Engineering teams need to adapt to AI’s scaling challenges
AI is not a linear process. To scale effectively, engineering leaders must account for varied edge cases, presenting a new set of challenges.
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Susi O'Neill
Susi O’Neill works where emerging tech meets communications. She’s led thought leadership campaigns for B2B tech and cybersecurity audiences to build trust in tech. An author and keynote speaker, she covers frontier tech topics like women in tech, digital twins, and responsible AI. She edits Rethinking the Hype Cycle, a newsletter that helps business leaders stay ahead of what’s now and next in tech.
Using GenAI as a learning tool, not a crutch
AI is changing how we think about coding. While tools evolve, critical thinking, problem-solving, and creativity remain the essential skills for top developers.
To get ahead with AI, fine-tune your data strategy
In the first episode of our new podcast series, Leaders of Code, we sat down with Don Woodlock, Head of Global Healthcare Solutions at InterSystems, and Stack Overflow CEO Prashanth Chandrasekar to discuss data strategy's critical role in AI development.
How to harness APIs and AI for intelligent automation
APIs have steadily become the backbone of AI systems, connecting data and tools seamlessly. Discover how they can drive scalable and secure training for AI models and intelligence automation.
