DT021

Higher AI-Assisted Development Speed vs. Code and Workflow Reliability

Business Context. AI-assisted development tools that generate code or workflow logic from natural language descriptions accelerate delivery significantly, but AI-generated logic can contain subtle errors that are not always caught before deployment.

Process TRIZ Resolution. Rather than deploying AI-generated logic directly without review, organizations should treat AI-generated code and workflows as a fast first draft, subjecting them to the same automated testing and lightweight human review applied to any other change before release.

Applicable TRIZ Principles

Principle 13 (The Other Way Round) treats AI-generated output as a proposal for review rather than a final deliverable.

Principle 25 (Self-Service) runs automated testing against AI-generated logic without requiring manual review of every line.

Principle 23 (Feedback) uses testing outcomes to refine how AI-assisted tools are prompted in future development.

Expected Outcome

Fast AI-assisted development

Reliable, tested output

Reduced risk of undetected errors

Continuously improving AI tool usage

Decision Indicators

AI-generated code has reached production without adequate testing.

Defects have been traced back to unreviewed AI-generated logic.

No review process exists specifically for AI-assisted development output.

Development speed gains have been offset by increased defect rates.

Teams treat AI-generated output as final rather than a draft requiring validation.

If several of these indicators are present, the contradiction is likely active and the Process TRIZ resolution above should be evaluated.