Machine learning · Minimum Viable Product

Is it ok to have a part-time CTO?

April 29th, 2016

I am trying to recruit someone with expertise in machine learning to help me get to the MVP. He works for Google and does not want to quit to work full-time on this but would be glad to help out part time with key algorithms (which are way beyond the average web / app developer). Should I find another full-time CTO while asking him to work on the algorithms only? Would equity be in the equation in that case?

Rob G

April 29th, 2016

Anh, do what ever you need to do to move the ball forward each day. If you are convinced this guy can do the work then bring him on part time. You may learn you can't work together or he may decide he love's what you are doing and decide to jump full time. while he is part time you can continue to look for a FT partner. If the 2 of you can agree on equity (and a vesting schedule) then go for it. If the alternative is no progress then that is really no option. keep moving.

Joseph Wang Chief Science Officer at Bitquant Research Laboratories

May 1st, 2016

Do whatever you need to do in order to get the business running. If you like the person and feel comfortable with the arrangement go with it. If not, then find someone else. Titles don't matter much. Just get the thing running.

The one gotcha that you'd have to watch out for is that make sure that you don't get into a situation where the person's current employer can make a claim for your IP, and this would be part of the discussion with the prospective CTO. I suspect that Google has pretty liberal policies when it comes to outside work (but you should ask the person), but I used to work for an investment bank, and they are much less open minded.

Graham Wert Co-Founder & CTO at ZenQMS and Mixette

April 29th, 2016

At this stage of your company, titles don't really mean all that much, so call the position whatever you or the candidate would like. Once you're past MVP and entering a growth phase, you can worry about titles, the org chart, etc.

Putting that aside, what you really need for the MVP is an engineer (or team) that has the skills and competence required to get the job done in the timeframe required. It sounds like you're looking for an individual who's within a subset of a small subset of people who are hard to find. If he's willing to do the work for reasonable compensation, I'd say go for it. If you're in a position to pay cash, then great, but equity is fine if you can arrive at an amount that you're both comfortable with, taking into account current risks and long term prospects.

Good luck!

Mikhail Gorelkin Principal AI Architect & Developer

April 29th, 2016

Unfortunately, this is a common misconception. CTO's responsibility is a domain of standard software engineering, but computational models and algorithms are different domains of computer science and computational engineering. You need to create another C: Chief Scientist and / or Chief Algorithm / AI Architect. Give him such a position.

Brett Gardner Serial Entrepreneur

April 29th, 2016

Does this guy plan to make the switch to full-time when the company gains traction?

1. If he is to be full-time CTO then it may be worth the time invested in waiting.

2. If he is not, what would be his roll other than providing those algorithms? If that is it then I would not give away equity. That will be a larger cost in the beginning to pay him for the time vested but in the end that equity is possibly something worth way more.

3. If you don't have the money, maybe look into Angel investments to get that guy paid. Angel's/VC's are in the business to protect and grow their money, so with them they have something to lose and will do whats best for the company (as a partner with vested money/equity)

Mikhail Gorelkin Principal AI Architect & Developer

April 29th, 2016

It depends on your product. If you are building a new kind of chatbots, this guy has to lead your vision, design, and all algorithmic programming. Give him a lot of your shares. The success will be defined mostly by his effort.

Neil Saunders http://clarity.fm/neilsaunders

April 30th, 2016

It is standard for the big tech companies to have an IP clause in employee contracts, so make sure that he is not bound contractually otherwise Google could own your algorithm!

Michael Barnathan Adaptable, efficient, and motivated

April 30th, 2016

Was going to say it but didn't want to be the first one to say it. Tell him he needs to get the outside activity approved by their Invention Reassignment Committee (note that this was a slow process that often took months while I was there). Google asserts ownership of all inventions made while employed there unless reassigned back to the author. Was the reason I left.

A. Andrew Chyne

May 1st, 2016

Equity would be the right option. Having a full time CTO would be the right step in machine learning. It is natural for someone who is passionate about his work to give his heart and soul into it. Part time would be good if the requirement is not much and if the work is not demanding at all. But a CTO is someone where every techie look up for direction.

Sam McAfee Building better technology leaders and teams

May 3rd, 2016

Some great responses here. I am going to take a slightly different approach. So, machine learning, right? You're trying to build a business that creates value in surfacing correlations in data that are difficult or impossible to do manually (or something to that effect). Great.

Do you have any market validation that it's time to jump straight into building the algorithm? In my (not directly hands on, but repeatedly nearby managing projects like this) understanding, there is quite a lot of work that goes into data acquisition, data cleaning, manually sorting through and guessing different correlations and weights that a data scientist would do that are way before actually implementing any algorithms. It seems like these bits of value that come from the statistics in the data could almost certainly be de-risked with more of a manual or concierge product way before you get to hiring your friend from Google. Have you pitched or acquired any beta customers to try this thing? Can you prove that there is a need for it?

I'll bet you could get a way with an MVP that has almost no actual AI in it. I could be totally wrong, but that's what I have experienced being around data science the last few years.

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