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Quality Review with AI

This document explains how to use AI as a reviewer (of code, docs, architecture) without giving it the final say. It is written for ConnectSoft team members using AI for quality review.

AI can be a powerful review assistant, but it should augment human review, not replace it. This guide shows how to use AI effectively for review while maintaining human oversight.

Important

Human Sign-Off Required: Critical decisions, security changes, and production pipeline modifications must have human review and final approval, not just AI approval. AI is a review assistant, not a decision-maker.

Review Levels

Level 1: Quick Sanity Check

Purpose: Quick validation of basic correctness

Use AI For: - Syntax errors - Basic style issues - Obvious bugs - Missing imports

Human Review: Minimal (spot check)

Level 2: Detailed Style/Consistency Review

Purpose: Ensure consistency with ConnectSoft patterns

Use AI For: - Style compliance - Pattern adherence - Terminology consistency - Cross-link validation

Human Review: Required (verify AI findings)

Level 3: Architecture & Risk Check

Purpose: Validate architecture and identify risks

Use AI For: - Architecture pattern compliance - Risk identification - Alternative suggestions - Best practice validation

Human Review: Required (critical decisions)

Using AI to Review Code Changes

Code Review Prompt Template

You are an expert .NET code reviewer reviewing code for ConnectSoft projects.

Goal: Review [code/file/PR] for quality and compliance.

Context:
- Code: [code snippet or file]
- Project: [project name]
- Pattern: ConnectSoft microservice template
- Libraries: ConnectSoft.Extensions.*

Review for:
- Clean Architecture compliance (Domain → Application → Infrastructure)
- DDD patterns (aggregates, entities, domain events)
- Observability (logging, tracing, metrics)
- Test coverage
- Code style and consistency
- Security issues
- Performance concerns

Output:
- Issues found (with severity)
- Suggestions for improvement
- Compliance assessment
- Risk assessment

Limitations

AI Cannot: - Run tests or validate functionality - Understand business context fully - Make final architectural decisions - Approve security changes - Understand customer requirements

Always: - Run tests manually - Validate functionality - Get human review for critical changes - Approve security changes with human security review

Using AI to Review Documentation

Documentation Review Prompt Template

You are the ConnectSoft Documentation Editor reviewing documentation.

Goal: Review [document] for quality and compliance.

Context:
- Document: [document content]
- Style guide: ConnectSoft documentation style guide
- Related docs: [list related docs]

Review for:
- Style compliance (title, intro, headings, callouts)
- Missing cross-links
- Inconsistent terminology
- Over-complication
- Missing sections
- Accuracy and completeness

Output:
- Style issues found
- Missing elements
- Suggested improvements
- Cross-link suggestions
- Terminology inconsistencies

Documentation Review Checklist

  • Single # title present
  • 1-3 sentence intro present
  • Logical heading structure
  • Appropriate callouts used
  • Cross-links to related docs
  • Consistent terminology
  • No missing sections
  • Content accurate and complete

See: Documentation Style Guide for style details.

Cross-Checking Architecture Decisions

Architecture Review Prompt Template

You are a ConnectSoft architecture reviewer.

Goal: Review architecture decision for [component/service].

Context:
- Decision: [architecture decision]
- Alternatives: [alternatives considered]
- Constraints: [technical/business constraints]

Review for:
- Alignment with Clean Architecture
- DDD pattern compliance
- Event-driven architecture compliance
- Cloud-native principles
- ConnectSoft patterns
- Risks and mitigations
- Alternatives not considered

Output:
- Architecture assessment
- Risk identification
- Alternative suggestions
- Compliance evaluation

Architecture Review Process

  1. AI Review - Use AI to review architecture decision
  2. Human Review - Human architect reviews AI findings
  3. Discussion - Discuss findings and alternatives
  4. Decision - Make final decision (human)
  5. ADR - Document decision in ADR

See: Decision Records Process for ADR process.

Human Sign-Off Rules

Critical Decisions Requiring Human Review

  • Architecture Decisions - All architecture decisions require human architect review
  • Security Changes - All security changes require human security review
  • Production Pipeline Changes - All production pipeline changes require human DevOps review
  • Breaking Changes - All breaking changes require human review and approval
  • Business Decisions - All business decisions require human product/business review

Review Process

  1. AI Review - Use AI for initial review
  2. Human Review - Human reviewer reviews AI findings
  3. Discussion - Discuss findings and concerns
  4. Approval - Human reviewer approves or requests changes
  5. Documentation - Document decision if significant

Important

Human Sign-Off Required: 1. Critical Decisions - Architecture, security, production changes 2. Breaking Changes - All breaking changes 3. Business Decisions - Product and business decisions 4. Final Approval - AI provides input, humans make final decisions