Y Combinator President Geoff Ralston shares actionable advice for startup founders

Running a startup accelerator comes with a number of occupational hazards, but “skepticism is the easiest thing to fall into when you’ve seen too many companies,” said Y Combinator President Geoff Ralston, “and it’s the thing you have to avoid the most.”

Ralston joined me last week for an hour-long Extra Crunch Live interview where we talked about several topics, including how YC has adapted its program during the pandemic, why he has “never stopped coding” and what he sees changing in tech.

“We try to not be too smart, because great founders often see things beyond what you’re seeing,” he said. “If you try to be too smart, you’ll miss the Airbnbs of the world. You’ll say ‘Airbeds in peoples houses? That’s stupid! I’m not going to invest in that,’ and you could’ve bought 10% of Airbnb for like nothing back then… 10% of that company… you can do your own math.”


Extra Crunch Live is our new virtual event series where we sit down with some of the top founders, investors and builders in tech to glean every bit of insight they care to share. We’ve recently been joined by folks like Hunter Walk, Kirsten Green and Mark Cuban.

To watch the entire interview with Geoff Ralston, sign up for ExtraCrunch — but once you’ve got that covered, you can find it (and a bunch of key excerpts from the chat!) below.


Advice for getting into YC

I prefer it when an Extra Crunch Live conversation starts out with actionable advice, so we kicked things off with any suggestions Ralston had for folks looking to apply to YC. And he had plenty! Such as:

  • Mind the deadline, but all hope is not lost if you miss it: “If you miss the deadline, it’s not the end of the world,” says Ralston. “Don’t tell anyone on the admissions team that I said this, but it’s a little bit of a soft deadline. We would never turn down the next epic company because you missed the deadline… although your odds go down of getting in if you don’t make it in by [the deadline]. Why shouldn’t your odds be as high as possible?”
  • Don’t change things up for YC’s sake: “Do whatever you can do to make your company as successful, as real as possible… but don’t try to like, pretty up your company for YC,” he says. “That’s never smart [to do] for an investor. Don’t make bad short-term decisions because you think there’s a deadline that you should do wrong things for. Instead, build your company for the long term, and do the best you can possibly do to find product market fit, to build the right product, to build the right technology, to build the right software or whatever it is you’re building.”

Later in the video (around the 40:55 mark), a question from the audience leads Ralston back to the topic, and he has a few more pieces of advice:

  • Stick to the instructions: “The instructions are fairly clear. It says: do a one-minute video, have all the founders there, and talk to us. That’s a good idea! Don’t give us some marketing video, we’re not interested in that. That’s not how we’re making our decision.”
  • Hone your pitch: “Think about expressing yourself concisely, with great clarity. It does not help to write a book in the application. Be kind to us! We’re reading, you know, hundreds of applications. Get your idea across as clearly as you can. That’s actually a really good signal to us, if you can describe what you’re doing with a minimum of words. That helps us a ton.”
  • Tell your story: “Do not skimp on talking about yourselves!” Ralston notes. “We are super interested in you, who you are, and why you’re doing what you’re doing.”

VenoStent has a new technology to improve outcomes for dialysis patients

Timothy Bouré and his co-founder Geoffrey Lucks were both near broke when they moved to Dallas to join the first accelerator they entered after forming VenoStent, a company that aims to improve outcomes for dialysis patients.

Failed dialysis surgeries occur in roughly 55% to 65% of patients with end-stage renal disease, according to the company. Caring for these patients can cost the Medicare and Medicaid Services system roughly $2 billion per year — and Bouré and Lucks believed that they’d come up with a solution.

So after years developing the technology at the core of VenoStent’s business at Vanderbilt University, the two men relocated from Nashville to South Texas to make their business work.

Bouré had first started working on the technology at the heart of VenoStent’s offering as part of his dissertation in 2012. Lucks, a graduate student at the business school was introduced to the material scientist and became convinced that VenoStent was on the verge of having a huge impact for the medical community. Five years later, the two were in Dallas where they met the chief of vascular surgery at Houston Medicine and were off to the races.

A small seed round in 2018 kept the company going and a successful animal trial near the end of the year gave it the momentum it needed to push forward. Now, as it graduates from the latest Y Combinator cohort, the company is finally ready for prime time.

In the interim, a series of grants and its award of a Kidney XPrize kept the company in business.

