Hi Steven, can you start with an introduction to yourself, please?

SH: Hi, I’m Steven. Most recently I was the Chief Technology Officer for Clear AI, a London based tech startup democratising access to AI and ML for supply chain and logistics companies. My background is actually in evolutionary biology, although I’ve had a non-traditional career path. I started off in computer science in my undergrad, ended up in psychology, and took most of a degree in photography along the way (turns out I’m a terrible photographer). Then I ended up doing my Master’s in psychology and my PhD in biology.

I’ve been programming since I was a kid. I’m a biostatistician and was doing machine learning way before it was cool. I’ve completed two postdocs, the first was three years in Sydney, doing work in viral and bacterial evolution, as well as modelling, epidemiology and infectious disease – which feels very topical at the moment. Then I went to Los Angeles where I did work in population and behavioural genetics, genomics, and machine learning work for data analysis. Then, I faced that classic dilemma: getting on the tenure track and hunting a position for a few years or getting out and giving industry a try. My wife and I were in LA and she’d followed me across pretty much half the planet at this point, so I said “well, where do you want to go next?” and she said, “I’ve always wanted to live in London”. So, we got on a plane – no jobs, no idea what the hell we were doing. I actually started at a data science boot camp here, S2DS (which may be familiar to some of the readers).

During the programme, I got a job with Babylon Health. I was really very fortunate to be one of the early employees, especially in data science, and they were just starting to pivot into the AI space. Through luck and having the right background I ended up building their AI team from scratch. I built that up to about 60 people before I left and laid down a lot of their core technology (which is still there in use).  After that, I ended up joining Sensyne Health, which at the time was Drayson Technologies, as their CTO. We took that through to the early stage IPO that we did. I was actually working as CTO and COO by the time I left, and I built the team up to close to 100 people. After that, I joined Clear AI as CTO in September 2019.

Throughout your career you’ve built quite a few tech teams, talk us through some of the teams (both successful and unsuccessful) that you’ve been a part of building?

SH: I’ve tended to operate in the early to middle stage startups. I’m not running enterprise teams of 3000 people; I’m a lot more hands-on and I’m at the smaller end of that. I will happily take a team of four people and build it up to 100. This is actually my fifth startup in total. Two of them were very small, basically, two or three people in a garage style, which didn’t make it. As for Babylon Health, that was that was pretty much from scratch (on the AI side).  At Sensyne Health, I was doing that broadly throughout the whole tech organisation and I built both the dev teams and the AI and  ML teams there. And now we’re doing the same thing here at Clear AI.

Where have you seen the issues in building strong and diverse tech teams?

SH: That’s a good question. There’s a lot of issues. People think that talent is the big problem and to be fair, I actually disagree. This might be a bit controversial, but there is a focus in the industry that is encapsulated in the saying that ‘A’s hire A’s and B’s hire C’s’. The nominal idea behind that is that you go and you find your senior devs (the ones who’ve worked at Google and the other big names that you want to have on their CV) and you just shove them into a room and… magic. If you get a group of superstars into a room, you’ve just sorted your tech team. I’m vehemently against that idea. I view a team as a systems problem. I come from a philosophy and a line of thinking in things like systems biology, where you can understand what a cell does, but unless you understand it in the context of the biological system it’s embedded in you don’t know anything. And I think tech teams are very similar. I think to build a good tech team, there’s a lot of moving parts and you have to balance them off against each other. You want people constantly coming through your organisation growing in skill, levelling up and adding their own distinct viewpoints to what’s going on. You need to pay attention to the culture that they’re embedded in. You need to pay attention to the structures in the company that support and enable them.

It’s a frustrating thing to respond to as a question in some ways, because I’d like to say ‘well, if you do A, B and C, you’ve got it sorted’. But in reality, you’re constantly spinning a dozen plates and you have to make sure that they’re all in the air and they all interact with each other. If you don’t take that into account, you’re going to build a bad team. Now, the nice thing is, there’s a lot of really great tech teams out there and the people who build them are all smart people, and they tend to do this instinctually. You can get by, this isn’t an insurmountable task. What I’m really trying to say at the end is, I don’t think there’s a checklist. I think it’s a living systems problem that you have to deal with.

How would you advise building a team from scratch within a startup?

SH: Early stage startups are a bit of an odd beast. People often describe it as a business and I often say ‘errr, actually no’ as a business has an idea of what it’s doing. I view a startup (and this comes from the lean ideas from Eric Ries and so on) as being a search. A search for a scalable and repeatable business model. The whole organisation and the whole group of people in the room are about that search. The reason I say this, and the reason I focus on this, is because that searching, hypothesis testing and searchlight approach, where it’s moving around until it finds a target, means that your environment is constantly shifting. So, if you were to sit down and write a document that says ‘okay, I’m gonna hire three of these and I’m gonna hire two of those, and that’ll get me through the next six months’ and you’re at an early stage startup, frankly I don’t believe a word you’ve just written.

