Random Thoughts

Life Update: New Job!

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Alas, the time has come to move on to a new job. I built some incredible technology at Workfront and helped put the company on a path that will ultimately allow them to build faster and create higher value products & features.

Workfront was a very interesting company to work for. I learned a lot around culture dynamics, what I like in a company, what I definitely don’t like, what types of leaders I want to work with, and so much more. Some of my biggest accomplishments were getting the company onto a microservices model, instituting a data lake capturing time series data, creating an analytics strategy, and creating a robust machine learning and artificial intelligence strategy that will last years to come.

The biggest take away I have from this company is that humans are hard. We got in the way of greatness so many times due to legacy culture and mindsets. There was a constant battle of new blood against old to deliver what was ultimately the best solution. In fact, for the new blood of the company, we started to monitor how long it would take for a strategic shift to happen from first inception. The answer? 6 months.

There came a time when I realized that I needed to be at a faster paced company. So I went on the hunt and found two companies: Zillow and Unsupervised.

Now, everyone knows about Zillow. I interviewed there to be a Principal PM over their customer profile strategies. It was an insanely interesting problem at an unprecedented scale, especially in a market that I’m interested in (real estate). The money was exceptional too (nearly double what I make today) which made it very tempting. However, I interviewed at Unsupervised and it blew my mind.

Unsupervised is an game changing AI company that automatically deliveries insights relative to your objectives – no matter how messy your data. I was evaluating buying their tech at Workfront and I’ll never forget when the CEO was walking us through the deck, there were two architecture slides that blew my mind. I have spent my career building data lakes, platforms, pipelines, and so forth all in the hope of delivering interesting insights. I’ve worked with massive analyst and BI teams who are strategically positioned to find these insights.

Those two slides showed me that they not only do not need ETL of data but that the BI/analyst world will become obsolete. You ingest data into Unsupervised, provide the AI a goal that you want achieve, and it will find anomalies contributing towards or against that goal. The best part? It actually expands on your data set to find additional insights. Sounds crazy? It is, but it’s crazy cool.

It’s an early stage startup. I think I’m employee 30 or 40 and I’ll be helping run product there, providing product management and strategy for the entire lifecycle (sales to customer support). The ability to own a ton at such a young but healthy startup paired with two awesome founders is what sold me.

I’ll be commuting to Colorado weekly until we can find a house to purchase out there. The company is based in Boulder, Colorado but I’ll be floating between Salt Lake City, Boulder, Denver, and Fort Collins (my home town!).

Here’s to rolling the dice again!

College Questions: Sustainability vs profitability

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This weeks college questions took a bit of a turn from the normal route. The question at hand is this: Can companies be eco-friendly/sustainable while also having high growth with profitability?

I’m going to focus on three examples today: New Belgium Brewery, Sun Basket, and Patagonia. So, all focused on consumer but I think it will help convey my sentiment.

In short, the answer is yes. And I would also qualify that as a big yes. If you were to ask me 40 years ago however, I think my answer would be very different. Historically, I would argue that vast majority of the population didn’t care about being environmentally sustainable. In 2019 however, I feel that the number is much higher – if not a vast majority.

There’s a lot of questions and conversations (although polarizing) around climate change and what corporations are going to do about it. I think this pressure comes from a few, over the top perspectives around how “the world is going to end in 12 years” and believing that fate is entirely because of humans. I’ll go on record and say that is the most self-centered, egotistical position we can take on a subject that is highly complex. Do humans contribute? Absolutely. Do I think we’re the primary driver of something like climate change? Possibly. Will we be ok? Probably not. Will the Earth be ok? 100%

The call to arms on doing something about climate change has certainly helped accelerate the desire for consumer goods that are on a more sustainable route. However, I would also say that general innovations in areas, such as automation, as well as higher overall consumer net wealth are the biggest factors pushing it.

There has been quite a historic shift from the middle to upper class in terms of families having upward mobility. This typically means more discretionary spending on goods. If we look at our first example, we can point to a company called New Belgium Brewing

In 1988 , two founders created a company called New Belgium Brewery with their flagship beer Fat Tire. They started to grow the company and continued to expand their beer line. Now, in 2003, they created an in-house sustainability department and also became a member of the “1% for the Planet”. This was entirely led by the individuals within the organization and they continued down that path as the company grew. in 2009, they purchased the largest solar array system at the time in the state of Colorado. Their growth continues today and are, as of 2018, the 4th largest craft brewing company in the world.

