Do You Know What Your AI Agents Are Doing? Lost Control? 🤔

Do You Know What Your AI Agents Are Doing? Lost Control? 🤔

While having a 2nd coffee - to be honest, it’s the third already as days are long at #MTM25 - I’m reflecting on what has been top of mind for the participants I’ve met here so far. They share two things: curiosity and fear. 🔍

Curiosity to learn about new technology and figure out what’s possible with it.

Fear of losing control and having to deal with a black box that gives them no way to understand what’s happening inside. How it achieves the results it delivers. No way to explain why these results and not others. 💭

Like a modern coffee machine. Complex. Hopefully providing good results… until it doesn’t. And then what? ☕

🛠️ The starting point for tackling this is to build observability in right from the start. And this is not new. This is not specific to AI. This need is very prominent in modern system architectures of the complex systems we build. There are established concepts, methods and implementations. OpenTelemetry — the project’s APIs and SDKs plus its OTLP wire protocol — is well established and integrated in many tools.

📊 One way to enable yourself to understand your AI agent is Amazon Bedrock AgentCore Observability — seeing what the agent does is the foundation; actually controlling it takes complementary mechanisms like permissions, guardrails, and human approval on top. It provides an end-to-end solution for monitoring, analyzing, and debugging AI agent interactions across different frameworks and foundation models, giving you operational visibility from day one and a much better shot at diagnosing reliability problems. With easy setup, automatic instrumentation, and seamless integration with AWS CloudWatch dashboards, teams get the visibility that enables faster development cycles and more trustworthy AI agent deployments — observability makes those possible; acting on what the traces show makes them real. This approach empowers organizations to build robust generative AI solutions with comprehensive visibility into agent inputs and outputs, tool calls, traces, performance, and user experience. Wanna dive deeper and build your own? Have a read of [1]

💡 As Alessandro Alviani mentioned yesterday in his talk: “Keeping control and being able to monitor was the key to the success of Süddeutsche Zeitung’s AI projects.”

Unfortunately, the coffee machine in the picture is not affordable for me. Love the design and it produces nice coffee. AI Agent Observability, in contrast, is very much affordable. Don’t miss out on this opportunity! ✨

[1] Blog “Build trustworthy AI agents with Amazon Bedrock AgentCore Observability” - https://aws.amazon.com/blogs/machine-learning/build-trustworthy-ai-agents-with-amazon-bedrock-agentcore-observability/ — official documentation: https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/observability.html

#MTM25 #AWS #AmazonBedrock #AgentCore #Observability

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