Our next guest on 'Tech Connects' is Harry Wang, Chief Growth Officer at Sonar, a Geneva-headquartered company that's been helping developers build better, safer software faster for 16 years. Sonar serves 28,000 paying customers, 400,000 organizations, and over 7 million developers worldwide by providing insights on code quality, vulnerabilities, and security directly in developers' workflows. With AI-driven coding becoming increasingly prevalent across organizations, I wanted to talk with Harry about how companies can effectively integrate these powerful tools while maintaining security and governance standards. At the same time, I was curious to explore how AI is reshaping the very nature of software development roles and what that means for engineers at every level.

Here are some quick takeaways from this discussion for any tech professionals navigating AI integration in their organizations:

Start with Pilot Projects and Gather Comprehensive Feedback: Don't roll out AI tools to everyone at once. Instead, test different AI coding tools with small groups first. Get feedback from developers about what helps them work better, and ask your security team about potential risks. Run these tests for a few months to really understand what works and what doesn't before making bigger decisions about which tools to use company-wide.

Cultivate AI Champions from Multiple Organizational Levels: AI adoption happens in different ways across your organization. Some developers will experiment with tools on their own, while management might run formal tests, and executives might push for company-wide AI strategies. Recognize that AI advocates come from all levels and backgrounds, so work with whoever is enthusiastic about these tools to help spread adoption throughout your company.

Invest in Tailored Training and Prompt Engineering Skills: Help your team get better at using AI tools effectively. This means learning how to ask AI the right questions to get useful answers, sharing successful approaches with teammates, and providing formal training through online courses or internal workshops. Think of it as building up your team's ability to work well with AI, just like any other skill.

Embrace AI as Career Augmentation, Not Replacement: Instead of worrying that AI will take your job, use it to do more interesting work. AI can handle boring coding tasks, write tests, and complete routine functions, which frees you up to focus on bigger picture problems like system design and architecture. This is actually an opportunity to level up your role and work on the strategic challenges you've always wanted to tackle.

Implement Robust Governance and Security Oversight: As more people in your company use AI coding tools—including non-technical staff—you need clear rules and safety checks. AI can make mistakes, suggest risky code, or import dangerous third-party libraries. Make sure you have tools and processes in place to catch these problems, and keep humans involved in reviewing and approving AI-generated code.

There was a lot more in that chat, of course, so give it another listen if you feel so inclined. Thank you for joining us—and remember, Dice is your best resource to find the tech talent you need to fill your open roles, and for tech pros, the best place to grow your tech career.

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