The success was hard won, as Bouré spent nearly three sleepless nights in the J-Labs, Johnson and Johnson’s  medical technology and innovation accelerator in Houston, synthesizing polymers and printing the sleeve stents that the company makes to keep replace the risky and failure-prone surgeries for end stage kidney disease patients.

The key discovery that Bouré made was around a new type of polymer that can be used to support cell growth as it heals from the dialysis surgery.

In 2012, Bouré stumbled upon the polymer that would be the foundation for the work. Then, in 2014, he did the National Science Foundation Core program and started thinking about the wrap for blood vessels. Through a series of discussions with vascular surgeons he realized that the problem was especially acute for end stage renal disease patients.

Already the company has raised $2.4 million in grant funding and small equity infusions. and the KidneyX Prize from the Department of Health and Human Services and the American Society of Nephrology. VenoStent was one of six winners.

“It’s part of this whole ongoing effort by the executive office to improve dialysis,” said Bouré. “[They are] some of the most expensive patients to treat in the world… Basically the government is highly incentivized to find technologies that improve patient’s lives.”

Now the company is heading into its next round of animal testing and will seek to conduct its first human trials outside of the United States in 2021.

And while the company is focused on renal failure first, the materials that Bouré has developed have applications for other conditions as well. “This can be a material for the large intestine,” says Bouré. “It has tunability in terms of all its properties. And we can modify it for a particular application.”

 

Hypotenuse AI wants to take the strain out of copywriting for ecommerce

Imagine buying a dress online because a piece of code sold you on its ‘flattering, feminine flair’ — or convinced you ‘romantic floral details’ would outline your figure with ‘timeless style’. The very same day your friend buy the same dress from the same website but she’s sold on a description of ‘vibrant tones’, ‘fresh cotton feel’ and ‘statement sleeves’.

This is not a detail from a sci-fi short story but the reality and big picture vision of Hypotenuse AI, a YC-backed startup that’s using computer vision and machine learning to automate product descriptions for ecommerce.

One of the two product descriptions shown below is written by a human copywriter. The other flowed from the virtual pen of the startup’s AI, per an example on its website.

Can you guess which is which?* And if you think you can — well, does it matter?

Screengrab: Hypotenuse AI’s website

Discussing his startup on the phone from Singapore, Hypotenuse AI’s founder Joshua Wong tells us he came up with the idea to use AI to automate copywriting after helping a friend set up a website selling vegan soap.

“It took forever to write effective copy. We were extremely frustrated with the process when all we wanted to do was to sell products,” he explains. “But we knew how much description and copy affect conversions and SEO so we couldn’t abandon it.”

Wong had been working for Amazon, as an applied machine learning scientist for its Alexa AI assistant. So he had the technical smarts to tackle the problem himself. “I decided to use my background in machine learning to kind of automate this process. And I wanted to make sure I could help other ecommerce stores do the same as well,” he says, going on to leave his job at Amazon in June to go full time on Hypotenuse.

The core tech here — computer vision and natural language generation — is extremely cutting edge, per Wong.

“What the technology looks like in the backend is that a lot of it is proprietary,” he says. “We use computer vision to understand product images really well. And we use this together with any metadata that the product already has to generate a very ‘human fluent’ type of description. We can do this really quickly — we can generate thousands of them within seconds.”

“A lot of the work went into making sure we had machine learning models or neural network models that could speak very fluently in a very human-like manner. For that we have models that have kind of learnt how to understand and to write English really, really well. They’ve been trained on the Internet and all over the web so they understand language very well. “Then we combine that together with our vision models so that we can generate very fluent description,” he adds.

Image credit: Hypotenuse

Wong says the startup is building its own proprietary data-set to further help with training language models — with the aim of being able to generate something that’s “very specific to the image” but also “specific to the company’s brand and writing style” so the output can be hyper tailored to the customer’s needs.

“We also have defaults of style — if they want text to be more narrative, or poetic, or luxurious —  but the more interesting one is when companies want it to be tailored to their own type of branding of writing and style,” he adds. “They usually provide us with some examples of descriptions that they already have… and we used that and get our models to learn that type of language so it can write in that manner.”

What Hypotenuse’s AI is able to do — generate thousands of specifically detailed, appropriately styled product descriptions within “seconds” — has only been possible in very recent years, per Wong. Though he won’t be drawn into laying out more architectural details, beyond saying the tech is “completely neural network-based, natural language generation model”.

