We are on the cusp of a big change. 

From healthcare and finance to self-driving cars and personalized search, the AI revolution is transforming industries. There’s no reason why AI shouldn’t impact what’s arguably the most logical of disciplines: coding. 

AI code-assistance platforms like Gemini Code Assist are leading the charge, accelerating software development with generative AI while helping to maintain enterprise-grade security and privacy. These platforms empower developers with features like auto code completion, code generation, and natural language chat, directly within their IDEs. Companies like Wayfair, PayPal, and Capgemini have already seen significant productivity gains thanks to Gemini Code Assist. However, to fully unlock the potential of these tools, companies need a way to measure their impact comprehensively. Understanding the "before and after" is crucial to demonstrating the ROI of AI code assistance and making informed decisions about its adoption and implementation.

Measuring the impact of AI-assisted application development

The growing prevalence of AI-assisted application-development tools necessitates a clear understanding of their real-world impact on developer productivity. This is especially true in today's economic climate, where budgets are constrained, and decision-makers demand concrete justifications for tool investments.

Measuring the impact of AI coding assistants is paramount for several reasons:

• Demonstrating ROI: Providing concrete evidence of productivity gains helps justify the investment in these tools to stakeholders.

• Informed decision-making: Measurement data enables informed decisions about which tools to adopt, how to best utilize them, and where to allocate resources.

• Continuous improvement: Tracking the impact of tools over time allows for the identification of areas for improvement in both tool usage and the development process itself.

But measuring impact is hard. Why?

• Subjectivity of impact: Developer productivity is multifaceted, encompassing code quality, speed, and maintainability. Quantifying the "improvement" brought by AI tools across these dimensions is inherently subjective.

• Difficulty isolating impact: Attributing productivity gains solely to AI tools is tricky. Factors like developer experience, project complexity, and even team dynamics also play a role.

• Lack of standardized metrics: There's no universally accepted standard for measuring developer productivity, making it difficult to compare the impact of different tools or across teams.

While measuring the impact of AI coding assistants presents challenges, it's an essential step towards realizing their full potential and optimizing their value within development teams. This is where Harness Software Engineering Insights (SEI) comes in, guiding teams toward elevated software quality, enhanced productivity, and overall excellence.

Harness AI Productivity Insights for Gemini Code Assist

The Harness Software Delivery Platform is an AI-augmented software delivery platform. A core module within the Harness platform, Harness Software Engineering Insights (SEI), empowers engineering leaders with actionable insights into software delivery performance, leveraging data from across the Software Development Lifecycle (SDLC) to optimize workflows, enhance developer experience, and accelerate time to value. 

Now, with the introduction of Harness AI Productivity Insights, a targeted solution based on Harness SEI, customers have even deeper visibility into the productivity gains unlocked by AI coding tools like Gemini Code Assist. By analyzing metrics from both traditional SDLC tools and AI coding assistants, this solution delivers:

• Data-driven decision making: Gain insights into the productivity gains, areas for improvement, and best practices for using AI coding tools.

• Qualitative feedback: Collect valuable feedback from developers to understand the impact of AI coding tools from their perspective.

• Comprehensive comparisons: Generate detailed reports comparing different developer cohorts, including those using AI coding tools versus those who are not.

• Tight integration: Easily integrate with your existing source code management systems and AI coding tools for effortless data collection.

Customer benefits

Harness AI Productivity Insights paired with Google Gemini Code Assist provides a powerful combination of advanced AI code assistance and precise metrics on its impact. Some of the key benefits to customers are: 

• Engineering leaders can make data-driven decisions about resource allocation, tool adoption, and team optimization. 

• Developers can use these insights to maximize their benefits from using Gemini Code Assist, leading to higher-quality code, speed, and increased innovation.

The overall result of using this solution is a more efficient and cost-effective approach to development, accelerating project timelines and enhancing overall productivity and developer experience.

“The combination of AI Productivity Insights from Harness and Gemini Code Assist is set to revolutionize our software development process by providing benchmarks to our generative AI investments. We're thrilled to witness the growing collaboration between these two industry leaders. This integration will greatly enhance our team's productivity and application reliability, empowering us to innovate more quickly and deliver top-quality software." - Sanjeev Hasiza, Head of Software Development & Director of Enterprise Architecture, Johnson Controls

With the global AI code assistance market set to grow, a robust impact measurement solution can help ensure you are solving the problems actually impacting your developers’ productivity. 

Ready to get started? Contact us to talk about how we can help your business. You can also check out the Harness listing on Google Cloud Marketplace or visit the Gemini Code Assist partner page.