What I focus on instead when building this, is not so much a laundry list as it is getting good general-purpose people who have as broad a range of skills as possible, putting them in a room and then putting the structures around them to allow them to figure it out themselves. I’m not a command and control type, I like to push autonomy into the teams. I view my job as being about creating the environment that gives them the flexibility to do that, instead of prescribing what they do.

During your time at Clear AI, you created the ‘Clear Academy’, could you talk us through that in a little more detail? 

SH: So, this kind of starts from a problem I’ve seen building teams in the last five years and even before that in academia. This problem is well known and understood of the leaky pipeline and the lack of diversity and the overall homogeneity in tech is really bad. If you look around a room of people leading most tech companies in London and you won’t be surprised to see they all look like me – a straight white male.  I don’t have a way of just snapping my fingers and fixing it right now, but there are things that we can do. We can support the great work that’s being done on STEM education and trying to bring more people into the tent. I believe enormously that a diverse team is a stronger team. That heterogeneity of thought and background and experience and perspective gives you something that you cannot get any other way. You can’t buy that and you can’t manufacture it. It’s organic and it comes from having people in the room.

So, if we’re going to fix that now how do we do it? For me, it started when I was looking at some of the programmes in London and I came across one called codebar. Codebar is a fantastic organisation that works for people who are trying to transition into the dev space. They particularly focus on helping minorities, LGBTQ, and all the under-represented backgrounds who want to get into tech and don’t have another way. It’s a volunteer organisation and they run workshops here in London. At the same time, I was thinking about an academy idea for Clear, because I wanted to have a pipeline that helps bring that diversity and talent into the company. This is an investment of my time as well as the resources of the company. I’ve had a lot of support within the company, but I’ve been teaching two hours a day. That may seem like a strange thing for the CTO of a growing organisation to do, but I view our assets as being the people in the building and so every minute or every pound I spend on that, improving them and helping them to grow their skills, is something that makes us stronger. So I created Clear Academy within the company. That’s a grandiose name at the moment, let’s be honest, but I wanted to create it in order to formalise the fact that in this company we bring people in, we’ll train them, we will bring them up and I will make them a part of this team by giving them the skills necessary because I want to draw in from everywhere I can. This is where we meet Jillian, because I went to a codebar workshop and I was looking for the first person to be a part of this (and she’s probably not going to want me to describe her this way, but I was looking for a guinea pig).

It’s amazing to see you’ve done this. I think it’s something all tech companies should think about.

Jillian, it’s lovely to meet you. Could you give us a bit of an introduction to yourself?

JE: I’m Jillian, I’m originally from Queens, New York, and I recently just moved to London in August. My dad is from Camberwell, so I was quite familiar with London before moving here. I graduated from Queens College with a degree in math and I taught math for six years, three years at a community college, and three years in high school. At high school, I was the coordinator of a math club and also the volleyball coach.

JE: As a math major, computer science was a part of the degree, but I went into it knowing that I wanted to teach after graduating, so I didn’t focus on looking into tech careers. To what Steven was saying that he was into tech before it was a hot career, I started becoming interested in tech and in software development as it became a hot career. I had come to London without an exact plan but teaching and tech were both on the table. After three extremely stressful, though fulfilling, years, I quit the last year of high school math and said to myself; ‘I’m leaving the country and starting over’. I came to London and started looking more into tech and started doing a little bit of research into what it was. I started taking two Udemy classes, one on web-development and the other was a Python bootcamp for beginners. In doing my research into tech careers and the tech industry in general, I also found codebar. And just as Steven said, the atmosphere of codebar being geared towards minorities, women and the LGBTQ community made it feel like a really good place to learn tech in a safe place. I think by the time I had met Steven, I had gone to maybe two or three workshops and I was doing the Udemy classes with whatever coach I was given. And then on that fateful Tuesday at Splunk is where I met Steven. I did not know he was looking for a “guinea pig” and I might not have chugged that glass of wine if I did – but maybe it helped, I don’t know!

How was it starting your first commercial tech role?

JE: When I first started (and even before Clear AI), I was like ‘I’ll just learn Python and hope for the best, that should be enough’ because that’s kind of how it’s all advertised. It’s like ‘Python boot camp – at the end of this you’ll be a full stack developer!’. In starting at Clear Academy, I realised that just knowing a language was absolutely not enough. In addition to learning Python, or just a language in general, I had to learn the ins and outs of a startup, global supply chains, and just generally working in a tech team. As for the team itself, right off the bat I was actually quite impressed with the diversity of the company. As a black/Asian female, I’m always very hyper-aware of my surroundings, and the types of people that are around me and that I’m going to be working with. Because I always have to mentally prepare on how people are going to see me versus how I want to be seen.