“The product descriptions that we are doing now — the techniques, the data and the way that we’re doing it — these techniques were not around just like over a year ago,” he claims. “A lot of the companies that tried to do this over a year ago always used pre-written templates. Because, back then, when we tried to use neural network models or purely machine learning models they can go off course very quickly or they’re not very good at producing language which is almost indistinguishable from human.

“Whereas now… we see that people cannot even tell which was written by AI and which by human. And that wouldn’t have been the case a year ago.”

(See the above example again. Is A or B the robotic pen? The Answer is at the foot of this post)

Asked about competitors, Wong again draws a distinction between Hypotenuse’s ‘pure’ machine learning approach and others who relied on using templates “to tackle this problem of copywriting or product descriptions”.

“They’ve always used some form of templates or just joining together synonyms. And the problem is it’s still very tedious to write templates. It makes the descriptions sound very unnatural or repetitive. And instead of helping conversions that actually hurts conversions and SEO,” he argues. “Whereas for us we use a completely machine learning based model which has learnt how to understand language and produce text very fluently, to a human level.”

There are now some pretty high profile applications of AI that enable you to generate similar text to your input data — but Wong contends they’re just not specific enough for a copywriting business purpose to represent a competitive threat to what he’s building with Hypotenuse.

“A lot of these are still very generalized,” he argues. “They’re really great at doing a lot of things okay but for copywriting it’s actually quite a nuanced space in that people want very specific things — it has to be specific to the brand, it has to be specific to the style of writing. Otherwise it doesn’t make sense. It hurts conversions. It hurts SEO. So… we don’t worry much about competitors. We spent a lot of time and research into getting these nuances and details right so we’re able to produce things that are exactly what customers want.”

So what types of products doesn’t Hypotenuse’s AI work well for? Wong says it’s a bit less relevant for certain product categories — such as electronics. This is because the marketing focus there is on specs, rather than trying to evoke a mood or feeling to seal a sale. Beyond that he argues the tool has broad relevance for ecommerce. “What we’re targeting it more at is things like furniture, things like fashion, apparel, things where you want to create a feeling in a user so they are convinced of why this product can help them,” he adds.

The startup’s SaaS offering as it is now — targeted at automating product description for ecommerce sites and for copywriting shops — is actually a reconfiguration itself.

The initial idea was to build a “digital personal shopper” to personalize the ecommerce experence. But the team realized they were getting ahead of themselves. “We only started focusing on this two weeks ago — but we’ve already started working with a number of ecommerce companies as well as piloting with a few copywriting companies,” says Wong, discussing this initial pivot.

Building a digital personal shopper is still on the roadmap but he says they realized that a subset of creating all the necessary AI/CV components for the more complex ‘digital shopper’ proposition was solving the copywriting issue. Hence dialling back to focus in on that.

“We realized that this alone was really such a huge pain-point that we really just wanted to focus on it and make sure we solve it really well for our customers,” he adds.

For early adopter customers the process right now involves a little light onboarding — typically a call to chat through their workflow is like and writing style so Hypotenuse can prep its models. Wong says the training process then takes “a few days”. After which they plug in to it as software as a service.

Customers upload product images to Hypotenuse’s platform or send metadata of existing products — getting corresponding descriptions back for download. The plan is to offer a more polished pipeline process for this in the future — such as by integrating with ecommerce platforms like Shopify .

Given the chaotic sprawl of Amazon’s marketplace, where product descriptions can vary wildly from extensively detailed screeds to the hyper sparse and/or cryptic, there could be a sizeable opportunity to sell automated product descriptions back to Wong’s former employer. And maybe even bag some strategic investment before then…  However Wong won’t be drawn on whether or not Hypotenuse is fundraising right now.

On the possibility of bagging Amazon as a future customer he’ll only say “potentially in the long run that’s possible”.

Joshua Wong (Photo credit: Hypotenuse AI)

The more immediate priorities for the startup are expanding the range of copywriting its AI can offer — to include additional formats such as advertising copy and even some ‘listicle’ style blog posts which can stand in as content marketing (unsophisticated stuff, along the lines of ’10 things you can do at the beach’, per Wong, or ’10 great dresses for summer’ etc).

“Even as we want to go into blog posts we’re still completely focused on the ecommerce space,” he adds. “We won’t go out to news articles or anything like that. We think that that is still something that cannot be fully automated yet.”

