• by William Mougayar
    Venture advisor, 4x entrepreneur, marketer & strategist. I live in Toronto, curate a lot, blog a bit, and help startups.

The Universe Will Try to Stop you from Building a Great Product. Don’t let it.

IMG_20150827_193444_HDRThat quote, by Simon Vallee, product manager at Slack resonated with me at the Product Hunt One Year Anniversary event last Thursday Aug 27th in Toronto. That event was organized by Daryna Kuyla of Deloitte’s Digital Innovation Lab, and attended by over 450 people.

I tweeted that statement along with its corollary that Simon echoed:

If you stop being relentless, you’re screwed.

It is true that most startups initially face a tremendous amount of skepticism about their product, to the point of being often ridiculed, because they are seen as going against all odds. That’s normal, and that is a common starting point. And I would add to the statement that it’s not just building a great product that’s difficult. It’s about getting out into the market.

If everything in a startup was so obvious, the business would look more like a franchise, and not a startup. In a franchise, they hand you the book and processes on how to operate the business, and they supply you with what you need. They even choose your location based on optimal traffic. You just show-up and operate the business.

When bringing a truly innovative product into a new market that doesn’t exist yet, or is ill defined, you are not always competing with other products. Rather, you’re competing with user habits, their time, and whether they believe in your ideas or not. And if you are targeting businesses with your product, companies have already engrained processes that are old, and take time to change.

Even established companies need to continue being relentless. Imagine if UBER caved in to the local cities and taxi cartels objections. Instead, they continued plugging away, and have been relentless in pushing and propagating their agenda and services worldwide, into every area that justified their business case, even if the cities objected to it.

Every year, thousands of new tech startups are founded. Several hundreds will make headlines, a few hundreds will acquire significant users and customers. But only a few dozens will make a lasting difference and stick with our habits, have us either buy their product/service or use their App.

You are fighting the universe, because the universe is complicated and doesn’t want to change. And there will be several barriers and challenges along the way.

As a startup, you are lifting a lot of weight in order to get noticed, to continue plugging and to win. Being relentless means that you never stop, even if you stumble and fall along the way.

What is important is to have the determination to finish. To join these two metaphors, you need to watch this incredible video of athlete Heather Dorniden Kampf who takes a terrible fall during a 600 meters race. Nonetheless, she gets up even more energized and determined to finish the race. How she ends the race is nothing short from spectacular. Trust me and click on this short 2:48 minutes video.

  1. Twain Twain

    Be prepared to dive into the black holes of the startup Universe because, within, you may just see the light.

  2. William Mougayar

    yes, aka “the grinding” phase.

  3. Twain Twain

    JamesHRH wrote something really en pointe the other day which segues with your “It’s not just building a great product that’s difficult. It’s about getting out into the market”. His gold nugget was:

    Apple understands that customers matter more than products.

    Being right but unadopted = fail.

    Being better but unadopted = fail.

    Being adopted = success.


    CBInsights recently published this obituary on deadpool startups:

    * https://www.cbinsights.com/blog/startup-failure-post-mortem/

    That list includes startups that may have had great products.

    The market, though, is a Black Hole. There’s a LOT of missing information which makes it hard to navigate. The information we do have is from patches of territory which may have been lit up before, e.g. from research conducted by user experience & product people, from following the examples of the big techcos (so we all know to build for mobile first, for example), from the big market research & strategy consultancy co’s and maybe from avoiding the missteps of startups that tried to do something similar to what we’re doing.

    Still, there’s a…A LOT OF MISSING INFORMATION. That presents huge opportunities.

    I read this article the other day on dark matter and apparently it could be up to 80% of the information that we need to piece together for how our Universe works:

    * http://www.wired.com/2015/08/dark-matter-may-complex-physicists-thought

    Now, in Machine Intelligence, the fathers of AI like Geoff Hinton of Google have started to refer to “Dark Knowledge” (YouTube video, 1+ hour long: https://www.youtube.com/watch?v=EK61htlw8hY).

