Before building an Amazon Bedrock agent, define the job it must do and how you will measure success. Then evaluate its instructions and model, tool use, knowledge retrieval, safeguards, and runtime behavior against representative tasks—not just a polished demo.
There is an important service distinction for new projects: as of July 30, 2026, Amazon Bedrock Agents Classic is no longer open to new customers. Existing customers can continue using it, while AWS recommends Amazon Bedrock AgentCore for new development and migration. Bedrock models, Knowledge Bases, and Guardrails remain supported. AWS documents the Agents Classic status and transition; check current service and regional availability before choosing an implementation.
What an Amazon Bedrock agent consists of
In the traditional Agents Classic configuration, the minimum prepared agent includes an agent resource role, a foundation model, and instructions. AWS also says to configure an action group or a knowledge base. Without either, the agent responds using the foundation model, instructions, and base prompt templates alone. Guardrails and provisioned throughput are optional configurations in that setup. AWS describes the Agents Classic components and setup.
For new development, assess the AgentCore path rather than assuming the older setup is the default. AWS describes a managed AgentCore harness for a model, tools, and instructions, as well as code-defined agents for applications that need custom orchestration. The migration guide compares capabilities, but does not establish that every feature maps identically between AgentCore and Agents Classic. Review AWS’s Agents Classic and AgentCore guidance and confirm the features and regions your project requires.
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1. Define the purpose, model, and instructions
Start with the task, not the model picker. Write down what the agent should accomplish, which requests are in scope, and what counts as a correct result. In the documented Agents setup, the foundation model performs orchestration and natural-language instructions guide its behavior. That makes the instructions and model part of the design to evaluate, not a substitute for defining the outcome. AWS explains how Agents are configured.
Build a small, versioned set of representative requests before changing the design. Include routine tasks, ambiguous inputs, and cases where the agent should decline or ask for clarification. Track task completion and answer correctness for each run. A successful demonstration on one request does not establish how the agent will handle the range of requests it will see in use.
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- Your favorite music and content – Play music, audiobooks, and podcasts from Amazon Music, Apple Music, Spotify and others or via Bluetooth throughout your home.
- Alexa is happy to help – Ask Alexa for weather updates and to set hands-free timers, get answers to your questions and even hear jokes. Need a few extra minutes in the morning? Just tap your Echo Dot to snooze your alarm.
- Keep your home comfortable – Control compatible smart home devices with your voice and routines triggered by built-in motion or indoor temperature sensors. Create routines to automatically turn on lights when you walk into a room, or start a fan if the inside temperature goes above your comfort zone.
- Do more with device pairing – Fill your home with music using compatible Echo devices in different rooms, or create a home theatre system with Fire TV.
- Say goodbye to drop-offs and buffering - With eero Built-in, Echo Dot doubles as a mesh wifi extender, adding up to 1,000 sq. ft. of wifi coverage to your existing eero network.
2. Measure tools and permissions
In Agents Classic, action groups expose operations an agent can perform. Their parameters and API handling determine which operations are available and how the agent invokes them. AWS’s Agents documentation covers action groups. Give the agent role only the permissions those operations require, and check that each operation is bounded to its intended purpose.
Measure whether the agent selects the right tool, supplies valid inputs, and handles tool errors appropriately. Include requests for which a tool is unnecessary or must not be called. Record both correct calls and mistaken calls; task completion alone can hide an unsafe or unreliable tool choice.
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3. Check knowledge retrieval and grounding
A knowledge base gives an agent information it can retrieve to answer questions. Retrieval access, however, is not proof that the generated answer is correct. AWS describes knowledge bases as an Agents capability, and its Knowledge Bases documentation covers the retrieval feature.
Test with questions whose answers and supporting source material are known. Check whether the relevant material is retrieved, whether the response reflects it accurately, and how the agent behaves when the material is missing or does not answer the question. Keep retrieval correctness separate from response correctness so a good-looking answer does not obscure a retrieval failure—or vice versa.
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- Your favorite music and content – Play music, audiobooks, and podcasts from Amazon Music, Apple Music, Spotify and others or via Bluetooth throughout your home.
- Alexa is happy to help – Ask Alexa for weather updates and to set hands-free timers, get answers to your questions and even hear jokes. Need a few extra minutes in the morning? Just tap your Echo Dot to snooze your alarm.
- Keep your home comfortable – Control compatible smart home devices with your voice and routines triggered by built-in motion or indoor temperature sensors. Create routines to automatically turn on lights when you walk into a room, or start a fan if the inside temperature goes above your comfort zone.
- Do more with device pairing – Fill your home with music using compatible Echo devices in different rooms, or create a home theatre system with Fire TV.
- Say goodbye to drop-offs and buffering - With eero Built-in, Echo Dot doubles as a mesh wifi extender, adding up to 1,000 sq. ft. of wifi coverage to your existing eero network.
4. Test safeguards against real policies
Amazon Bedrock Guardrails can evaluate user inputs and model responses. AWS documents configurable content filters, denied topics, sensitive-information filters, word filters, and image content filters, and says Guardrails can be used with Agents and Knowledge Bases. See AWS’s Guardrails overview for the documented controls.
For each policy you intend to enforce, test requests that should trigger intervention and benign requests that should still be allowed. Review whether the configuration matches the application’s actual boundaries. Filtering can help enforce configured policies; it is not a general guarantee that answers are correct or that every risk is addressed.
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5. Evaluate outcomes and monitor operations
AgentCore Evaluations can assess end-to-end goal attainment, tool-call accuracy, and custom criteria. AgentCore observability documents latency, duration, token use, error rates, and session activity, with CloudWatch as the telemetry destination. AWS documents AgentCore Evaluations, and its observability guide describes runtime telemetry.
Use a versioned scenario set and retain results so changes can be compared with a baseline. For each scenario, record:
- Whether the agent achieved the goal and whether its answer was correct.
- Whether it selected and called tools accurately, including when not to call one.
- Whether the right knowledge was retrieved and used, if a knowledge source is involved.
- Whether guardrails intervened on expected inputs while allowing acceptable requests.
- Latency, duration, token use, errors, and the cost implications of the selected services.
When a run fails, review traces and runtime signals to locate the failure: the task interpretation, tool selection or execution, retrieval, response, or configured safeguard. Compare concrete designs on task success, correctness, tool accuracy, latency, token use, operational complexity, and custom orchestration required. Choose measures that fit the application; AWS’s documented metrics do not create a universal score or identify a best model.
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