Looking further ahead he dangles the possibility of the AI enabling infinitely customizable marketing copy — meaning a website could parse a visitor’s data footprint and generate dynamic product descriptions intended to appeal to that particular individual.

Crunch enough user data and maybe it could spot that a site visitor has a preference for vivid colors and like to wear large hats — ergo, it could dial up relevant elements in product descriptions to better mesh with that person’s tastes.

“We want to make the whole process of starting an ecommerce website super simple. So it’s not just copywriting as well — but all the difference aspects of it,” Wong goes on. “The key thing is we want to go towards personalization. Right now ecommerce customers are all seeing the same standard written content. One of the challenges there it’s hard because humans are writing it right now and you can only produce one type of copy — and if you want to test it for other kinds of users you need to write another one.

“Whereas for us if we can do this process really well, and we are automating it, we can produce thousands of different kinds of description and copy for a website and every customer could see something different.”

It’s a disruptive vision for ecommerce that is likely to either delight or terrify — depending on your view of current levels of platform personalization around content. That process can wrap users in particular bubbles of perspective — and some argue such filtering has impacted culture and politics by having a corrosive impact on the communal experiences and consensus which underpins the social contract. But the stakes with ecommerce copy aren’t likely to be so high.

Still, once marketing text/copy no longer has a unit-specific production cost attached to it — and assuming ecommerce sites have access to enough user data in order to program tailored product descriptions — there’s no real limit to the ways in which robotically generated words could be reconfigured in the pursuit of a quick sale.

“Even within a brand there is actually a factor we can tweak which is how creative our model is,” says Wong, when asked if there’s any risk of the robot’s copy ending up feeling formulaic. “Some of our brands have like 50 polo shirts and all of them are almost exactly the same, other than maybe slight differences in the color. We are able to produce very unique and very different types of descriptions for each of them when we cue up the creativity of our model.”

“In a way it’s sometimes even better than a human because humans tends to fall into very, very similar ways of writing. Whereas this — because it’s learnt so much language over the web — it has a much wider range of tones and types of language that it can run through,” he adds.

What about copywriting and ad creative jobs? Isn’t Hypotenuse taking an axe to the very copywriting agencies his startup is hoping to woo as customers? Not so, argues Wong. “At the end of the day there are still editors. The AI helps them get to 95% of the way there. It helps them spark creativity when you produce the description but that last step of making sure it is something that exactly the customer wants — that’s usually still a final editor check,” he says, advocating for the human in the AI loop. “It only helps to make things much faster for them. But we still make sure there’s that last step of a human checking before they send it off.”

“Seeing the way NLP [natural language processing] research has changed over the past few years it feels like we’re really at an inception point,” Wong adds. “One year ago a lot of the things that we are doing now was not even possible. And some of the things that we see are becoming possible today — we didn’t expect it for one or two years’ time. So I think it could be, within the next few years, where we have models that are not just able to write language very well but you can almost speak to it and give it some information and it can generate these things on the go.”

*Per Wong, Hypotenuse’s robot is responsible for generating description ‘A’. Full marks if you could spot the AI’s tonal pitfalls

The rules of VC are being broken

Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast (now on Twitter!), where we unpack the numbers behind the headlines.

As ever I was joined by TechCrunch managing editor Danny Crichton and our early-stage venture capital reporter Natasha Mascarenhas. We had Chris on the dials and a pile of news to get through, so we were pretty hype heading into the show.

But before we could truly get started we had to discuss Cincinnati, and TikTok. Pleasantries and extortion out of the way, we got busy:

It was another fun week! As always we appreciate you sticking with and supporting the show!

Equity drops every Monday at 7:00 a.m. PT and Friday at 6:00 a.m. PT, so subscribe to us on Apple PodcastsOvercastSpotify and all the casts.

YC-backed Statiq wants to bootstrap India’s EV charging network

Electric vehicles (EVs) are spreading throughout the world. While Tesla has drawn the most attention in the United States with its luxurious and cutting-edge cars, EVs are becoming a mainstay in markets far away from the environs of California.

Take India for instance. In the local mobility market, two- and three-wheel vehicles are starting to emerge as a popular option for a rapidly expanding middle class looking for more affordable options. EV versions are popular thanks to their reduced maintenance costs and higher reliability compared to gasoline alternatives.

