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  • Why Your Agent Probably Needs Skills

    Kiln has added agent skills support! Here's what skills are, why progressive disclosure works, and how to use them in your agents.

    Kiln Blog3 min read

  • Introducing Mothership

    Sim v0.6 introduces Mothership—a central intelligence layer for orchestrating your AI agents—alongside Tables, Files, Knowledge Base Connectors, and Scheduled Tasks.

    Sim Blog8 min read

  • Multimodal Search with Gemini Embedding 2 in Haystack

    Embeddings are the backbone of modern AI applications, from semantic search and recommendation systems to Retrieval-Augmented Generation (RAG). However, most embedding models operate in a single modality, typically focusing only on textual data.

    Haystack Blog7 min read

  • Your Team Works Hard. So Why Is Productivity Still Falling?

    How to Increase Employee Productivity? When a startup grows and brings in talented people, it should move faster. However, the reality is often the opposite. Yet with more people and stronger skills on the team, decisions slow down and communication starts to break.

    Refinder AI Blog5 min read

  • GPT-5.4: OpenAI's RAG Regression

    OpenAI released GPT-5.4 with a Pro variant for extended reasoning. We tested both on our LLM-for-RAG leaderboard across three workloads.

    Agentset.ai Blog1 min read

  • Top Alternatives to LibreChat

    LibreChat has quickly become a favorite for developers and technical teams who want a self‑hosted, open‑source chat UI that can sit in front of multiple LLMs. It gives you flexibility and control without per‑seat SaaS pricing.

    AICamp Blog11 min read

  • Claude Sonnet 4.6 for RAG

    We evaluated Claude Sonnet 4.6 in a RAG setup across factual retrieval, synthesis, and scientific tasks compared to frontier models.

    Agentset.ai Blog1 min read

  • Voyage 4: Evaluation Notes

    We tested Gemini 3 inside an actual retrieval setup and compared it directly with GPT-5.1 across five areas that matter for RAG.

    Agentset.ai Blog1 min read

  • Claude Opus 4.6 Performance in RAG

    We evaluated Claude Opus 4.6 in a RAG setup across factual retrieval, synthesis, and scientific tasks versus 11 frontier models.

    Agentset.ai Blog1 min read

  • Context Blindness: A Fundamental Limitation of Vector RAG

    We argue that context blindness — the inability of vector-based retrieval to condition on full conversational and reasoning context — is a fundamental limitation of vector RAG, and outline a paradigm shift from semantic similarity to context-dependent relevance classification.

    PageIndex Blog6 min read

  • Introducing Sim v0.5

    This new release brings a state of the art Copilot, seamless MCP server and tool deployment, 100+ integrations with 300+ tools, comprehensive execution logs, and realtime collaboration—built for teams shipping AI agents in production.

    Sim Blog9 min read

  • Gemini 3 Flash: A strong factual RAG model

    We evaluated Gemini 3 Flash in a RAG setup to understand where it excels and where it falls short—focusing on factual retrieval and grounding.

    Agentset.ai Blog1 min read

  • RAG for Technical Manuals

    How PageIndex’s vectorless, reasoning-based RAG overcomes the challenges of traditional vector RAG in long, complex technical manuals.

    PageIndex Blog12 min read

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