Feeling Behind on AI? How to Learn AI Without Doing It Alone

Fey Pelleg, founder of AI Goddesses, says the fear comes from not knowing where to start and feeling that it is too big, and that a project that is too big fails fast. She starts people on something small and playful where no specific result is needed, so there is nothing to fail at. Once you have made something with AI, she says, it is hard to ignore that you can do it (6:31, 7:16).

Fey says even teams that were trained in AI probably still don't feel comfortable with it. As far as she remembers, most workplace training was very technical, with no playful moment and no creative project (32:41). She adds that it is often something you complete on your own, or a Zoom call where one person talks while others turn off their cameras and cook dinner (34:57).

Fey suggests learning together and in a playful way, with whatever tool the team already uses. Do it as a group, share what each person makes, and keep the task light, for example by taking your latest task and making it a comic book. She says people who are not expected to succeed and have a personal connection to what they are doing are far happier to learn and remember it later (33:23, 34:00, 35:35). Kerstin Dallinger adds that in a heavily regulated space such as Europe, not every tool is usable, especially free ones (31:34).

Fey says AI has a default style: give it no instructions about style and you get the look everyone has, the same and a bit overpacked. Naming a specific style, even one word like "quilt", already changes a lot, and you can also give it reference images or the names of styles you like (23:55, 24:24). If you don't want to decide yourself, she suggests asking the AI to act as your design expert and recommend a style for your message and audience (25:56).

Fey recommends about two to four months if you do it once a week, adjusted to how much your team works with AI (36:48). She suggests writing down what you want to achieve and what it would save, and mentions a student whose week-long task took two minutes live in class (37:01, 37:21). As a team lead, she ran a weekly training during work hours instead of the stand-up (37:57).

Fey says the work would run out anyway, because AI is not going away and the people working in your field later will be the ones who know how to use it, so your time is better spent learning the tools (40:26). From her own experience, work doesn't seem to run out in companies: her development team of about 10 people always had a backlog of at least a year (41:23, 41:31). If you do run out, she suggests adding projects that still benefit the company (42:03).