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Kenshin Thoughts Posts

Difference between CTO and VP of Engineering

This is a consecutive post to Difference Between Co-founder and Founding Member. In fact, the previous post is one of the most read articles on this website indicating many people are constantly looking for the answer to it, which lead me to write this post because I have my own definition between two.

First, I’d like to make my version of concise definition as below.

“CTO is a person who has the most technical knowledge in management team. VP of Engineering is a person who manages engineering team.”

Now, let’s break them into smaller pieces. Amongst many differences between these two types of people, there is a clear distinction in terms of which team in the company he/she belongs to. CTO is considered as a member of management team or often board members. Thus, CTO belongs to the same team to where other C-level people belong including CEO.

On the other hand, VP of Engineering is considered as a member or head of engineering team. Therefore, VP of Engineering belongs to the same team to where other employees belong. Perhaps, there are few startups or companies that appoint VP of Engineering to be a board member.

To make it even clearer, the biggest difference is what these two types of people represent. CTO represents a management team and speaks to employees. VP of Engineering represents an engineering team and speaks to the management team. A direction of communication is completely opposite each other.

More importantly, this is my own perception by the way, CTO was chosen just because he/she happens to be the most technical person in other C-level people. Due to this nature, a language spoken in two parties is also different.

In management team, the official language is business. Everyone in management team talks from business perspective since other C-level people most likely may not understand technical terminologies so that CTO should not use these technical terminologies in board meeting. In engineering team, the official language is of course technical. They are allowed to use any technical terminologies in order to proceed their projects.

A role of CTO is to come up with the means to implement a business decision made by the management team based on outcome from engineering team. A role of VP of Engineering to come up with and experiment the technical solutions toward a problem given by CTO and provide the best possible solution to CTO with reasonable explanation.

Sometimes I happen to encounter a startup lead by young CEO where their CTO is constantly talking about technical details in board meeting. If it’s absolutely necessarily, then it’s okay. But most often, it’s just CTO doing a job of VP of Engineering.

If CTO continues this behavior, then VP of Engineering will start doing a job which people at one level lower are supposed to do. Eventually, the startup will end with paying salary to a whole engineering team where everyone in engineering team is doing a job on which people at one level lower should be working. This is the situation to be avoided, particularly for startup with cash constraint.

Remember, the official language CTO is supposed to use in board meeting is business, not technical. Otherwise, he/she won’t be able to communicate with CEO/CFO/COO/CMO and other C-level people fully. In other words, if VP of Engineering wants to step up to CTO, then he/she must be equipped with some business knowledge at least.

a16z Podcast: Taking the Pulse on Bio

As a CEO of digital health startup, I could not miss this one.

Bioengineering can also benefit from unsupervised learning approach as discussed in another a16z podcast by letting AI show us the unique features that lead to a theory (or CRISPER) rather than having a human ‘guess’ it. There is no doubt that quantum computing will play an important role here in the near future.

I’m 100% certain that new type of entrepreneur who understands both bioengineering and computer science (perhaps, quantum computing) will attract so much attention from VCs as a bio industry needs this kind of talent.

Well, I gotta go back to college and study bioengineering again. :)

American startup disrupting Japanese sushi industry

This Week in Startups episode 783: Jason speaks with Finless Foods co-founder and CEO Mike Selden about how his company produces real fish meat from stem cells, the increasing scarcity of healthy and affordable seafood, more

Finless Foods looks very interesting and promising to me, but at the same time the existence of this startup concerns me being a native Japanese loving sushi so much.

This kind of innovation should happen within Japan, a country surrounded by sea and lived with it for long time, not America. Looking at it from different angle, what we are seeing here is a American startup disrupting Japanese sushi industry.

I’m not talking about Japan vs the rest of the world or anything like that. I’m talking about Japanese government and Japanese startups only trying to ‘rescue’ the people in fishing industry either by pouring millions of dollars of grants into the industry or partially automating the process where human used to do with the help of IT and robotics. Needless to say, both are not considered true innovation.

I’m based out of Kyoto, and we have a top-notch stem cell scientists at Kyoto University which is known as the driving force behind a Nobel prize winning iPS (induced pluripotent stem cell) technology.

Why aren’t we seeing a startup like this here? Should I convince someone to do that? Should I make an angel invest into the startup working on a similar topic and turn around? Or, am I the one who is supposed to get it done myself?

Hmm. There are so many things to work on, but I got a single life to spend. Life is too short indeed.

a16z Podcast: AI, from ‘Toy’ Problems to Production

I like this “end of theory” approach. Some businesses might not need a theory about what’s correct outcome will look like. In other words, AI deployment in the future will always start with unsupervised learning, let the AI tell us unique features, and then define a problem to solve from what the algorithm told us.

Plus, it’s no more about how to implement AI or what technique to use given that the technologies like TensorFlow are available for everyone today. As the podcast says, a couple of data scientists can start a real AI business within few days using these ready-to-use technologies.

It’s about how you pick which business problem to solve in terms of ROI. If you apply a cutting-edge technique to a problem that does not have a meaningful business impact at the company you are talking to, then the whole project is considered as ‘failure.’ You are simply solving a wrong problem.

So my conclusion is that as AI technologies are commoditized the startups whose strength is only technology will eventually go out of business. Instead, the startups that can tell a customer which problem to solve and contribute to the customer’s ROI will stay in business. Sometimes it results in denying what the customer wants to do with AI.

To do that, what you need is not a data scientist or software developer. You need a new type of business person who can take advantage of unsupervised learning and lead a customer in the right direction.

I also agree that a key differentiator will be domain expertise and not AI technology itself, meaning that a startup with the specific vertical focus such as medical imaging will stand out from others. I think this is true for both supervised and unsupervised learning.

Fireside Chat by Tom Foley SilverEgg

Awesome fireside chat by Tom Foley, CEO of SilverEgg, that just filed IPO recently.

Interesting to hear the story about the company that raised $7M and went through a complete reset of business after burning it. It must be super difficult when doing reset.

It was the most appropriate talk as the last session at 500 Kobe Pre-Accelerator program.