Two-wheeled electric scooters are a fast-growing segment of India’s mobility market.

There’s just one problem, and it’s the same one faced by every country which has attempted to convert from gasoline to electric: how do you build out the charging station network to make these vehicles usable outside a small range from their garage?

It’s the classic chicken-and-egg problem. You need EVs in order to make money on charging stations, but you can’t afford to build charging stations until EVs are popular. Some startups have attempted to build out these networks themselves first. Perhaps the most famous example was Better Place, an Israeli startup that raised $800 million in venture capital before dying from negative cash flow back in 2013. Tesla has attempted to solve the problem by being both the chicken and egg by creating a network of Superchargers.

That’s what makes Statiq so interesting. The company, based in the New Delhi suburb of Gurugram, is bootstrapping an EV charging network using a multi-revenue model that it hopes will allow it to avoid the financial challenges that other charging networks have faced. It’s in the current Y Combinator batch and will be presenting at Demo Day later this month.

Akshit Bansal and Raghav Arora, the company’s co-founders, worked together previously as consultants and built a company for buying photos online, eventually reaching 50,000 monthly actives. They decided to make a pivot — a hard pivot really — into EVs and specifically charging equipment.

Statiq founders Raghav Arora and Akshit Bansal. Photos via Statiq

“We felt the need to do something about the climate because we were living in Delhi and Delhi is one of the most polluted cities in the world, and India is home to a lot of the polluted cities in the world. So we wanted to do something about it,” Bansal said. As they researched the causes of pollution, they learned that automobile exhaust represented a large part of the problem locally. They looked at alternatives, but EV charging stations remain basically non-existent across the country.

Thus, they founded Statiq in October 2019 and officially launched this past May. They have installed more than 150 charging stations in Delhi, Bangalore, and Mumbai and the surrounding environs.

Let’s get to the economics though, since that to me is the most fascinating part of their story. Statiq as I noted has a multi-revenue model. First, end users buy a subscription from Statiq to use the network, and then users pay a fee per charging session. That session fee is split between Statiq and the property owner, giving landlords who install the stations an incremental revenue boost.

A Statiq charging station. Photo via Statiq

When it comes to installation, Statiq has a couple of tricks up its sleeves. First, the company’s charging equipment — according to Bansal — costs roughly a third of the equivalent cost of U.S. equipment. That makes the base technology cheaper to acquire. From there, the company negotiates installations with landlords where the landlords will pay the fixed costs of installation in exchange for that continuing session charge fee.

On top of all that, the charging stations have advertising on them, offering another income stream particularly in high-visibility locations like shopping malls which are critical for a successful EV charging network.

In short, Statiq hasn’t had to outlay capital in order to put in place their charging equipment — and they were able to bootstrap before applying to YC earlier this year. Bansal said the company had dozens of charging stations and thousands of paid sessions on its platform before joining their YC batch, and “we are now growing 20% week-over-week.”

What’s next? It’s all about deliberate scaling. The EV market is turning on in India, and Statiq wants to be where those cars are. Bansal and his co-founder are hoping to ride the wave, continuing to build out critical infrastructure along the way. India’s government will likely continue to help: its approved billions of dollars in incentives for EVs and for charging stations, tipping the economics even further in the direction of a clean car future.

OneKey wants to make it easier to work without a desktop by integrating apps into mobile keyboards

“The app that you use the most on your phone and you don’t realize it is your keyboard,” says Christophe Barre the co-founder and chief executive of OneKey.

A member of Y Combinator’s most recent cohort, OneKey has a plan to make work easier on mobile devices by turning the keyboard into a new way to serve up applications like calendars, to-do lists, and, eventually, even Salesforce functionality.

People have keyboards for emojis, other languages, and gifs, but there have been few ways to integrate business apps into the keyboard functionality, says Barre. And he’s out to change that.

Right now, the company’s first trick will be getting a Calendly-like scheduling app onto the keyboard interface. Over time, the company will look to create modules that they can sell in an app-store style marketplace for the keyboard space on smartphones.

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For Barre, the inspiration behind OneKey was the time spent working in Latin America and primarily conducting business through WhatsApp. The tool was great for messaging, but enterprise functionality broke down across for scheduling or other enterprise app integrations.

“People are doing more and more stuff on mobile and it’s happening right now in business,” said Barre. “When you switch from a computer-based world to a mobile phone, a lot of the productivity features disappear.”