The secret to their growth was exceptional branding and a corporate mission focused on sustainability which created a cult-like sensation. One of the biggest cult-like facilitators was an event called Tour de Fat created in 2000 by branding savant Greg Owsley. The idea was to effectively create a mock Tour de France that was allowing individuals to becomes something they’ve always wanted to be – to elevate the individuals in the group. People came dressed up as astronauts, wacky clowns, and the like. Oh, and there was also lots of great beer and music. To this day, that event attracts literally tens of thousands of bikers all around the USA and was one of the primary drivers to accelerated growth. At each of these events, sustainability was a huge focus. One of the big sub-events was a drawing where individuals would submit their name and, if chosen, they would trade in their car for a bike to help reduce carbon emissions. New Belgium Brewery would build a custom bike to spec for the individual and then held a giant ceremony for them during Tour de Fat – elevating individuals who took the brave step toward dramatically changing their life towards sustainability. The overall sentiment around leveraging a bike with like-minded people to create a movement worked spectacularly with continued revenue growth, higher margins, and more members part of the eco-friendly cult.

Ironically enough, New Belgium Brewery had a deep partnership with another awesome company: Patagonia. Patagonia is an extremely eco-focused company with large efforts going towards staving off climate change and releasing their internal annual Sustainability Report each year. They have multiple corporate strategies to help reduce their foot prints that they transparently publish each year. Like New Belgium, they have also create a cult of followers by carving out a niche of “outdoor high fashion clothing” akin to a Gucci or Prada.

With high fashion comes high margins. Pair that with a growing cult following and you net high margins and revenue growth. As of 2013, the company had tripled it’s profits and grown their revenue to over $600M. The common theme keeps coming back to brand appeal and creating a cult that has a common cause. This attracts others because, as humans, we want to socially be part of something.

In more recent times, there is a company called Sun Basket that has come onto my radar. They’re a food delivery service which has historically been very difficult to scale and make profitable. Sun Basket started in 2014 and has taken $143M in funding with an ARR of $275M. From a sustainability perspective, nearly everything they ship is produced from recycled materials and can be recycled. Their food is sustainable by locally sourcing the food relative to their plants (east and west coast).

How are they achieving revenue growth and profitability while also being sustainable in an extremely tough industry? Automation. This company is heavily focused on creating warehouse automation to trim fat, stay lean, and focus on sustainable revenue growth instead of trying to hit the hyper-scale that most startups want to hit. Instead of creating a cult, they’ve created a model that makes the price point attractive enough to consumers while still staying in a somewhat niche market (organic foods).

If I were to throw my own observations at the whole situation, I think what allows companies like these to grow is, ultimately, a thirst from the market paired with highly effective branding. I think it would be awesome to have every company be sustainable, especially larger companies who tend to have a higher footprint. However, transitions away from one energy source to another typically takes ~50 years because of the eco-system they command. I think that in the long run capitalism will push companies to be sustainable because the vast majority of consumer will want it, it will be more cost effective, or it will create a competitive advantage to the company to do so. As the economics of being sustainable continue to drop, it will become a large driver of business decisions instead of largely being perceived as “charity”.

College Questions: AI and Jobs

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If AI takes over and we lose “jobs”, where will people find their meaning, creativity, etc.? Could AI become far enough advanced that we would slide down the food chain? Can AI learn common sense reasoning?

An AI question this week! This will be a bit of a philosophical, rambling post since I’m writing this at 30,000 feet on my way to St. Lucia, so no internet! This means that instead of the normal thought gather and internet searching I do for the 1st hour, I’ll be just be dumping my thoughts.

To start with, there’s a handful of complex questions here that I’ll be breaking out individually. The first is the age-old theory around machines taking over jobs and replacing humans. While I’m a big believer that even strong historical trends are not a good indicator of what will happen in the future, I do believe that, so far, every time that we’ve created a “job replacing machine”, humans end up still finding new work.

If my memory is serving me correctly, there were many times in the past where an invention that resembles replacing a human, humans have typically reacted poorly by doing things like burning the machines, lobbying to stall progress, etc. 

In the long run, it is my belief that jobs end up getting offloaded to machines. I say offloaded specifically because it implies that we task the machines to do the mundane and boring. As we enter the world of ML and AI however, machines are becoming quite amazing at doing complex tasks and exceeding human capabilities. This last point brings up where my thoughts stray from the historical trends.

