A large proportion of EF cohort members come from direct recommendations or from being headhunted by the EF team. It probably makes sense to check who of your LinkedIn connections went through EF and ask for a recommendation. Being recommended or being headhunted has a strong correlation with being successful at EF.
EF describes what they’re looking for here. At the same time many of these terms seem rather vague. After all, everyone says they want ‘out-of-the-box’ thinking (whatever that means 🤷 ), and EF’s framework does not challenge convention in many ways. EF is set up on a rigid paradigm that seems optimised for reducing bad companies, at the cost of sometimes foregoing truly great companies. This is natural, every heuristic has to balance false negatives and false positives.
So let me go through the ones that I noticed at EF:
If you have friends who were at EF, ask them to share their application. If you don’t, just do some cold outreach to EF alumni. There will be many keen to help. Ask them to share theirs and review yours.
Konrad’s EF Application Berlin 2021
This is my application. My application is not very relevant to everyone, because I had founded a startup before. Following this application, I had three 30 minute interviews. In these interviews, pretty much the same questions were repeated and my answers were pretty much the same. First, I thought this was to check for consistency (to weed out liars), but I know think it’s because the EF team doesn’t have time to prepare for these calls. They seem to be back-to-back, so you start the conversation from scratch each time (that seems to be a general problem at EF). These conversations were very casual and we just went a bit deeper into the points we talked about.
I think the level is generally lower for technical founders as in my cohort there were several with zero or very little professional experience. These shined by showing leadership at university and studying at fancy universities for computer science. At the same time, business cofounders were generally more senior with several years at consulting firms or having built a company before. This makes sense given the shortage of tech talent.
The statistics they share vanity metrics. Here is a pipeline I saw:
That makes it look like a 0.05% conversion rate, which sounds super exclusive. However, what does conversations mean and why is the drop-off so high? I assume it’s something like looking at a profile. Applications are not a strong selection either, the application takes <1h to complete, so I assume the quality will all over the place. I would say that the application-to-interview ratio is more relevant. That being said, I know of some surprising rejections and some surprising acceptances.
Keep in mind that these funnel shapes are never a good metric for selectiveness, because it doesn’t say anything about prequalification.