Keys to Building a High Impact Startup

Reflection and key takeaways from attending a Creative Destruction Lab session

Maggie Li
9 min readMar 12, 2020

The speed at which emerging tech is progressing is literally exponential.

And humans tend to think linearly. So, we don’t really understand the concept of ‘exponential growth’. We are living in a world that is likely unfathomable to someone who lived in the same world 20 years ago.

These areas, from artificial intelligence to quantum computing, are all tools that will be used to solve some of the world’s most complex problems.

Just to give you some perspective, we’re seeing some record amount of investments in these deep tech areas, like artificial intelligence and machine learning… if the field wasn’t going anywhere, venture capitalists and firms wouldn’t invest.

Image credits here

And every once in a while, we hear about trailblazers pushing industries forwards and making incredible progress. We hear about their startups and the amazing work they are doing.

However, not many individuals understand and/or witness the process of building and scaling a startup.

So, I was very lucky to have had the chance to experience and witness part of this process! I recently attended a Creative Destruction Lab session and shadowed Micah Siegel, an awesome mentor who shared many valuable insights (and I thought I’d share some of them)!

Why is this even relevant?

Well, to truly understand where all this is headed and what the future of the world will look like, I think it’s important to understand the behind the scenes work of these deep tech startups for 2 reasons:

  1. You’ll be able to better decipher what’s actually happening versus what is media hype. That’s an underrated skill to have.
  2. From developing the technology versus commercializing it, you’ll be able to better understand where the gaps are in the technology.

Common mistakes a startup could make (and how to avoid them)

Since we’re talking deep tech, the set of criteria for success is slightly different from what you would expect from a typical startup. Specifically, there may be stakes at hand in terms of the technical development of the product. It’s no longer just about building out innovative features or a software application, it’s about bringing the emerging technology to the user in a meaningful way.

That means, regardless of how technically advance the product is, if there is no market fit, you can say bye-bye to any hopes of funding or scaling.

And so, here are some of the common challenges the startups faced… and some of the reasons why certain startups were cut from the program stream.

1. There is no clear value proposition with the startup’s product because the startup lacks a sense of direction

Before any significant growth/scaling, it should be very clear what the unique value proposition of the startup’s product is. In terms of deep tech, that probably means having some MVP (minimal viable product) developed as early on as possible.

Why? Because the startup needs to back up what they say they can do. It’s simple — without a proof of concept, the concept is just fluff.

The technology can be incredibly exciting but feasibility and scalability can often be an entirely different story.

That means the best product might not be the most technically advanced one, but it’s just the most technically fitting one for the market.

If it isn’t clear half a year in why the product is better than what currently exists, then there’s probably something wrong.

In fact, having a sense of direction is so important because it helps the startup figure out which market verticals (essentially, specialized markets with very specific demands for products) they want to target. In other words, what are the various use cases for the product?

Some of the startups lacked this sense of direction and were either 1) spreading themselves too thin by trying to create a product that satisfied the demands of very different consumer groups or 2) had no clear target consumer groups so their product was just ‘out-there’.

2. The startup didn’t approach de-risking with a solid framework

Quick crash course on types of risk (shoutout to Micah for teaching me about this)! There are 3 types of risk that a startup should be concerned about:

  • Technology risk: the ‘what if’ questions with the technical part of the product… if the technology has not yet been developed, can it be developed and delivered by the startup in the promised timeframe?
  • Market risk: ‘what if’ questions about the market…is there a good market fit? Is the sufficient demand for the technical product? How competitive is the market? What does the revenue model look like (e.g recurring)?
  • Founder risk: ‘what if’ questions about the starter team… are they a good fit for each other and can they work well to deliver as a team? More about this in the next section…

In a nutshell, it’s asking these ‘what-if’ questions (that my grade one teacher told me to avoid asking). Of course, you should ask them in a relevant context.

In deep tech, mitigating tech risk was what I saw placed as the first priority for many of the startups who were scaling. However, if the team was confident they could deliver the desired outcome even with a high risk, then they could still chose to move forward. That means market and founder risk should be low.

So, in considering all these aspects risk (aka chance of failure), there shouldn’t be more than one area that has very high risk.

That’s why startups should come up with a framework for tackling and mitigating these 3 types of risks well ahead of scaling. In other words, a good game plan with plan A, plan B (if plan A doesn’t work), plan C (if plan B doesn’t work), plan D….

Some of the pitches that stood out to me where the ones where the founder(s) could explain their backup plans when the CDL mentors poked holes in their product and/or their methods of de-risking.

Backup plans, with a good framework for mitigating tech, market, and founder risk is key. If things fall through, then there needs to be something to fall back on.

And in terms of market risk, startups should avoid getting caught up in the media hype at all costs. I repeat, don’t get caught up with the hype — startups don’t need buzzwords in every line of their pitch to be successful or to prove their technical grit.

