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      <title>Mixture of Agents: Why Hermes 0.6 Beats Single Models</title>
      <link>https://aiagentsnews.top/posts/mixture-of-agents-why-hermes-06-beats-single-models/</link>
      <pubDate>Sun, 19 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/mixture-of-agents-why-hermes-06-beats-single-models/</guid>
      <description>Hermes 0.6 uses parallel reference models to isolate reasoning from tool use, preventing hallucinated actions while improving decision quality.</description>
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      <title>Inference latency: Why 41B active beats 975B</title>
      <link>https://aiagentsnews.top/posts/inference-latency-why-41b-active-beats-975b/</link>
      <pubDate>Thu, 16 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/inference-latency-why-41b-active-beats-975b/</guid>
      <description>Learn why 41B active parameters matter more than total count for agent latency. Discover selection criteria for reliable, cost-effective systems.</description>
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      <title>Agent runtime rules: boost scores by 14 points</title>
      <link>https://aiagentsnews.top/posts/agent-runtime-rules-boost-scores-by-14-points/</link>
      <pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/agent-runtime-rules-boost-scores-by-14-points/</guid>
      <description>See how SelfUse jumped TerminalBench scores from 23.8% to 38.1% by mining execution traces instead of tweaking model weights manually.</description>
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      <title>LangChain custom tools: stop LLM guessing now</title>
      <link>https://aiagentsnews.top/posts/langchain-custom-tools-stop-llm-guessing-now/</link>
      <pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/langchain-custom-tools-stop-llm-guessing-now/</guid>
      <description>Learn to build a CircumferenceTool in LangChain. This guide shows how custom tools replace token-based guessing with grounded, repeatable functions.</description>
    </item>
    <item>
      <title>Native interaction models: why 0.4s latency matters</title>
      <link>https://aiagentsnews.top/posts/native-interaction-models-why-04s-latency-matters/</link>
      <pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/native-interaction-models-why-04s-latency-matters/</guid>
      <description>Thinking Machines&#39; native interaction models hit 0.40s latency, outpacing GPT-realtime2&#39;s 1.18s for concurrent audio and text streams.</description>
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    <item>
      <title>Orchestrator-worker pattern cuts AI costs 10x</title>
      <link>https://aiagentsnews.top/posts/orchestrator-worker-pattern-cuts-ai-costs-10x/</link>
      <pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/orchestrator-worker-pattern-cuts-ai-costs-10x/</guid>
      <description>Splitting orchestration from execution can cut inference costs by around 10x. Learn how the orchestrator-worker pattern separates planning from routine tasks.</description>
    </item>
    <item>
      <title>Agentic AI 2026: Free Tools That Execute Tasks</title>
      <link>https://aiagentsnews.top/posts/agentic-ai-2026-free-tools-that-execute-tasks/</link>
      <pubDate>Wed, 08 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/agentic-ai-2026-free-tools-that-execute-tasks/</guid>
      <description>Perplexity removed Comet&#39;s paywall in March 2026. Explore free agentic tools that decompose goals and execute sequences without human prompts.</description>
    </item>
    <item>
      <title>TerminalBench v2.1: 89 Tasks for Real Agent Mastery</title>
      <link>https://aiagentsnews.top/posts/terminalbench-v21-89-tasks-for-real-agent-mastery/</link>
      <pubDate>Tue, 07 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/terminalbench-v21-89-tasks-for-real-agent-mastery/</guid>
      <description>TerminalBench v2.1 uses 89 curated tasks to test if AI agents can execute complex system commands rather than just generating static code snippets.</description>
    </item>
    <item>
      <title>Agent frameworks compared: LangGraph 0.2&#43; vs CrewAI 0.86&#43;</title>
      <link>https://aiagentsnews.top/posts/agent-frameworks-compared-langgraph-02-vs-crewai-086/</link>
      <pubDate>Mon, 06 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/agent-frameworks-compared-langgraph-02-vs-crewai-086/</guid>
      <description>Gartner predicts 40% of enterprise apps will use task-specific agents by 2027. Compare how LangGraph and CrewAI handle this complex shift.</description>
    </item>
    <item>
      <title>Hermes Agent models: Sonnet 4.6 vs DeepSeek V4</title>
      <link>https://aiagentsnews.top/posts/hermes-agent-models-sonnet-46-vs-deepseek-v4/</link>
      <pubDate>Sun, 05 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/hermes-agent-models-sonnet-46-vs-deepseek-v4/</guid>
      <description>Compare Claude Sonnet 4.6 ($3) against DeepSeek V4 ($0.30) for Hermes Agent. Learn which model prevents malformed tool calls in production.</description>
    </item>
    <item>
      <title>React agents vs function calling: 2026 guide</title>
      <link>https://aiagentsnews.top/posts/react-agents-vs-function-calling-2026-guide/</link>
