🤝 If you would like to add or comment, I invite you to do so. It’d be great to have more voices.

⚠️ *Disclaimers:

• I have not been through Antler but it’s similar enough for info to be relevant. If you went through Antler and want to contribute, let me know!

• I did not team up with anyone through EF or ever pitched to them. I found my cofounder through YC co-founder matching and we’re building Peanut Protocol (hmu if you’re curious!). I still consider the programme to be extremely valuable and it definitely changed my life in many positive ways.

• I am often wrong and these are just my opinions.*

Why write this?

1. I get asked the same questions about EF, so it’s easier to answer them once, rather than repeat the same conversations.

2. I want to help. Maybe if help someone with this, that someone will help me later on?

3. Startup world as a whole is messy and opaque. The barriers to entry are much lower than people think, but ecosystem and culture knowledge is paramount. For instance, both EF and YC use obscure terminology for well-known concepts. YC asks “what do you know what others don’t” instead of asking for “competitive advantage”. They probably think that’s avoiding jargon, but without clarifying the question it could refer to anything. This actually increases the barrier, rather than lowering it, because you can’t google what they mean by that. EF uses “followership” instead of “leadership” 🤷. And I’m sure some midwit will be able to explain all the subtle differences, but idc. It’s a poor attempt at differentiation at best, and subcultural barriers to create in and outgroups at worst.

4. I like to talk to founders. So hit me up.

What is EF & Antler

They call it “talent investment” but that’s just a term to make us feel better about ourselves. It should be called something like pre-team & pre-idea accelerator, or founder matching accelerator. Confused? Me, too. The above graph illustrates it. In case you’re not familiar with venture capital, read my noob intro below.

The key hypothesis of EF & Antler is that they can get in super early. They believe that:

• successful founders share many similarities (you can tell in advance)

• many people do not found companies, because they can’t find a co-founder (co-founder search is really really hard and solo founders usually fail)

• many great founders need an extra cushion or an extra push, this means:

  • personal runway (how many months you can live without a salary)

  • ecosystem

    • knowing other founders really helps

    • knowing investors helps

    • having access to frameworks and learning materials helps

So their idea is to take would-be founders and give them this stuff, in exchange for a % of their future companies.

Noob Intro to VC

In case you know how the basics of VC and equity work, you can skip this.

Companies have equity (also known as stock or shares). This was invented, so that people could buy a part of a company. The more valuable a company is, the more expensive 1% of it is. Companies that solve a lot of problems that people are willing to pay for, e.g. Airbnb, are worth a lot ($50B or so). Now, if you had just 1% of Airbnb, you would have equity worth $500M, and you would be very rich.

But Airbnb was not always worth $5B. It started off as a small company, worth a few dozen thousands, perhaps. Whoever invested early, is very well off. Early investors (like Sequoia or Y Combinator) invested a few million for 10-20% of Airbnb equity, leading to a 1000X return on that investment.

However, most companies are not successful as Airbnb. 90-99% of startups fail, depending on how you define failure. Early stage venture capital investment deal with this by investing into 100 companies, knowing that 90 will fail, 5 will be barely OK, but 1-5 will make back their money more than X100.

Early companies are worth less, because it’s not yet clear whether and how profitable they will be. This makes them more risky investments, but with much higher potential returns. Risk and high returns go hand in hand. After all, if there were risk-free high returns, then everyone would bid for those, thus increasing the price and lowering the return.

Anyway, the earlier, the riskier but the more % you get for your $. That’s how finance works. And VCs go for the high-risk, high-reward end of this.

The Deal

EF’s deal is 10% equity for roughly $100k + the programme (2022 info).

To give extra incentive to join, they also pay you €6k for the 4 months of the programme. Yes, it’s actually 4 (not 3, like they say), because the programme starts when they release cohort names and people start networking. That helps with your personal runway (how long you can build a business without a salary), and people don’t feel that they’ve given up that much other than time, in case EF doesn’t work out for them. I think this is a gamechanger for many people.

EF do not invest in every company that’s at EF. They only invest in 30-40% or of the companies who have teamed up. In my cohort, there were 30 people who teamed up, and 17 who did not. That’s 15 teams. This means that EF will invest in only 6-8 teams, i.e. 12-16 people, which is only 30% of the total cohort. Don’t think that because you are in the programme, you will find a co-founder and get the pre-seed investment.

Is it a bad deal?

