“Run toward problems.”
Lisa Su has described “run toward problems” as one of the most important pieces of advice she received as a young engineer at IBM. In a 2021 profile for IEEE Women in Engineering Magazine, she connected the idea with finding large opportunities and taking on the next difficult challenge. The phrase is deliberately active. Problems attract attention, resources, and learning precisely because many people avoid them. Su’s career in semiconductor research and the turnaround of AMD gave the principle an unusually demanding business context: important progress begins where the work is hard enough to matter.
Running toward a problem does not mean rushing without diagnosis. Leaders can define who experiences the problem, collect evidence about its causes, and choose a part of the system where action can produce useful learning. Difficult assignments need authority, resources, and access to expertise; otherwise volunteering becomes a way to inherit accountability without the power to succeed. A healthy organization rewards people who surface trouble early and supports them through resolution instead of valuing only the person who arrives after a crisis has become publicly visible.
The maxim also needs limits. Companies can romanticize emergency work, rely on the same employees to rescue preventable failures, and call burnout courage. Some problems should be prevented through maintenance, staffing, and better design rather than celebrated as heroic challenges. Leaders must distinguish growth from unmanaged exposure and distribute difficult work fairly. The goal is not to keep talented people in constant crisis. It is to direct capability toward consequential obstacles while improving the system so that the same emergency does not recur.
The semiconductor and AI industries show why the posture matters. Technical bottlenecks in energy use, memory, supply chains, software, and accessibility will not disappear through optimistic messaging. Teams can rank problems by customer and social importance, create cross-functional ownership, and measure whether each experiment reduces the constraint. Su’s compact advice turns uncertainty into a place to look for contribution. The strongest version pairs courage with engineering discipline: approach the hard problem, understand it, give people what they need to solve it, and preserve the learning for the next challenge. A problem portfolio can show which challenges are strategically important, who is affected, what resources are committed, and whether the work is prevention, discovery, or recovery. Leaders review whether the same people repeatedly carry urgent problems and whether a solved issue truly stays solved. The portfolio makes courage distributable instead of heroic. It also reveals when the organization celebrates intervention while failing to fund maintenance, documentation, and design changes that would make the next intervention unnecessary.
Su has credited an IBM mentor with advising her as a young engineer to run toward problems.
She later described the approach as a route to large opportunities, learning, and consequential work.
Difficult problems can concentrate learning when teams receive evidence, authority, resources, and expert support.
Constant firefighting is not courage; leaders must prevent recurring crises and avoid rewarding burnout as heroism.
Semiconductors and AI face intertwined technical, energy, supply-chain, software, and access constraints.
Cross-functional ownership and preserved learning turn a hard challenge into durable organizational capability.
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