AI-ASSISTED DEVELOPMENT
Keep visibility as AI accelerates development.
AI-assisted development can create and change software faster than ever.
Code Tuner helps teams understand what that acceleration is doing to the resulting codebase — measuring complexity, technical debt and software health as the system evolves.
Faster development creates a visibility challenge.
AI coding tools can dramatically increase the volume and pace of software development.
That creates significant opportunities for engineering teams.
It also means more code can be created, modified and introduced into software estates in less time.
As development accelerates, understanding the condition of the resulting system becomes increasingly important.
Measure the system AI helps create.
Code Tuner analyses the resulting codebase rather than the tool or process that generated it.
It helps teams track:
Complexity
See whether areas of the system are becoming increasingly difficult to understand or change.
Technical debt
Identify where maintainability signals are emerging or becoming concentrated.
Change hotspots
Understand which parts of the software are experiencing the greatest development activity.
Codebase trends
Track how important indicators change as AI-assisted development increases.
AI increases the importance of independent evidence.
AI-generated code is not automatically poor-quality code.
But greater development velocity increases the importance of maintaining visibility over the resulting software.
Accenture research found that 41% of executives identified AI as a leading contributor to technical debt, level with enterprise applications.
The answer is not necessarily to slow AI-assisted development.
It is to ensure that the ability to understand the software keeps pace with the ability to create it.
Complement your existing development controls.
Code Tuner is not an AI coding assistant or line-by-line AI code reviewer.
It is designed to provide a broader, codebase-level evidence layer alongside existing engineering processes.
Code Tuner does not replace:
Pull-request review.
Automated testing.
Security analysis.
Architecture review.
Engineering judgement.
Instead, it helps teams understand the condition and direction of the wider software system.
Direct human attention where it matters.
As code volume increases, treating every technical signal as equally important becomes increasingly impractical.
Code Tuner helps teams identify areas where closer investigation may be warranted while allowing healthier areas of the software to continue developing.
Investigate where the evidence supports it.
Monitor where appropriate.
Keep building where it doesn’t.
Independent of how the code was created.
Code Tuner analyses source code itself.
That means the same evidence can be applied across software created by developers, AI assistants or a combination of both.
The focus remains on the resulting system.
Read-only by design.
Code Tuner analyses source code without modifying or executing it.
Source code is not retained following analysis.
Develop faster without losing sight of the codebase.
We are particularly interested in working with teams increasing their use of AI-assisted software development.
Help us test where codebase-level evidence creates the greatest value as development velocity increases.
There is no cost to participate during the design-partner phase.
[Book a 30-minute conversation]
FAQs
Does AI-generated code automatically create technical debt?
No. However, increasing the speed and volume of software change can make ongoing visibility into complexity, maintainability and technical debt increasingly important.
Is Code Tuner an AI code-review tool?
No. Code Tuner provides broader codebase-level evidence, trends and analysis. It complements rather than replaces line-by-line review, testing or security tooling.
Can Code Tuner work alongside AI coding tools?
Yes. Code Tuner analyses the resulting source code rather than depending on which developer, AI tool or workflow produced it.