People tend to complain about this deal. I disagree. At EF you start with nothing. Even when the investment happens, the most you would have done, is probably a waitlist or maybe a few FFF (friends, family and fools) customers. The 100k let’s you build things for 9-12 and pay yourselves a $2.5k-3k monthly salary. Generally, you should be able to raise more capital a few months in.

Of course, when you look at the company’s pitches, it sounds like insane traction for a few months. But it’s not. For instance, one of EF’s flagship stories musiioo, claimed that they have a database with millions of songs already. Sounds impressive, right? Well, it’s not if you think more than 5 seconds about it. It’s a vanity metric. All the songs came from an open access database. Anyone tech savvy could download them and run some data analysis on them. It just sounds impressive, because it’s a large number. Anyway, just wanted to emphasise that it’s reaaaallly early for most of these companies. It’s not common to build something big in a few weeks.

When you pitch, you have “to be onto something”, not have a seed-ready company with a working business model. A few letters of intent, some decent weekly progress, etc. are good enough.

On top of this, you have to think where you are in the stack to see whether it’s a good or bad deal. If you’ve founded a successful startup before, you know investors already and they trust your business much more. That’s a bad deal then, you don’t need the EF money or the many talks and lectures. The only thing EF will be good for is your co-founder search, and that alone might be worth 10%. And it will be great for that, because you’re likely to already know what you want in a co-founder.

But if you’ve never raised much money, ever founded or worked as an early employee at a startup, then EF could be your gateway to the startup world. I think that’s the most attractive thing about EF. It’s a very easy, low-risk entry to give it a try in that world.

Is EF a good investor?

Short answer - they’re probably 2nd or 3rd tier. I’ve heard that they expect frequent updates but give little in return. However, that’s a good worry to have.

Is the alumni network worth it?

Short answer - no. The alumni community is relatively dead and there almost no events. The cohorts are very active, but once you ‘graduate’, there is nothing that sticks with you as an alumnus. Sifting through current cohort members might be useful for hiring however.

EF Personas

This is highly subjective, but also the most common question I got was “what’s the crowd like?”. So here is my very poor and biased attempt at answering it. Keep in mind that the “common weaknesses/strengths” are extremely subjective and biased.

Type in EF or the cohort name (e.g. BE9, LD5) into LinkedIn and you will find the kind of profiles who go through EF.

Who goes to EF?

EF attracts ambitious ~25-35 year olds (in my cohort it was min 23, max 42). My gut feeling, after looking at 4 cohorts (Berlin, London, Paris, Toronto) is that EF cohorts have a similar composition. I would categorise these as follows:

Ex-Founders 20%

Both, business and tech. People who already have built some kind of company, usually a small startup, and sometimes more traditional companies with low potential to scale. Mostly either small failed startups, side hustles, or traditional non-scalable businesses. In that mix, there are some impressive ones too. For instance, one guy scaled his company to 30 employees and reached 100% market saturation with a small gadgets business. There is someone who bootstrapped a proptech app and had hundreds of paying customers. I’ve not met anyone whose business was Series A funded.

McKinsey types 30%

They’ve spent a few years in a top consulting firm. Maybe the went to a fancy business school or studied econ or finance. Many of them worked in business roles at startups as well.

Devs 30%

Just good devs, with a decent mix of specialised and full-stack. You could probably find someone for most ideas.

Academics 20%

The hyper-specialists with deep insider knowledge. Examples: lawyer with 15 experience in a very specific legal field. Examples PhD in batteries, PhD in genomics.

Application

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:

• Followership: weird way of saying leadership. You rally people behind a cause. Maybe at your university you ran a charity fashion show, maybe you have a large newsletter.

• Clarity of thought. This is crucial. Here are a few tips to help with this.

  • Use short sentences. This forces you to pick words clearly.

  • Structure paragraphs clearly. Make your point, then present the evidence, then end with what this means for the overall story you’re telling.

  • Before responding to a question, rephrase it and ask whether you’ve understood it correctly.

• Technicality & Commerciality: this is the basic for EF’s CEO/CTO dichotomy. You should know how to build or how to sell and manage. Maybe you won several hackathons or you were a dev at some important company. Maybe you worked at McKinsey or went to a fancy business school.

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.

How selective is EF?

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 are vanity metrics. Here is a pipeline I saw:

• 9000 conversations

• 600 applications

• 184 interviews

• 48 selected

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.

The EF Framework

I can’t write about Antler, because Idk. I invite anyone who has been through Antler, to collaborate on this section.