    He applies it in two use cases:

    (1.) Model compression: using a simpler model with fewer parameters to match the performance of a larger model.

    (2.) Specialist Networks: training models specialized to disambiguate between a small number of easily confuseable classes.

    It’s really well-known in AI circles that we need whole new models for solving the Natural Language problems so that’s what the Googles, Baidus, FBs, IBM Watson are all sinking capital into.

    Meanwhile, Princeton neuroscientist Michael Graziano put forward an “Attention Schema” for understanding a huge chunk of information (another Black Hole) we don’t currently have about how our minds work and how we learn and classify information:

    * http://aeon.co/magazine/psychology/is-consciousness-an-engineering-problem/

    He notes that the way we’ve been approaching Machine Intelligence has been in the absence of an internal model. That is the case. Without exception, the AI of the big techco’s focus on the already generated big data from external sources. They pull it in and then try to correlate that information into clusters, and compound any pre-existing issues with the data in the process.

    Let’s just say that my logo has the colors of the EM spectrum for good reasons. I dived into the Big Black Hole and made those “Leaps of Faith for the future” years before the fathers of AI started talking about “dark knowledge”, the neuroscientists started proposing “attention schemas” and MIT quantum physicist Max Tegmark postulated for “Perceptronium, the most general substance that can feel subjectively self-aware.”

    While the academics think and philosophize, I’ve already BUILT a commercial system capable of measuring consumer perceptions which consumers+brand companies+advertisers+more need and that also solves the hardest problem in Machine Intelligence via:

    (1.) A simpler model with fewer parameters;

    (2.) Training the system to be able to classify and disambiguate between easily confusable data.

    Instead of an “attention schema”, I made an attenuation compass (leveraging my Chinese heritage).

    So in years ahead…We’ll be able to navigate those Black Holes much much better because the information will be visible and lit up by my system.

    It WILL be adopted just as 5-star ratings, the Periodic Table and DNA have been universally adopted because my system’s just as easy and vital as ABC123.

    [Yes, Google’s move into Alphabet is very very funny because Google Ventures’ Head of EMEA invited me to a meeting back in 2012. The conversation went like this:

    Googler: Who’s your target audience?

    Twain: First adopters?

    Googler: 18-25, ABC, a few smart devices–

    Twain: No, 6 year olds who are growing up with tablets and hoping someone like me will invent cool, smart stuff.



    Googler: I get the impression there’s a LOT MORE to your system that you haven’t shown me and that it’s for a LOT of people to use. You’ve obviously thought about it. When you feel more comfortable sharing more, the door is always open for you.]

    Hmmn……well……indeedy……I only shared 0.000000000000000001% of what I was building.

    The Universe, the grind, under radars and all that.

    Google, Baidu, FB, IBM Watson, Amazon et al are fighting over the 20% of the visible information Universe.

    Meanwhile, I built a spaceship that deep dives into the other 80%: the currently invisible information — which can only be lit up by my system.

    Yes, it WILL be adopted just as 5-star ratings, the Periodic Table and DNA have been universally adopted because my system’s just as easy and vital as ABC123.

    And as my brother said about me: “You’ve always been the driver.”

    “Grind is…GREAT!” (Gekko, eat your heart out.)

  4. William Mougayar

    Wow. Thanks Twain. Great add-on.

  5. Twain Twain

    Here are 5 personal examples of overcoming “the Universe will try to stop you building a great product”:

    (1.) Incubator directed me to make a “me too” variant of Disqus instead of my product. Despite being nominated by the course leader as President of graduating class, I decided to drop out rather than build anything I don’t believe in.

    I’m an “all or nothing” person and have been since I was a kid.

    (2.) When trying to source top developers with experience of rating systems — which underpins how content recommendations and Machine Intelligence works — I found an echo chamber of unimaginative, “This is the way it’s always been done, so let’s carry on doing it” (despite everyone knowing it’s deeply, deeply flawed):

    * http://www.quora.com/Is-there-a-better-alternative-to-the-5-star-rating-system

    After that, I saw some of Stanford’s best Comp. Sci. minds do what Steve Jobs would call “incremental improvement” rather than make the leaps of imagination and technical execution the systems need, for the data and machines to be a lot more intelligent.

