Forget coding: Autodesk CEO pitches 'total systems thinking' as your ultimate shield against the AI takeover

Economic Times

2 days ago

Synopsis
As AI increasingly automates coding, Autodesk CEO Andrew Anagnost emphasizes that 'total systems thinking' is crucial for career success. He suggests future roles will require individuals to creatively manage AI output and connect diverse fields. Experts like Wharton's Ethan Mollick highlight the importance of 'bundled roles' blending empathy and judgment, while warning about potential loss of entry-level positions.
iStock Autodesk CEO Andrew Anagnost suggests that total systems thinking, not just coding, will be crucial for career success as AI increasingly automates coding tasks. Future roles will require individuals to creatively manage AI output and connect different fields. (Images: iStock, LinkedIn) In a world racing to keep up with artificial intelligence, simply knowing how to code might no longer be the edge it once was. According to Autodesk CEO Andrew Anagnost, the skill that may truly help future-proof your career is something deeper, broader, and far more human: total systems thinking. In an interview with Business Insider, Anagnost emphasized that as AI models become increasingly capable of writing code independently, the most valuable human contributions will come not from technical repetition, but from interdisciplinary insight. 'If the coding models are going to be doing the code for you, what's more important is that you understand this whole notion of systems-level and interdisciplinary thinking,' he said.
Anagnost, who holds a Ph.D. in aeronautical engineering and computer science, is a strong advocate of breaking out of traditional disciplinary silos. He believes future job roles won't necessarily go to those who go deep into one niche area, unless they're aiming for research careers. Instead, the next big value-add will come from individuals who can connect the dots across different fields — and creatively manage the output of AI systems. 'Humans will need to take the role of creative orchestrators,' Anagnost said, adding that it's not just about what is made but how it all fits together. In other words, those who can understand the broader picture of how a product is designed, built, and delivered — and how AI fits into that lifecycle — will be in demand. This shift in thinking is already playing out in workplaces as tools like GitHub Copilot and OpenAI's Codex automate increasingly complex coding tasks. 'There will be more people generating code than ever before,' Anagnost said. 'And many of them won't have backgrounds in computer science.'
Rather than making coding obsolete, this democratization means that coding becomes just another tool — and not necessarily a distinguishing one. According to Anagnost, a typical software company today employs a team that includes a product manager, designer, engineer, and quality assurance tester. But that's changing fast. In a near-future setup, he envisions a leaner model where a product designer collaborates directly with an AI coding assistant to handle both development and testing. What ties this streamlined workflow together? 'Total systems thinking,' he said. It's about knowing how the entire machine works — from vision to execution — and not just being a cog in the system. Anagnost's message aligns closely with Wharton professor Ethan Mollick, author of Co-Intelligence: Living and Working with AI. In a recent interview with CNBC Make It, Mollick argued that the safest roles in an AI-driven world aren't necessarily the most technical — they're the most complex.
'AI may outperform you in one or two things,' Mollick said, 'but if your job requires five or six of them, it's a lot harder to replace.' He advises professionals to gravitate toward 'bundled roles' — jobs that blend empathy, judgment, creativity, and domain expertise. These roles are harder to automate, and more importantly, make room for humans to collaborate with AI rather than be replaced by it. One unintended consequence of this shift could be the loss of traditional entry-level roles. As AI handles more of the repeatable grunt work, young professionals may have fewer chances to learn by doing. Without that foundational experience, Mollick warns, the pipeline for future leaders could be at risk. Mollick and Anagnost agree on one thing: the real problem isn't AI — it's leadership lag. Companies must rethink hiring, training, and education models to adapt to this new world. The future belongs to those who can think broadly, manage complexity, and orchestrate outcomes with the help of intelligent machines.
If you're planning your next career move — or even your college major — consider this: it's no longer just about learning to code. It's about understanding how systems connect, how humans and machines can co-create, and how creativity still holds the power to differentiate. In Anagnost's words, the future may hold fewer traditional computer science grads in software firms, 'but there'll probably be more people creating product than ever before.'