You can read all about it here. This is a great reading list and along with YC content will teach you a lot about startups. Don’t binge read this this stuff, some seemingly simple concepts really need time to digest. E.g. scalability is a concept that seems simple but one could write books about.

I’ll very briefly go over one that is only briefly mentioned in this database, but that I find very useful.

Non-obvious beliefs

EF encourages you to think about your past experiences and what insights you’ve gained there. Ideally, you should made some surprising insights, that someone who is vaguely acquainted with the field would have no way of knowing after a few minutes of research.

Examples of obvious beliefs:

• Millennials have a hard time buying real estate

• Teenagers spend too much time on their phones

• Genomics is getting cheaper (even if you didn’t know, anyone can google this in 1 minute)

Examples of non-obvious beliefs:

• Good teachers are coaches primarily, there is little knowledge transfer

• 2nd hand batteries would be 50% more efficient, if they were stored properly

• Many defi products fail, because it’s very hard to properly test solidity code

Essentially, don’t work on stuff that you have no experience in. It’s usually very hard to solve a problem better than the people who face them every day.

The idea here is to weed out all the startup ideas that everyone has or can have. People tend to come up with similar ideas all the time. Airbnb for X, fractional real estate investing, investing with friends, an AI that does legal work, etc. Usually, these are bad startup ideas.

It takes some experience in the space to realise the real paint points. E.g. AI can do legal work but it’s more about document meta data and tags, than figuring out the legal logic. It takes some legal experience to know this.

Timelines

I can’t write about Antler, because Idk. I invite anyone who has been through Antler, to collaborate on this section.

Throughout the program, there are many workshops and talks. These are your usual accelerator talk. Sometimes great, usually mediocre. IRL talks are not a good way to learn, but workshops definitely are. Make sure to attend workshops. Talks you can probably skip and just read. YC has great content. Reading EF materials carefully and deeply is also a great source of knowledge and thought.

What Happens at EF

Month 0

This is a crucial month that EF haven’t told us anything about. Essentially, EF released the cohort list sometime early March, but did not tell you that’s when the programme starts. They claim it starts with Week 1 (two weeks after Kick-Off weekend). This is not true. As soon as the cohort lists are released, people start networking. This is a very important time because people are already chatting and gauging with whom to work.

Kick-Off Weekend

We had some speed networking sessions, some dinners and drinks. It was an intense weekend and you had the opportunity to meet 50 people or so. Definitely a must-go.

The two weeks before the start of the programme and the kick-off weekend are crucial as well. People meet up for coffees and drinks and already start networking intensively.

Months 1-2

Team formation time. It’s like love island, but for founders. People team up, split up, there is drama. They make you do weird posts on Slack where you compliment each other and give reasons for your break ups, then people react with weird emojis to them. It’s all a bit bizarre but seems to work.

Month 3

A lot of people seem to be in a rush to co-found at this point. It’s a little bit of a last attempt at EF. It’s important not to get overwhelmed by FOMO.

IC

Essentially, you pitch to the investment committee. They seem to judge you primarily on the data they gathered before the IC, on your progress etc. Keep in mind that they gather A LOT of data.

I am not qualified to talk about IC, because I dropped out before and found a co-founder outside of the program. I can’t write about IC, because Idk. I invite anyone who has been through IC (both accepted/rejected), to collaborate on this section.

Things I didn’t know but wished I knew

Timeline

EF does not communicate the point of the start of the program very well. It’s crucial to understand that the program starts the very moment they release the candidate profiles. People will immediately start networking and prequalifying teams. This effectively means that the programme starts roughly 1 month before the official start and 2 weeks before the Kick-Off Weekend.

People who join late are at a huge disadvantage, so don’t let them tell you that it doesn’t matter if you’re late. It’s false. In my case, I was heavily involved in humanitarian aid for Ukrainian refugees, the largest migration crisis since WW2, and was not in a mental or logistical place to start the program. However, I was assured that the start would not matter too much. It does matter a lot. There were other people who joined very late and they did not find good matches.

The first weeks are absolutely crucial. Do all your self-discovery before the program. I should have asked myself things like:

• who do I want to work with

• what are the topics that excite me

• what are the values I care about

• who do I want to hang out with

Pre-investment & Post-investment / Advisors vs VCs

What do I mean by this distinction?

Advisors & angels: specialists or more senior execs who have some skin in the game with your company, usually equity.

VC investors: professionals who sift through thousands of companies looking for investments that will return 100X.

