<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>AgentDaily</title><link>https://agentdaily.si/</link><description>AI agents, explained for the work ahead.</description><language>en</language><item><title>LFM2.5-24B-A2B: what to check before running a local agent</title><link>https://agentdaily.si/articles/liquid-ai-local-agents-release/</link><guid isPermaLink="true">https://agentdaily.si/articles/liquid-ai-local-agents-release/</guid><description>Liquid AI’s October release gives local-agent builders another model to evaluate. Check the checkpoint, workload and usage conditions before interpreting its benchmark scores.</description><category>AI</category><pubDate>Wed, 21 Oct 2026 01:14:10 GMT</pubDate></item><item><title>Google Antigravity surfaces an antimicrobial candidate for laboratory validation</title><link>https://agentdaily.si/articles/antigravity-science-candidate-evidence/</link><guid isPermaLink="true">https://agentdaily.si/articles/antigravity-science-candidate-evidence/</guid><description>Google’s October walkthrough follows a researcher from protein searches to a candidate for experimental investigation. The useful question is which evidence supports each step.</description><category>Research</category><pubDate>Wed, 21 Oct 2026 01:14:10 GMT</pubDate></item><item><title>MCP or A2A? Choose by the work crossing the boundary</title><link>https://agentdaily.si/articles/mcp-a2a-agent-boundaries/</link><guid isPermaLink="true">https://agentdaily.si/articles/mcp-a2a-agent-boundaries/</guid><description>A tool operation and an independent agent collaboration expose different responsibilities. Map the service first, then check the protocol version and implementation.</description><category>Agents</category><pubDate>Wed, 21 Oct 2026 01:14:10 GMT</pubDate></item><item><title>How to evaluate an agent beyond its best demo</title><link>https://agentdaily.si/articles/read-agent-evaluations/</link><guid isPermaLink="true">https://agentdaily.si/articles/read-agent-evaluations/</guid><description>Define the final outcome, preserve failed attempts and measure correction effort. A synthetic invoice example shows how to turn that advice into a usable evaluation.</description><category>Agents</category><pubDate>Wed, 21 Oct 2026 01:14:10 GMT</pubDate></item><item><title>Computer-use agents need checks before every consequential action</title><link>https://agentdaily.si/articles/computer-use-permission-boundaries/</link><guid isPermaLink="true">https://agentdaily.si/articles/computer-use-permission-boundaries/</guid><description>One model response can contain several desktop actions. The integrating application decides how to execute the sequence and where a human decision is required.</description><category>AI</category><pubDate>Wed, 21 Oct 2026 01:14:10 GMT</pubDate></item><item><title>How to read METR’s AI task-completion time horizons</title><link>https://agentdaily.si/articles/what-ai-time-horizons-measure/</link><guid isPermaLink="true">https://agentdaily.si/articles/what-ai-time-horizons-measure/</guid><description>The duration uses a human baseline to describe task difficulty. Reliability, task selection and the dashboard’s update status determine what the chart can support.</description><category>Research</category><pubDate>Wed, 21 Oct 2026 01:14:10 GMT</pubDate></item></channel></rss>