One thing that I really like about what Steven has done in bringing me in and building the team is that he’s done a really wonderful job of just making me feel like I deserve to be in the company just as much as anyone else does. Because of that, I’ve been able to not have to worry about that. It’s always an extra thing a woman or a black person or any minority has to think of, but I’ve been able to not even have to worry about that at all and been able to solely focus on learning and getting better. Especially since I came into this with zero tech experience – Steven even had to show me how to open a terminal. So, overall it’s been really good.

What advice would you have for anyone that’s wanting learn new tech skills?

JE: From someone who was an absolute beginner, learn how to use the terminal, learn how to use Git and learn how to use GitHub. I had no idea what any of that stuff was. The Python bootcamp pretty much goes straight into just the language and nothing around it. I think learning those base skills I think are very important.

In the vein of diversity, this advice is specifically for minorities and women looking to get into tech. Remember that even though as women and as minorities we have to work harder and do a lot more just to be seen at the same level as our cis-gendered white, straight male peers, we are not lucky to be in the room. We deserve to be in the room. Stick with the learning. Fight through the imposter syndrome and work like you belong there.

SH: To add to that, I would say to people sitting in my seat that we should not forget that we are nothing without the people on our teams, and frankly, they don’t have to be here. We should be thankful that they’re choosing to give their time and energy to us. This isn’t just ‘we’re offering them a job and they should be grateful for it’. We should be grateful that these brilliant people choose to give their talent, their time and their energy to us to build that tech team. Without that, we are nothing.

Steven, what advice would you have for other tech leaders that are looking to build a stronger and diverse tech team?

SH: I mean, there’s a lot you could say and I think I would go back to what I opened with, which is to say, consider this as a system. Because you cannot get away from all of the other moving parts. Building a tech team is not just about your tech stack or about what cool thing you’re building. It’s about what’s the culture of the place you’re building, what’s the structure of the organisation, what are your ways of working, and how do you support the members of your team. Those all come together in one big soup to make a tech team. And above all, for crying out loud, go find people like Jillian. Having that representation in your team is one of the most important things you can do, because everything else flows organically from it.

I would like to make sure that one of the things that the people who’ve read Jillian’s story understand about her is that she recently graduated from the Clear Academy to become a Junior Software Engineer. She’s been working on this for months now and she really did start off not knowing how to open a terminal, and now she’s picking up tickets in our teams and starting to build production code. She has made an amazing journey and amazing jump, in circumstances that are more challenging than they would be for other people. So, I think that deserves recognition.

What’s the best piece of advice you’ve ever received? 

JE: Don’t be scared to ask questions, there are no stupid questions and Google is your friend.

SH: For me, it’s perhaps hard to call this advice so much as learning. My PhD advisor turned to me one point and said; “you know, there’s a lot of things they don’t teach you to become a professor such as you have to start a lab, there’s a lot of things that they didn’t prepare you for, like finance, or balancing your books and making sure that you spend your grant money appropriately, how to how to hire people and how to do all these things which were not obviously central to science”. Yet, these were so important for when he went to build a lab. I realised there and then that there was a whole universe of things outside of  science and tech. I spend a lot of my time as a nerd – reading, building, coding – but you can’t forget the other parts of it. It makes you stronger. The more you invest in it, the better you’ll be.

What is one book that you would recommend?

JE: I feel I know which one Steven is going to say, so I’m going to go with a book that I’ve been listening to which is called Not Nice by Dr. Aziz Gazipura. I think it’s a really good book and it kind of ties this all together for people getting into spaces that they’re brand new to, but realising that they still have a voice and can still speak when they need to.

SH: I think what Jillian was expecting me to say was probably The Phoenix Project by Gene Kim, Kevin Behr, and George Spafford, which is a book I really recommend – that and the sequence of books [The Goal, The Phoenix Project, and The Unicorn Project]. But for this, I think the book I would pick is a book called Range by David Epstein. The reason is that, personally, I’ve always been more of a generalist than a specialist. One of the reasons I didn’t continue in science is because I liked to be a collaborator and I like to work on a wide variety of projects. I wasn’t ever going to be the guy who studied turtles for 40 years and did nothing but turtles, and then when you retire, you find a new kind of turtle to study – I wasn’t going to be that guy! I’ve always felt insecure and bad about that. I’ve had a broader range of skills and I’ve been more of a generalist, and anybody who’s reading this and recognises that insecure feeling, go read Range as it will put your head right.