Chains and application orchestration

A chain is a defined sequence of steps such as input validation, retrieval, prompt construction, model invocation, and response validation. Explicit orchestration makes each step observable and testable. Keep transformations deterministic where possible and assign clear input and output contracts to each component. Handle timeouts, empty retrieval, model errors, and invalid output at the step where they occur. Avoid turning every workflow into an autonomous agent. A fixed chain is often easier to evaluate, secure, and operate when the steps are known in advance. Use branching only when a measurable requirement justifies it. Pass request IDs and trace context across boundaries, and avoid logging secrets. A chain is easiest to maintain when each step has a clear input, output, timeout, and failure path. Validate the request first, retrieve only authorized context, assemble the prompt, call the model, validate the response, and finally format the user-facing result. Keep deterministic transformations outside the model where possible. Add request correlation IDs so logs and traces connect the stages without exposing secrets. Test each step with a stubbed dependency as well as an end-to-end case. When the workflow is fixed, an explicit chain is usually simpler to audit than allowing an agent to invent its own route. Implementation drill: trace one representative request through the stages in the diagram. Write down what enters each stage, what output or evidence it produces, and which identity is allowed to perform it. Then test an empty input, an unauthorized request, a dependency timeout, and an unexpected result. For each case, state whether the application should retry, reject, abstain, or ask a person for help. Keep the observed failure as a regression example so changes to prompts, models, data, or code can be checked against the same behavior. Practice task: When is a fixed chain usually preferable to an agent?