      <pubDate>Sun, 05 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/react-agents-vs-function-calling-2026-guide/</guid>
      <description>Compare ReAct&#39;s iterative reasoning loops against structured function calling for external API access in 2026 agent architectures.</description>
    </item>
    <item>
      <title>Agent tools that enable action, not just chat</title>
      <link>https://aiagentsnews.top/posts/agent-tools-that-enable-action-not-just-chat/</link>
      <pubDate>Sat, 04 Jul 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/agent-tools-that-enable-action-not-just-chat/</guid>
      <description>Late 2025 data shows action-enabling tools are now the majority use case. Learn how nine specific tool categories prevent context window overload.</description>
    </item>
    <item>
      <title>Local coding agents: Build free private stacks</title>
      <link>https://aiagentsnews.top/posts/local-coding-agents-build-free-private-stacks/</link>
      <pubDate>Mon, 29 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/local-coding-agents-build-free-private-stacks/</guid>
      <description>Skip the $7.60 per task fee. I show how to run Qwen3.6 locally on 32GB RAM for private, zero-cost code generation.</description>
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    <item>
      <title>TerminalBench 2.1 exposes agent wrapper gaps</title>
      <link>https://aiagentsnews.top/posts/terminalbench-21-exposes-agent-wrapper-gaps/</link>
      <pubDate>Sun, 28 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/terminalbench-21-exposes-agent-wrapper-gaps/</guid>
      <description>Codex CLI paired with GPT-5.5 sits at the top of the Terminal-Bench 2.1 leaderboard with an 83.4% pass rate.</description>
    </item>
    <item>
      <title>LlamaIndex agents: connect live data sources</title>
      <link>https://aiagentsnews.top/posts/llamaindex-agents-connect-live-data-sources/</link>
      <pubDate>Fri, 26 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/llamaindex-agents-connect-live-data-sources/</guid>
      <description>Learn how LlamaIndex uses over 200 data loaders to connect static LLMs to live enterprise sources and bypass training cutoffs.</description>
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    <item>
      <title>GLM5.2 model: openweight coding performance data</title>
      <link>https://aiagentsnews.top/posts/glm52-performance-rivals-closed-coding-models/</link>
      <pubDate>Tue, 23 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/glm52-performance-rivals-closed-coding-models/</guid>
      <description>GLM-5.2 improved internal task success rates from 21/70 to 48/70 over its predecessor, signaling a shift in open-weight viability.</description>
    </item>
    <item>
      <title>Frontier code surge: Anthropic&#39;s 2026 self-improvement risks</title>
      <link>https://aiagentsnews.top/posts/recursive-improvement-risks-anthropics-2026-code-surge/</link>
      <pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/recursive-improvement-risks-anthropics-2026-code-surge/</guid>
      <description>Anthropic reports an 80-fold revenue surge in 2026 as recursive self-improvement accelerates, raising urgent questions about frontier safety protocols.</description>
    </item>
    <item>
      <title>MAI models: Microsoft&#39;s 35B reasoning engine explained</title>
      <link>https://aiagentsnews.top/posts/mai-models-microsofts-35b-reasoning-engine-explained/</link>
      <pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/mai-models-microsofts-35b-reasoning-engine-explained/</guid>
      <description>Microsoft&#39;s MAI-Thinking1 uses 35B active parameters within a 1T-parameter MoE to cut costs while handling 256K context windows for complex reasoning.</description>
    </item>
    <item>
      <title>Ollama models: Stop AI ghostwriting on Windows</title>
      <link>https://aiagentsnews.top/posts/ollama-models-stop-ai-ghostwriting-on-windows/</link>
      <pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/ollama-models-stop-ai-ghostwriting-on-windows/</guid>
      <description>Shift from ghostwriting to coaching with Ollama on Windows. This guide details a 100% offline workflow that keeps sensitive data secure.</description>
    </item>
    <item>
      <title>Prompt engineering beats trial and error for LLMs</title>
      <link>https://aiagentsnews.top/posts/prompt-patterns-beat-trial-and-error-for-llms/</link>
      <pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/prompt-patterns-beat-trial-and-error-for-llms/</guid>
      <description>Stop iterative guessing by applying a strict 5-block prompt architecture that shifts probabilistic model outputs toward accurate, stable results.</description>
    </item>
    <item>
      <title>Small LLM on Intel i5: 36 Tokens/Second Reality</title>
      <link>https://aiagentsnews.top/posts/small-llm-on-intel-i5-36-tokenssecond-reality/</link>
      <pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate>
      <author>AI Agents News Editorial</author>
      <guid>https://aiagentsnews.top/posts/small-llm-on-intel-i5-36-tokenssecond-reality/</guid>
      <description>Testing five models on an Intel i5 reveals 36 tokens per second is the ceiling for small LLMs due to 20 GB/s memory bandwidth limits.</description>
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