156 summarised stories about Agent Orchestration, each linking back to the original source. Browse all topics →
Product Hunt 1 month ago 18
Sierra launched its multimodal agents, letting a single customer-conversation agent switch among voice, text, and visuals. The release is Sierra’s 2nd launch and it’s launching today. As a result, the agent can automatically shift communication modes based on what the conversation needs instead of relying on one input type.
monday AI engineering 1 month ago 50 ● 2 sources
monday.com described how it built a production harness for its feedAgent to prevent AI agent failures across data/context, the agent flow, and the feedback loop. The article says it used recursion and model call limits (with exitBehavior set to end) to cap loop iterations and stop runs safely. As a result, the agent’s inputs are token-limited and PII-removed, outputs must match a validated schema, hallucinated or non-resolving activity citations are filtered, and behavior from user interactions feeds back into future runs via an explicit-plus-inferred rules loop.
Product Hunt 1 month ago 3
Twigg launched as a stateful API for interacting with LLMs by creating a chat once and sending only the next event per request. The platform includes a Dashboard that lets you control tool schemas, system prompts, and context windows. This removes the need for developers to manage and host conversation context themselves, since Twigg fits, compacts, truncates, and routes calls to the target model.
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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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