I see many academics try to start companies. While there are a few noteable examples of this working out: Coursera, Tableau, Google (though Larry/Sergey were still early in the PhD when they left), all of Chris Re's companies, etc. Those are the exemptions, not the rule. There are many examples of this not working out. This is because the habits, skills, and instincts engrained into great academic are almost antithetical, certainly orthogonal, to what would make you a great founder. Academics need to unlearn key instincts beat into them by their PIs, over years of bleary-eyed nights, to make it as founders. This is literally killing a part of their identity. Academics have the intelligence to pull it off, but most do not have the will. I break it down to a few key issues below:
Academic-Brain is focused on # of citations and # of papers published (literally the only 2 measures in H-Index calculation); Founder-Brain is focused on usage, are you building something people want or care about. That requires focus on a single customer's problem and walking backwards and maniacally focused on that one singular customer and that person's problems. In a lab, a 3% lift on a static benchmark is exciting; in startups, who the hell cares? You need to be 10x better to get a company to switch to you. Academics are constantly optimized for Reviewer #2 and proving him/her wrong; in startups you optimize for your customer always. Will he/she pay for this? The researcher loves a new loss function; the founder loves watching a user share their screen and say, “Wow! This is so much better than before”.
>99% of Academic benchmarks and papers are written and tested against immutable (unchangeable) datasets. This is great for science so its clear what is happening. However its impracticle for the real world. The easiest way to improve on a specific skill (like self-driving car, or robotic manipulation) is to capture more, diverse, clean data. The ROI on that beats always any architecture improvement out there. So just do it. Do the dumb thing to improve the product. Academics will consider this "cheating" which it is in academia, but in the real world, its the right answer! Every academic turned first time founder wants to start building training pipelines. This is usually the wrong first step. The right first step is almost ALWAYS HITL (Human in the loop) pipeline. You need the incoming live data stored remotely anyway. You need the labeling pipeline anyway. Your v1 model is going to have some % human validation anyway that will start at 10% going through HITL then will get to 0.1% or so. So just start it at 100% and get customer feedback, etc, right off the bat! You will find that once you do this, your understanding of the end product, labeling docs and how to solve the problem, domain shifts, etc etc will all be drastically different than what you expected. And you will pull in timeline by a year or more. Also you will allow your company to run in parrallel vs. in series bc now product can start customer interviews, sales can start demoing / selling (even if unprofitably), etc etc. All good things.
In startups, you dont have time. You are dying. You are falling out of the sky while you are trying to assemble the plane. You dont have time to worry about why this tweak to the tokenizer results in an improvement, it just does, and thats good enough. Empericism is fine. The scent for what is important and what is not is completely different. Important = anything that moves the needle for the business: sign-ups, activation, retention, revenue, or referrals. Unimport = anything that is extremely interesting but doesnt move the needle, may make your brain tingle though! Proving a new lemma that your algorithm is globally optimal? Unimportant. Visiting 10 users to get feedback on a new launch? Important. Publishing. Unimportant. Pushing product. Important. Many academic startups die because they are run out of money focusing on the interesting but unimportant before they get to PMF and default alive.
Joe Lonsdale has a great talk about MIT startup vs. Stanford startup. MIT startups are all about this new invention, the black box that does some magic. Stanford startups are all about a single customer problem, and how to solve it better and better over time. The former barely ever turns into a massive company. The latter almost always does if done right. This is because MIT is much more "Academic" and academica loves (LOVES!) novelty. You dont get published with a me-too paper.. BUT in startups not true! You can become a billionaire with me-too'ing. e.g. Building Uber 2.0 (lyft) or OpenAI 2.0 (Anthropic) or Instacart for Latam (Rappi!). Peter Thiel famously said the something of somwhere is the nothing of nowhere and thats not necessarily true when geographic barriers exist. The google/twitter/amazon/uber of china, all ended up being great businesses. The instacart of latam, great business. In fact, that is derisking! Novelty is a liability in startups! Its ok. You can be a me-too, even if it hurts your inner academic.
Companys say marketing type stuff all the time that may or may not be true but its simple, easy to digest and most importantly it works. "Geico can save you 15% or more on your car insurance" How inexact. Can save me? Does it? How? Vs. an academic wants rigor and qualificiation with such claims which ends up being boring, technical, and overly verbose. You dont have time to get to stat-sig most the time. You need to move. Sometimes you will have time for 'some' rigor. But that is usually way post PMF.
You need confidence to run anything, but humility is really important. No one wants to work for a brilliant a-hole. No one cares about how much you know about finite automata and prototype trees. Just stop. Academics can come off like complete jerks because they are so smart and so right it actually just is not effective. Yes you may be smarter than your customers and investors. So what? Why shove it in their face? A more intelligent person would drop the ego, and be so curious about how other people's brains work and why they do what they do that it wouldnt be about letting the world know how smart I am.. but how cool THEY are and how much I can learn from THEM. Academics are awful at this. But you can choose otherwise!
I used to love having my paper submitted, deleting all the open tabs of relevant papers, my overleaf, github, etc. cleaning up my desktop of 200 different png's, etc. Its submitted. I am done. Lets start clean. There is no cathartic stop/start in startups unfortunately. You need to keep plowing through. The threads are never cut. You need to keep pulling on the same threads for a decade. Its a much different mind set. So in this way, you are constantly working on the same customer problems. This changes the timeline of your plan fundementally.
VERY few academics who are looking to start a company have read Brad Feld's Venture Deals and so they dont really understand what a liquidation preference is or a cap, or pre/post and they get HOSED when they go and raise because while there are a lot of good Venture Capitalists, there are also a lot of bad Vulture Capitalists. You are smart enough to understand this stuff. Do it. Take the time to learn it. Buy the book. Read it. Ask clarifying questions about NVCA framework. It will pay off immensely in time.
Another wierd thing I have seen is that many Academics who want to start companies will deride people who make a lot of money or who run money. This is misfounded. This is also why academia tends to skew more socialistic vs. capitalistic. If you believe in socialism, I am not sure starting a company will be the right thing for you. This is the most capitalistic thing you can do with your FLOPS. You are building new inventions that you are going to charge money for for the world, you are going to take in capital from venture funds who need to post a return and expect you to create economic value for your shareholders, and beat our your intense competition. This is antithetical to socialistic mindsets. If this is you, carefully consider why you are starting a company.
The last and most important issue, academics are not curious about people which makes them poor leaders and low empathy for their users; This gives them a rough API and turn off many people. Founders must be able to close deals, attract/retain great talent, raise millions. That takes an interest in people. Even more so, you need to really empathize with your customer. Who buys (procurement), who uses it (the intern), who signs (the VP), who blocks (IT), and who suffers currently (?) are all the real variables and those a people problems. Sitting in on support calls, ask “what did you try before us?” and “what breaks right after you click ‘export’?” You’re building for real people. Dana who has 14 tabs open and a deadline in 12 minutes and just wants it to work. Be scholar-level curious about their pain, not beautiful ideas in your head. This is a major shift that needs to be practiced. 7 Habits of Highly Effective People and SPIN selling are my go to resources. If you are very poor on EQ, perhaps Dale C' How to win friends and influence people.