The AI in Development Episode

Introduction to the Guest and Topic:

Host Allie Krings introduces Robert Clark, Senior Team Lead on the Development Team at Kirkpatrick Price. The conversation focuses on how artificial intelligence is transforming software development. Robert shares his perspective on adopting AI tools within development workflows, explaining how his team has leveraged AI to accelerate development, improve productivity, and experiment with new ideas more efficiently.

What Is AI-Assisted Development?:

AI-assisted development is the use of artificial intelligence tools to help developers write, review, test, and enhance software. Rather than replacing developers, AI acts as a productivity tool that can generate code, create prototypes, suggest improvements, and assist with troubleshooting.

Robert explains that AI allows development teams to move faster by automating repetitive tasks and helping teams visualize ideas before significant development time is invested.

What Does AI Development Look Like Up Close?:

For Developers:

Developers can use AI to quickly prototype new features, generate sample code, and explore design concepts. Instead of spending hours manually building an idea, developers can describe what they want through prompts and receive working examples in minutes.

AI is particularly helpful for experimentation, allowing developers to evaluate different approaches before committing significant resources to implementation.

For Teams:

Development teams use AI to standardize workflows, accelerate project delivery, and improve collaboration. By selecting approved AI tools and establishing common processes, teams can work more consistently while ensuring security and quality standards are maintained.

The goal is not to eliminate human involvement but to allow team members to focus on higher-value tasks.

How Is AI Being Used in Development Today?:

Robert explains that AI is currently used for:

• Creating feature prototypes
• Generating code suggestions
• Reviewing code for potential issues
• Accelerating troubleshooting
• Assisting with workflow design
• Supporting development experimentation

In some cases, developers can generate an early version of a feature within 20 to 30 minutes instead of spending hours building it manually.

What Are the Biggest Concerns About AI Adoption?:

One major concern is moving too quickly. Because AI can generate large amounts of code very rapidly, teams must ensure they are still maintaining quality standards and thoroughly reviewing what is being produced.

Another concern is the possibility of exposing sensitive company information. Developers must use approved tools that prevent training public AI models on proprietary company data.

There are also concerns about developers becoming overly dependent on AI without fully understanding the underlying technology.

How Can Organizations Use AI Securely?:

Organizations should establish approved AI platforms rather than allowing employees to use any public AI tool they find.

Robert emphasizes the importance of:

• Using enterprise or organization-managed AI tools
• Disabling model training on company data
• Limiting AI permissions
• Creating approved usage policies
• Monitoring how AI tools are being used

These controls help ensure sensitive information remains protected.

What Controls Should Be in Place for AI-Generated Code?:

AI-generated code should never be deployed directly into production without review.

Kirkpatrick Price uses several layers of oversight:

Human Review: Developers must inspect and validate AI-generated code before submission.

Peer Review: Another team member independently reviews the code to confirm its accuracy and quality.

AI Review Agents: Additional AI tools can help identify risks and provide early feedback before human reviewers begin their evaluation.

These safeguards help ensure quality and security remain intact.

How Does AI Improve Productivity?:

AI significantly reduces the time required to experiment with new ideas.

For example, instead of manually coding multiple versions of a webpage feature, a developer can prompt an AI tool to generate several options. The developer can then quickly refine those options through conversation rather than building everything from scratch.

This allows teams to spend more time solving business problems and less time performing repetitive development work.

What Challenges Does AI Create for Future Developers?:

One challenge is ensuring future developers still develop strong foundational skills.

Robert notes that many coding problems can now be solved instantly with AI, which may reduce opportunities for newer developers to struggle through problems and learn fundamental concepts.

While AI can accelerate learning, developers still need to understand how code works so they can evaluate AI-generated solutions, troubleshoot issues, and identify mistakes.

What Makes a Good AI Prompt?:

Robert recommends starting with simple prompts and gradually adding detail as needed.

For example, rather than beginning with a lengthy description, developers can start with a concise request and evaluate the result. If the output is not sufficient, they can expand the prompt and provide additional requirements.

This iterative approach often leads to better outcomes than attempting to create overly detailed prompts from the start.

How Might AI Development Evolve in the Future?:

Robert believes AI will continue to improve incrementally over the next year, particularly in:

• Code quality
• Security reviews
• Development workflow automation
• Feature prototyping
• Review accuracy

Rather than expecting a completely new revolution, he anticipates steady improvements that make AI tools increasingly useful and reliable within development environments.

How Can Companies Ensure Compliance and Security When Using AI?:

Organizations should develop formal AI governance processes, approve specific tools, and establish controls around how AI is used.

This includes:

• Selecting approved AI platforms
• Reviewing generated code
• Limiting access to sensitive information
• Maintaining human oversight
• Educating employees on responsible usage

AI can significantly improve productivity, but organizations must balance innovation with security, governance, and proper review processes to ensure successful adoption.