Barre, originally from the outskirts of Paris, traveled to Bogota with his partner. She was living there and he was working on a sales automation startup called DeepLook. Together with his DeepLook co-founder (and high school friend), Ulysses Pryjiel, Barre set out to see if he could bring some of the business tools he needed over to the mobile environment.

The big realization for Barre was the under-utilized space on the phone where the keyboard inputs reside. He thinks of OneKey as a sort of browser extension for mobile phones, centered in the keyboard real estate.

“The marketplace for apps is the longterm vision,” said Barre. “That’s how you bring more and more value to people. We started with those features like calendars and lists that brought more value quickly without being too specialized.”

The idea isn’t entirely novel. SwiftKey had a marketplace for wallpapers, Barre said, but nothing as robust as the kinds of apps and services that he envisions.

“If you can do it in a regular app, it’s very likely that you can do it through a keyboard,” Barre said.

The iron rule of founder compensation is dead

Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast (now on Twitter!), where we unpack the numbers behind the headlines.

We had the full team this week: Myself, Danny and Natasha on the mics, with Chris running skipper as always.

Sadly this week we had to kick off with a correction as I am 1) dumb, and, 2) see point one. But after we got past SPAC nuances (shout-out to David Ethridge), we had a full show of good stuff, including:

And that’s Equity for this week. We are back Monday morning early, so make sure you are keeping tabs on our socials. Hugs, talk soon!

Equity drops every Monday at 7:00 a.m. PT and Friday at 6:00 a.m. PT, so subscribe to us on Apple PodcastsOvercastSpotify and all the casts.

Extra Crunch Live: Join Y Combinator’s Geoff Ralston for a live chat today at 12pm PT/3pm ET

How has Y Combinator adapted its accelerator program to work through a pandemic? What does YC look for in a company in a year as rocky and unpredictable as this one?

Y Combinator President Geoff Ralston will join us on Extra Crunch Live later today to talk about all this and more, starting at 12 p.m PT/3 p.m ET.

Want to tune in? EC Members can find details for the live Zoom Q&A down below — and if you’re watching along live, you’ll be able to submit questions of your own.

Extra Crunch Live: Join our Q&A tomorrow at noon PDT with Y Combinator’s Geoff Ralston

From Airbnb to Zapier, and Coinbase to Instacart, many of the tech world’s most valuable companies spent their earliest days in Y Combinator’s accelerator program.

Steering the ship at Y Combinator today is its president, Geoff Ralston . We’re excited to share that Ralston will be joining us on Extra Crunch Live tomorrow at noon pacific.

Extra Crunch Live is our virtual speaker series, with each session packed with insight and guidance from the top investors, leaders and founders. This live Q&A is exclusive to Extra Crunch members, so be sure to sign up for a membership here.

Ralston took on the YC President role a little over a year ago shortly after Sam Altman stepped away to focus on OpenAI.

In the months since, Y Combinator has had to reimagine much about the way it operates; as the pandemic spread around the world, YC (like many organizations) has had to figure out how to work together while far apart. In the earliest weeks of the pandemic, this meant quickly shifting their otherwise in-person demo day online; later, it meant adapting the entire accelerator program to be completely remote.

While still relatively new to the president seat, Ralston is by no means new to YC. He joined the accelerator as a partner in 2012, and his edtech-focused accelerator Imagine K12 was fully merged into YC’s operations in 2016.

VC Garry Tan shares 3 ways founders screw up their startups

There are many painful ways for a startup to fail — including founders who ultimately throw in the towel and turn off the lights.

But assuming a founder intends to keeps moving forward, there are a few pitfalls that Garry Tan has seen during his career as a founder, Y Combinator partner and, lately, co-founder of venture firm Initialized Capital.

During a fun chat during last week’s TechCrunch Early Stage, he ran us through these avoidable mistakes; for those who couldn’t virtually attend, we’re sharing them with you here.

 1. Chasing the wrong problem

This sounds insane, right? How can you be blamed for wanting to solve a problem?

Tan says people choose the wrong problem for a wide variety of reasons: Founders sometimes choose a problem that isn’t problematic for enough people, he said, citing the example of a hypothetical 25-year-old San Francisco-based engineer who may be out of touch with the rest of the country. When founders target the wrong problem, it typically means that the market will be too small for a venture-like return.