Sample Excerpt: AI Prototype Architecture Review

A simplified, fictional example shows how the system overview, decisions, findings, and 30-/90-day plan are documented. No email gate.

This sample excerpt is fictional and intentionally simplified. It shows the format of the results; actual findings, scope, and level of detail depend on the repository and intended use.

Simplified System Overview

Example scenario: A B2B web application developed with AI tools is to be opened to its first paying customers after a successful demo.

  • Web frontend: Sign-in, customer management, and reporting.
  • API application: Business logic, data access, and external integrations in one deployment.
  • PostgreSQL: Customer, user, and transaction data.
  • External identity provider: Sign-in; authorization is also handled in the application.
  • CI/CD: Build and deployment are in place, but automated quality checks are only partial.

Critical flow: A user uploads transaction data, which is assigned to a tenant, processed, and shown in a report.

Decision Matrix

System component Decision Rationale
Frontend structure Refactor User flows work; state and API access are tightly coupled.
Authentication Keep The external provider is integrated appropriately and encapsulated for replacement.
Authorization Harden Tenant access is not centrally enforced for every data access.
Data import Refactor Business rules and persistence are mixed; error handling cannot be tested reproducibly.
CI/CD Harden The build is reproducible, but migration and integration tests are missing as release criteria.

Three Example Findings

01 · Tenant boundary not centrally enforced

Evidence: Two repository queries filter by a tenant ID supplied by the client; a shared server-side access context is missing.

Impact: Erroneous or manipulated requests could read another tenant’s data. This conflicts with the planned B2B use.

Recommendation: Derive the access context server-side, centralize data access, and add negative integration tests.

Effort class: M · Priority: immediate

02 · Schema changes are not tested for rollback

Evidence: Migrations run only at production startup; CI does not start an empty database or check either forward migrations or compatible application startup.

Impact: A faulty migration can block deployment and recovery.

Recommendation: Run migrations in CI against an empty and representative schema, document compatibility rules, and test the restore procedure.

Effort class: S–M · Priority: before launch

03 · Business logic is covered only by UI tests

Evidence: Import rules reside in the controller and data access; three central error cases cannot be tested in isolation without a full browser run.

Impact: Small changes require substantial review effort and increase the risk of unintended functional deviations.

Recommendation: Move import rules behind a clear interface, define representative sample data, and add fast domain tests.

Effort class: M · Priority: within 30 days

Example Decision

Conditional Go: A limited pilot with selected customers is viable once the tenant boundary is centrally secured and supported by negative tests. A general launch should additionally require migration verification and a tested recovery path.

The application does not need to be rebuilt. Authentication and large parts of the frontend can remain; authorization, import logic, and delivery require targeted measures.

Excerpt from the 30-/90-Day Plan

First 30 Days

  1. Centrally enforce tenant access and introduce negative integration tests as a release blocker.
  2. Verify database migrations reproducibly in CI; test backup and restore once under realistic conditions.
  3. Separate critical import rules from transport and persistence; add representative domain tests.
  4. Define error handling and monitoring for the import flow.

By Day 90

  1. Decouple frontend state and API access along the most important user flows.
  2. Version API contracts and test data for critical integrations.
  3. Fully document the roles and permissions model and review additional data access.
  4. Standardize quality criteria for changes in pull requests and deployment approvals.

What an Actual Architecture Review Adds

The full report includes specific repository references, scope and assumptions, a prioritized risk register, decisions for each relevant system component, open uncertainties, and a joint review of the results.

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