Fastest-Learning Generation

The best-trained absorbers, the worst-trained transmitters

Micky Malka, who spends a large share of his time with founders in their early twenties, describes the cohort as the smartest, fastest-learning generation in history by a specific mechanism rather than a vague compliment: they listen to podcasts at one and a half to two times normal speed, and they never had to wait a month for an annual letter to arrive by mail before reading it, because everything reaches them in real time.¹ He places his own education on the other side of the comparison deliberately, describing it as a mailed Berkshire Hathaway letter once a year plus a reference book to decode the vocabulary in it.

The interesting half of the claim is the deficit it implies. Speed of intake was trained into this generation by its media diet; transmission was not. Malka is direct about it: they were not trained to be great communicators, so the few who are great communicators have it embedded in them rather than taught. That produces an unusual and bimodal talent distribution, uniformly high on absorption and split sharply on articulation, and it locates the scarce founder skill precisely where it is scarcest, not learning quickly, which the whole cohort can do, but being able to put a vision and a story into words that bring other people along.

The diagnostic question

Malka's screen for this cohort, whose members range from about eighteen to twenty-six, is a single question: what were you doing during COVID. It works because it isolates a stretch of unstructured time that everyone in the generation shared, then asks what each person did with it when nobody was watching or grading anything. His finding is that the most successful founders he has backed were the ones who spent that period on YouTube, absorbing information about anything and everything, unsupervised.¹ Pressed on whether he and older operators could close the gap simply by using AI heavily themselves, Malka agrees with David Senra's observation that they have other commitments pulling their attention, while this cohort can live inside the tools full time. His answer is flat: "Yes. And they will." He also names the compounding piece: the current graduating college class is the first to have had access to AI tools for all four years of school, and likely the first in which a meaningful share used a model to help write the essay that got them in, which he expects to widen the gap between this generation and the ones before it rather than close it.

What it implies for everyone older

The practical consequence is about what an experienced person is actually for. Malka's answer to a thirty-five-year-old technical leader worried about being outpaced by a twenty-four-year-old is not reassurance that youth will fade as an advantage. It is that the older person is playing the wrong game if throughput is the axis of comparison, and that what they actually bring is wisdom, judgment, and accumulated experience rather than raw processing speed. The market has already priced this in its own way: young founders are recruiting older operators into small pods, commonly two or three twenty-two-year-old founders paired with one older operator, rather than the reverse arrangement that used to be the default.¹ The corollary is what stays scarce: with absorption now abundant across the cohort, the bottleneck moves to articulation and to taste, the two gaps Malka names directly.¹