17:[[47676157,{"by":"bnchrch","descendants":11,"id":47676157,"kids":[47676224,47729230,47688353,47681230,47676452,47765673,47676528,47684757,47679097],"score":40,"time":1775572818,"title":"Show HN: Output.ai - OSS framework we extracted from 500+ production AI agents","type":"story","url":"https://output.ai/"}],[47675213,{"by":"timbilt","descendants":62,"id":47675213,"kids":[47678771,47680281,47827027,47685930,47678103,47680883,47729205,47686524,47678974,47687573,47678956,47678729,47678593,47687905,47677768,47679854,47681622,47678369,47679300,47681522,47710189,47677763,47687030,47679071,47679962,47678683,47678661,47681564,47678978,47681247,47679200,47680403],"score":230,"text":"https://googlecloudplatform.github.io/scion/overview/","time":1775569155,"title":"Google open-sources experimental agent orchestration testbed Scion","type":"story","url":"https://www.infoq.com/news/2026/04/google-agent-testbed-scion/"}],[47349510,{"by":"yanitcorel","descendants":1,"id":47349510,"kids":[47376642,47349896,47353139],"score":1,"text":"Many AI agent demos work well in prototypes but break when moved to production.

We’ve been exploring how teams are running agentic AI systems reliably on AWS, including orchestration, scaling, monitoring, and guardrails.

We’re hosting a live technical masterclass where we’ll walk through architectures and real-world patterns used in production environments.

If this topic is useful for engineers here, they can join the session.

Event link - https://www.netcomlearning.com/webinar/productionizing-agentic-ai-on-aws-from-poc-to-enterprise-scale?utm_source=newplatform_event&utm_medium=event&utm_content=master_classes&utm_term=hn

Are you curious how others here are running AI agents in production today?","time":1773317553,"title":"Ask HN: How are teams productionizing AI agents today?","type":"story"}],[47325105,{"by":"harperlabs","descendants":6,"id":47325105,"kids":[47420654,47325268,47371804,47328379,47424704,47326204],"score":2,"text":"$18","time":1773158647,"title":"Ask HN: How are you testing AI agents before shipping to production?","type":"story"}],[47301395,{"by":"jairooh","descendants":8,"id":47301395,"kids":[47371748,47335583,47341291,47301541,47301531,47301651,47315155,47313926,47320747,47410300,47374144,47310488,47303309,47321314,47321343],"score":5,"text":"With the recent incidents (DataTalks database wipe by Claude Code, Replit agent deleting data during code freeze), it's clear that running AI agents in production without observability is risky.

Common failure modes I've seen: no visibility into what the agent did step-by-step, surprise LLM bills from untracked token usage, risky outputs going undetected, and no audit trail for post-mortems.

I've been building AgentShield (https://useagentshield.com) — an observability SDK for AI agents. It does execution tracing, risk detection on outputs, cost tracking per agent/model, and human-in-the-loop approval for high-risk actions. Plugs into LangChain, CrewAI, and OpenAI Agents SDK with a 2-line integration.

Curious what others are using. Rolling your own monitoring? LangSmith? Langfuse? Or just hoping for the best?","time":1773003642,"title":"Ask HN: How are you monitoring AI agents in production?","type":"story"}],[47358618,{"by":"skhatter","descendants":10,"id":47358618,"kids":[47371581,47358619,47387258,47385982,47368409],"score":1,"time":1773357554,"title":"How are people debugging multi-agent AI workflows in production?","type":"story","url":"https://www.agentsentinelai.com/"}]]

user:	chirdeeps
created:	August 19, 2024
karma:	2