I’ve seen ML/AI that can craft beautiful music, create incredible novel pieces of art, drive cars, detect cancer at a higher precision than humans, and more. This is definitely worrisome because historically highly skilled professions, such as radiology, had a significant moat around them. The jobs we historically automated away were lower tradesmen jobs. Now, we’re going after the white-collar.

In this new paradigm, what I believe may happen is that humans will exceedingly start to create tools that they can leverage in isolation or concatenation in order to compete strategically. What I don’t think machines will be able to do effectively is a win in the arena of business strategy or where human emotions need to be evoked. There’s a certain level of complexity that is hard for a machine to evoke.

Let’s take consumer branding as an example. What is difficult about really amazing branding is crafting a story that taps into the storyline that potential customers have experienced themselves. Unless the machine has a deep understanding of its consumers from a humanistic perspective, it’s going to be very hard, if not impossible, for it to craft branding at that level. If we were to dive into a specific example, we could look to New Belgium Brewing. Their craft beers attract a type of eco & socially conscious type of crowd based on their designs, the words they use, the events they hold (eg. Tour de Fat), and so much more. It’s been an embedded story in their ethos since day 1. How could a machine be able to replicate that?

Getting back to the 1st core question, I think as jobs are taken away from humans, humans will end up circling back to the arts, macro business strategy, creative fields, or highly complex macro fields. On the last point, this would look something like creating a macro-level vision for humans, such as becoming multi-planetary. A mission like that has most of its purpose rooted in the “why not do it” and the means of getting there is where humans & machines work together to get there.

On the second question of whether humans can slide down the food chain, I think the short answer is yes, this could happen but feels unlikely. It’s a yes because theoretically it would be possible but would require a ton of dependencies. Machines becoming sentient will likely take many decades and, even then, would have limited scope on what they could accomplish. The example Elon Musk usually provides is the email spam problem. If you give a strong enough AI the task to remove all email spam, the deduced logic reasoning would be to get rid of humans because they create the spam in the first place. Now, the means of “removing the humans” would not be a simple effort for the AI. For starters, it would need to tap into key items that could harm humans. However, before that, it would need to know what harming humans look like. Before even that, it needs to know what harm means to a human (eg. verbal vs. physical harm). All of these would be very complex “things” that it would need to learn through training data sets. And sure, someone could theoretically create a training data set for it, but then a whole slew of other questions come up. For example, if the training data set came to the conclusion that using guns to harm humans, how would the AI know how to wield one? How to use one?

Of course, that’s a more physical example. There are likely other examples that could come to fruition, like blowing up nuclear plants (see Student) or infrastructure-related damages. Overall, however, I think that as humans continue to develop AI technology the vast majority will course correct the AI towards a favorable outcome instead of a detrimental one. That’s not to say we shouldn’t be cautious and provide or create guiding mechanisms to ensure that we go down the right path.

Last question: Can AI learn common sense reasoning? I think my answer to this is that it depends on what you mean by “common sense reasoning”. The reason I say that is that common sense is in the eye of the beholder. What is logical and easy to reason through for one is illogical and complex for another.

Let’s take an example of DOTA. A group of researchers has created an AI system to play the game DOTA. This is a MOBA with 5 players versus another 5. You can choose different champions with different types of skill sets. The composition of the team heavily dictates how the game will go. After many, many hours of training the AI, it was able to beat the top-ranked players who had spent years reaching to the top. When interviewed, the players said that it had inhuman-like speeds and took completely different, unpredictable routes to beat them. The playstyle was so effective that it took the DOTA eSports field by storm with many teams adopting elements of the AI play style.

For the AI, those game mechanics were common sense. For humans, they were uncharacteristic of anything they’ve seen. So, the short answer is yes, I think in particular cases that AI can develop common-sense reasoning. However, I think that it will be largely isolated to one problem set and wouldn’t be something completely transferrable. I don’t think you could take elements of logic that the AI learned from one game and easily transfer the same sort of common logic to another game. I’m probably wrong but I’ve yet to see any studies around effective reasoning transfer between training data sets without having to go through a significant amount of model contouring, smoothing, and modifications.

That’s it for this week! I’ll likely not be writing for a week given that I’m traveling but stay tuned as there will be more content coming.