The big difference is the kind of things you talk about to both. VCs don’t have skin in the game before they invest, they have no reason to help you before they invest. There is a careful balance of telling them about problems and actually making things look investable. Everyone knows that you’re likely to pivot a million times and that you know very little. However, if already at pitching stage there are major problems, such as a very small total addressable market, or a bad team-company fit, then you’re not investable.

Once they invest however, incentives change drastically and now both of you have a big interest in helping each other. After the investment VCs have skin in the game and if they’re able to increase your valuation by 2X, they will be 2X better off.

For instance, sharing any kind of issues such as doubts about team fit, mental health or family issues pre-IC will be extremely detrimental to whether you’re investable. This is super hard at EF, because you meet the team and become friends with them, so it’s natural to share worries etc. However, remember not to treat them as advisors or mentors before they invest.

Transparency

Expect that everything you share with EF team members, will end up in their databases, so treat them as bad HR interviews. This is crappy, because in 1:1 conversations, there is a reasonable expectation of privacy. Expect that everything that EF people can get their hands on, will end up in their database, which they will use to evaluate whether you are investable.

In other words, talk to them as you would to a VC, do not share problems with EF, unless these are problems that an investor should now about. So, for instance, do not talk about emotional worries, mental health, potential disputes with your cofounder. They will ask about these things, you have no obligation to tell them.

Here is an example scenario. This actually happened to me. EF team member has a 1:1 check in with you and asks “how productive have you been with your co-founder last week?”. Both of you are honest and say that you went off for a holiday and weren’t productive at all. This would be a totally normal response to other founders, angels or a VCs who has already invested, yet to a pre-investment VC that’s a red flag.

Exploration vs Exploitation

All choices face the exploration vs exploitation dilemma. Do you spend more time getting a clearer picture of the choices you face, or do you stick to one without knowing

Imagine that you’re looking for gold. You can either keep digging where you last found some small gold veins and get a constant payout of 10-20 nuggets per day, or explore more dirt at 0 nuggets per day, hoping that you will find a better vein.

Here is a weird thing about choice. Imagine you have three buttons, pressing them gives the following random pay-outs : A → $10-20, B → $12-22, C → $9-14. You can press a total of 100 hundred times and you want to maximise your pay-out. The dominant strategy would be to press a number of times (stats nerds can figure it out exactly), say, 6 times on each, get the averages, and then keep pressing on the one that yields the most. Both computers and humans act the same way here. However, introduce an additional rule: after not pressing a button for 10 presses, it disappears. What would you do? Rationally, you should proceed the same way. After all, after your first 24 rounds, you stopped exploring and start exploiting. However, people don’t like disappearing options and will waste their precious presses on lower-yielding buttons. That’s what people do in dating, cofounder, job, shopping search, etc. People love to hedge their bets. However, for very serious choices, it might be detrimental. You can’t explore 2 co-founder relationships at once.

Anyway, back to EF. You will face something like 25 CEO/CTO complimentary cofounder candidates. Perhaps 10 of them will be a good fit in terms of your areas of interest. That’s a lot of candidates to go through. You won’t be able to test deep and meaningful work with all of them. You will be out of sync in terms when you’re in the solo founder pool a lot. You’ll get maybe 3-4 shots of trying out a week or two with someone, and perhaps 5-10 chances of trying out a few hours.

Here are the costs of team switching:

• Announcement costs: every time you form a team formally, everyone gets a slack message and people ask you about it. That creates some pressure to stick to it

• Break up costs: every time you break up, you write a slack message with a mini review (always praising) your ex-would-be-cofounder. This results in everyone asking questions etc. This takes up time.

• Project management costs. Every time you switch, you have to have conversations about working hours, preferred methods of communication, tool stacks, division of AoRs, setting goals, etc.

• Emotional cost. It’s a bit like dating, so chances are you start getting emotionally involved in fantasies of success, what your life might look life later etc.

Finding the Right Cofounder

It’s hard. Don’t rush it.

Check out my substack article on co-founder fit questions.

Alternative ways of finding co-founders:

• YC Startup School Cofounder Matching

• Hackathons

• Friends

Other Voices

🙏🏼 If you wrote something on EF, please DM me https://twitter.com/0xkkonrad or here https://www.linkedin.com/in/konrad-urban/

My journey at Entrepreneur First Berlin

UNLICENSE, because fuck copyright. You can’t own ideas. Attribute me if you want to. It’d be nice.