Sometimes, the product that is being built may not even require the application/integration of AI or ML. Sure, might sound a lot more exciting, but this doesn’t automatically mean the company is now building a better product.

3. The idea is great, but the execution isn’t

This is because execution < 50% of the process. The idea could be great, but if the execution is terrible, the startup is not going anywhere.

Good execution is about making good decisions and to make good decisions, the startup needs a strong team. That means building a team of decision makers and strong team culture very early on is incredibly important.

Having a strong and balanced team that complements each other in terms of skillsets and personality is half the battle uphill.

With respect to building a team, an interesting problem I’ve never thought of before was the background of the team. Often, the original founders of the team come from a very technical background, meaning they are not as experienced with respect to the business side of things. That means financing, legal concerns (over the data collected, over the patents)… and so on.

In fact, the question of ‘to be a CEO or not to be a CEO’ is a nuanced and tortured question for many startup founders, ‘and the decision on whether the product founder maintains a CEO title or not is far more complicated than you might think’. Read this article from a16z for more interesting perspectives.

Whether to bring on an external CEO or not is a important question to ask throughout the process of building the startup, because if the technical founder(s) are overwhelmed with the financing/business side of things, then their ability to build up their technical product quickly and constantly iterate and implement user feedback will likely be hindered.

Interestingly, there were actually several startups in the stream that encountered this exact problem.

4. The team doesn’t move fast enough and constantly iterate on feedback

Startups should not wait until the product is perfect. There should be constant iteration on the product and constant collection of user feedback. If there is no MVP or demo of the product, then there is no way to collect feedback.

It’s important to move fast and fail fast. Collecting feedback is the best way to 10x growth.

In fact, investors invest in founder(s) and not necessarily the startup. They are looking for specific traits in the founder(s) and one of the most important ones (as a common thread throughout the day) was coachability.

The founder(s) and team needs to be able to take the feedback of their mentors and investors (who often have more experience and have seen startups fail) into consideration and act on it.

In fact, there were stories about startups who completely pivoted their product after re-evaluating their market fit. Being able to move fast enough in order to realize the need to pivot early on attributed to their successes. Had they not pushed out a MVP, it would have likely been more difficult to effectively evaluate the market fit.

On the founder(s) themselves

Before I end off, I’d also like to share some of the common traits / soft skills that stood out to me throughout the day. The strongest founder(s) had the following:

  • The ability to pitch (strong communication skills): that means the ability to be concise and clear. The founder(s) that impressed the investors sold their idea well made it clear what they were working on in the first few seconds, taking a top down approach. Don’t waste time!
  • Flexibility and openness: being able to pivot quickly and being open to feedback means the founder(s) will be able to maximize their learning from others (who are giving advice) and from their failures.
  • Passion: this is probably not a skill, but if the founder(s) are not passionate and invested in what they are doing, then the interest of potential investors and mentors also falls. This passion translates to determination in the long term, and the ability to perserve and continue working on the startup even when times are rough.
  • Ability to think long term: founder(s) need to be able to grasp and understand the big picture (e.g. what the startup will look like/be doing in 5 years… 10 years) and how to get there + the obstacles to overcome.
  • Ability to make good decisions: decision making attributes greatly to a startup’s success. Founder(s) need to consider opportunity cost and have good frameworks for making all kinds of decisions, from business ones to technical ones.

TL;DR

Common mistakes startups make:

  • There is no clear value proposition with the startup’s product because the startup lacks a sense of direction. It’s important to consider market verticals and market fit for the product very early on.
  • The startup didn’t approach de-risking with a solid framework. 3 areas of risk to address: technical, market, and founder.
  • The idea is great, but the execution isn’t. There needs to be a strong and balanced team with complementary skillsets and personalities.
  • The team doesn’t move fast enough and constantly iterate on feedback. It’s important to move fast and fail fast.

Important traits founders should have:

  • Ability to pitch (strong communication skills)
  • Flexibility to pivot and openness to feedback
  • Passion for what they do + determination to preserve
  • Ability to think long term
  • Ability to make good decisions (and evaluate opportunity costs)

Before I end off, I’d like to give a few shoutouts and thank yous!

  • The awesome CDL team for organizing the HSGP program, which gives the opportunity for high school students to shadow VCs and mentors at CDL for a day. Special thank you to Garima, Valerie, and Malaika!
  • To all the awesome individuals that I met and had a conversation with (long or short). Thank you to Micah Siegel, Elizabeth Caley, Medhi Bozzo-Rey, Liran Belenzon, Barney Pell, and Sonia Sennik!

I learned so much about what is currently happening in the AI space, thanks to all the awesome people mentioned above. This experience was ridiculously valuable and I hope to attend CDL again in the future! 🙏

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