lockless journal flushes, btree optimizations, and improved sharding. It also supports up to 255 storage devices per filesystem and offers Ubuntu 26.04 LTS packages.
The article discusses the concept of adding a network layer to AI agents, building on existing tools and vector stores to enable better coordination and communication among agents.