53 summarised stories about Agent Frameworks, each linking back to the original source. Browse all topics →
OpenAI 9 months ago 42
A Practical Guide to Building AI Agents provides guidance on designing, orchestrating, and deploying AI agents. It covers model selection, tool design, guardrails, and multi-agent patterns. As a result, readers get a structured checklist-style approach rather than an implemented system or measured performance change.
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TLDRocket
20 October 2026
AI infrastructure is getting a very practical second act today: making agents faster to start, cheaper to run, and easier to govern once they’re running. Daytona, which sells an “agentic cloud” built around VMs for agent “computers,” raised $60 million in a Series B and landed at a $1 billion valuation, targeting 60-millisecond sandbox provisioning—an attempt to knock down the latency tax that makes agents feel sluggish between steps. IBM, Red Hat, and others also pushed llm-d framework 1.0, adding operational controls for in-house distributed inference, including multi-tenant QoS, zero-downtime upgrades, and router behavior measured on an agentic coding test that reportedly captured 97% cache reuse.
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