AI agents are here—are your skills ready?

Tips to help developers and students get started with AI and prepare for the agentic future.

Jon Reifschneider, director of the AI Master’s program at Duke University and CEO of Inquisite AI, sat down with the All Things Open team to share why the real progress in AI lies in how we build systems around models. Beyond improvements in foundation models, he highlights the rise of AI agents, tools that chain models together to complete complex tasks, as a major step forward for developers and teams.

Many challenges remain when it comes to AI, especially around bias, misinformation, and the growing “AI divide” between those who use AI tools and those who don’t. Jon stresses the need for accessible training and support across individuals, employers, and government. With costs rising and adoption surprisingly uneven, closing that gap will be critical for both productivity and equity.

To get started, Jon recommends a hands-on, parallel approach: Begin using AI tools like ChatGPT, Gemini, or Claude while also learning the basics through free courses from platforms like Coursera. Developers should pair experimentation with a deeper understanding of how AI works to better guide its use and avoid common pitfalls.

Read more: How AI agents are turning LLMs into real software tools

Looking ahead, Jon sees major potential in agentic AI where intelligent systems are capable of completing real work on behalf of users. This shift brings both opportunities for productivity and serious questions about how the workforce will adapt. For students and professionals, he suggests focusing not just on programming skills, but also on soft skills like critical thinking and problem-solving that remain uniquely human.

Key takeaways

• Systems matter: Building infrastructure around models is where much of today’s AI progress is happening.
• Upskilling is essential: Employers, individuals, and governments all have a role in closing the AI divide.
• Start learning AI now: Free online tools and hands-on use are the best way to learn and build AI literacy.

Learn more

• Artificial Intelligence – Master of Engineering
• Inquisite AI

Conclusion

Jon’s insights offer a grounded view of AI’s future, where learning, curiosity, and adaptability matter as much as technical skill. For developers, this means building not only with the latest models, but with intention and responsibility. Many people still haven’t used tools like ChatGPT, creating a gap between those who are leveraging AI to accelerate productivity and those who aren’t. Closing that divide will shape not just the future of work, but who gets to participate in it.

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