My Thought about the work in the era of AI

Many companies look for FDEs. Building is not a bottleneck anymore, but understanding and communicating with customers are. At the same time, knowing technology is a superpower in understanding and suggesting feasible solutions. The previous lean startup needs another change because splitting product person and tech person isn’t optimal anymore. In reality, one needs to get trained to absorb the other’s functionality. But it’s not as difficult as in the pre-AI era. Getting customer-mindset comes after understanding how they work and their pain in the process. So, the related basic soft skills: sympathy and communication, and systematized interviews. Getting product-mindset comes after training on the methodology of managing products, and continuous discovery + practice & time. Getting in-depth tech-knowledge comes after studying fundamentals (like math), and system architecture + practice & time.

All require some study and practice, but the study part doesn’t require tremendous effort and time in the AI era. I’d argue about 1-3 months once you have been through the basics (college math and science). And practice is again about 3-6 months each.

Even if you are responsible for only one part of the task in your organization, you still have a chance to be partially involved. You are maintaining backend but still it’s mostly encouraged to suggest in product management. You are researching a forecasting model but still it’s often welcomed to interview customers. You are customer success but still it’s great to build a micro-service to automate part of internal work.

As a cross-functional talent (not a cross-functional team), you are able to cope with a variety of challenges end-to-end. When I skim through job postings, most companies do not look for this talent. These companies look for X-years of experience in Y-tech stacks. If a talent is expected to work on one function, that’s fine. However, the team with the old-fashioned structure will have a hard time speeding up in an AI-boosted working environment.

Maybe, it’s difficult to find this talent from CV-screening and an hour of brief interviews. Checking X-years of experience in Y-tech stacks is relatively easy by giving a case-study problem and asking a couple of conceptual questions. How can we evaluate the capability of end-to-end functions of product life cycle (customer discovery - pm - build)?

I believe, AI makes each component simple, so there’s huge potential that business can grow multiple times faster than in the pre-AI era. However, it requires not only different strategy in hiring, but also greater effort to find the talent and give the environment to foster the “complete end-to-end capability”.