    (3.) Two huge companies sent their lawyers to try to prevent me from filing that great logo of mine as a trademark. We reached a happy agreement and the trademark’s registered.

    (4.) London ecosystem is a lot more conservative, has fewer product+engineering skills cf SV and NY and is less conducive for founders. If you’re an inventor too, it’s worse because the bar for what investors want before they’ll invest is ridiculously high (ref: David Cohen’s observations, “They like to torture founders”) .

    (5.) I’m a woman. There are all sorts of gender biases that get directed my way.

    Nevertheless…my system and method is patent published. My trademarks are registered, including ones that are even greater than the main brand name.

    Out of necessity, I had to keep it under-radars up to now.

    My system re-frames not only the last 80 years of 5-star rating systems which has limited the data, recommendations and intelligence of the machines, it re-frames economics, mathematics and linguistics from ever since we first recorded our human experiences and thoughts.

    Why did I do it and what keeps me driving forward?

    My Dad died a few years ago following a coma. It set me on a path to “Do something meaningful with my life” (rather than climb the corporate ladder; I’d been promoted into CEO-Chairman’s Office of UBS investment bank by my mid-20s anyway so had already gained insights from those experiences).

    So I decided to build a system to do two things, in tandem:

    (1.) Make sense of the meaning in us and our data => implications for Natural Language and Machine Intelligence.

    (2.) Understand why we buy => solve a key missing piece of signal:noise and economics.

    It occurred to me that the signal:noise in my Dad’s brain was similar to the signal:noise across the Global Brain that is the Web. It also occurred to me that there was a need to ATTENUATE the signals and that the tools to do so coherently DIDN’T EXIST.

    Big Data claims to be able to solve signal:noise but, as a maths graduate whose Econometrics project at university involved data modeling the Tiger Economies and worked in a hedge fund where we applied Machine Learning to do portfolio asset allocation, I’m fairly aware of what Big Data can and can’t do.

    The ability to quantify (correlate) is not the same as the ability to qualify (measure causation)— even if mathematicians would confer qualification to what is actually a quantification event, like so: “We’re 95% CONFIDENT that the data falls within these bounds.”

    But what if the bounds are amiss or inadequate? What if the Euclidean, Descartian and Bayesian frameworks we’ve used aren’t sufficient for qualitative analysis — even if they are, undeniably, set up for quantitative analysis?

    Sure, the Big Data tools and their Euclidean-Descartian-Bayesian frameworks can detect and quantify the 20% of visible information that’s already lit up. However, they may not be able to qualify that 20% and, further still, they may not be able to detect and quantify+qualify the other 80% of as-yet invisible information.

    So, there was this Big Black Hole of unknowns in my Dad’s brain which the neurosurgeons couldn’t measure because of the limitations of the existing tools.

    And, in the same way, the limitations of existing tools for the Global Brain also means there’s a Big Black Hole of unknowns that haven’t yet been measured.

    Now, as I wrote above, I’m an “all or nothing” type.

    So I applied every atom of intelligence, experience and fearlessness in me to quantum fission+fusion a system and method that MAKES SENSE.

    In tandem, I put hands to code and heart to drive. Fearlessness because everyone else thinks 5-stars and Euclid-Descartes-Bayes “sont suffice” and I don’t believe that at all.

    Black Holes and their as-yet unknowns are where to be. It’s where the important information and our intelligence is. It’s what my spaceship (system) is built for.

  6. William Mougayar

    You are perserving.
    One key thing amidst this is to have a great product, as it does make things a little easier.

  7. Twain Twain

    My personal logo reflects how I think+do, walk+talk, show+tell.

    It also indicates the DNA my system has.

    It’s how I see the Universe of information and intelligence in humans and in machines.